eastern africa power pool (eapp) and east african community (eac)

EASTERN AFRICA POWER POOL (EAPP) AND EAST AFRICAN

COMMUNITY (EAC)

REGIONAL POWER SYSTEM MASTER PLAN

AND GRID CODE STUDY

FINAL MASTER PLAN REPORT

VOLUME I

01 - Introduction 02 - Demand Forecast

(WBS 1100) 03 - Generation Supply Study &

Planning Criteria (WBS 1200)

04 - Supply-Demand Analysis & Project Identification (WBS 1300)

May 2011

SNC LAVALIN INTERNATIONAL INC. in association with

PARSONS BRINCKERHOFF

PREFACE

The objective of the present study is to identify regional power generation and interconnection projects in the power systems of EAPP and EAC member countries in the short‐to‐long term. The study also aims at developing a common Grid Code (Interconnection Code) in order to facilitate the integrated development and operations of the power systems of the member countries.

The study further aims at contributing to the institutional capacity building for the EAPP and EAC through training of counterpart staff. The development of institutional capacity will enable EAPP/EAC to implement the subsequent activities, including the updating of both the Master Plan and the Interconnection Code.

This study covers the following countries in alphabetical order: Burundi, Djibouti, Democratic Republic of Congo, Egypt, Ethiopia, Kenya, Rwanda, Sudan, Tanzania and Uganda.

The Master Plan Report has been organized according to the following structure:

Volume Section Executive Summary

Volume I

01 – Introduction 02 ‐ Demand Forecast (wbs 1100) 03 ‐ Generation Supply Study & Planning Criteria (wbs 1200)

04 ‐ Supply‐Demand Analysis & Project Identification (wbs 1300)

Volume II 05 ‐ Transmission Network Study (wbs 1400) 06 ‐ Interconnection Studies (wbs 1500) 07 ‐ Regional Market Operator Location (wbs 2900)

Volume III 08 ‐ System Studies For Expansion Plan (wbs 2100)

Volume IV

09 ‐ Environment Impact Assessment (wbs 2200) 10 ‐ Cost Estimates And Implementation Schedules (wbs 2300) 11 – Financial & Economic Evaluation – Risk and Benefits (wbs 2400/2500) 12 ‐ Development and Investment Plan (wbs 2600) 13 ‐ Institutional and tariff aspects (wbs 2700) 14 – Project Funding (wbs 2800) 15 – Conclusions

Appendix A TOR, Cost Estimates and Implementation Schedules for Feasibility Studies for Projects identified in the first five years

Appendix B

Part I – WBS 1100 Demand Forecast Part II – WBS 1200‐1300 Gen. Supply Study – Supply Demand Analysis Part III – WBS 1400‐1500 Transm. Network – Interconnection Studies Part IV – WBS 2600‐2700 Investment Plan – Institutional & Tariff Aspects

Final Master Plan Report Acronyms and Abbreviations May 2011

EAPP/EAC Regional PSMP & Grid Code Study

Acronyms and Abbreviations A AC Alternate Current AEO Annual Energy Outlook AfDB African Development Bank AICD Africa Infrastructure Country Diagnostic ARIMA Autoregressive Integrated Moving Average ARR Annual Required Revenue Avg Average B BADEA Arab Economic Development Bank in Africa bbl Oil barrel BCR Benefit/Cost Ratio BR Burundi C CAPEX Capital Expenditure CBEMA Computer and Business Equipment Manufacturers’ Association CCGT Combined Cycle Gas Turbine - Thermal Power Plant CDM Clean Development Mechanism CEO Chief Executive Officer CF Capacity Factor CIRR Commercial Interest Reference Rate CKT Circuit CO2 Carbon Dioxide COR Composite Outage Rate CPI Consumer Price Index D DB Djibouti DC Direct Current DC Democratic Republic of Congo DGHER General Directorate for Hydropower and Rural Electrification DOE Department of Energy (USA) DRC Democratic Republic of Congo DSCR Debt Service Coverage Ratio E EAC East African Community EAPMP East African Power Master Plan Study EAPP Eastern Africa Power Pool EdD Électricité de Djibouti EDF Électricité de France EEHC Egyptian Electric Holding Company EEPCo Ethiopia Electric Power Corporation



EETC Egyptian Electricity Transmission Company EG Egypt EIA Energy Information Administration EIC Existing Interconnections EIJLLST Egypt, Iraq, Jordan, Libya, Lebanon, Syria and Turkey EIRR Economic Internal Rate of Return EMF Electro-Magnetic Field EMP Environmental Management Plan ENPTPS Eastern Nile Power Trade Program Study ENPV Economic Net Present Value ENTRO Eastern Nile Technical Regional Office EPC Engineering Procurement and Construction EPCM Engineering Procurement and Construction Management Esc. Escalation ESIA Environmental and Social Impact Assessment ET Ethiopia EU European Union F FC Fictitious Company FDI Foreign Direct Investment FIRR Financial Internal Rate of Return FNPV Financial Net Present Value FOR Forced Outage Rate FS Feasibility Study FttH Fibre-to-the-Home G GCI Global Competitiveness Index GDP Gross Domestic Product GHG Green House Gases GNI Gross National Income GoE Government of Ethiopia GT Gas Turbine GTP Growth and Transformation Plan H HFO Heavy Fuel Oil HPP Hydro Power Plant HVAC High Voltage Alternate Current HVDC High Voltage Direct Current I ICNIRP International Commission of Non-Ionizing Radiation Protection ICS Interconnected System (Ethiopia) ICT Information and Communication Techonology IDC Interest during Construction IDO Industrial Diesel Oil



IFC International Financial Corporation IMF International Monetary Fund Inst. Cap. Installed Capacity IP Internet Protocol IPO Initial Public Offering IPP Independent Power Producer IRR Internal Rate of Return IT Information Technology J JMP Joint Multipurpose Project K KenGen Kenya Electricity Generation Company KETRACO Kenya Electricity Transmission Company Limited KPLC Kenya Power and Lighting Company Ltd KTCIP Kenya Telecommunications Infrastructure Project KY Kenya L LAP Libyan African Portfolio LCEMP Least Cost Electricity Master Plan LCPDP Least Cost Power Development Plan LD Liquidated Damage LDC Load Duration Curve LDCs Least Developed Countries Level of Prep. Level of Preparedness LFO Light Fuel Oil LNG Liquefied Natural Gas LOLE Loss of Load Expectation LOLP Loss of Load Probability LRMC Long Run Marginal Cost LRO Light Residual Oil LSD Low-Speed Diesel Engine LTPSPS Long-Term Power System Planning Study LVL Level M MAED Model for Analysis of Energy Demand Max Maximum MD Maximum Power Demand Min Minimum MINIFRA Rwanda Ministry of Infrastructure MOU Memorandum of Understanding MoWR Ministry of Water and Energy MP Master Plan MPIP Medium-term Public Investment Plan MSD Medium-Speed Diesel Engine



N NBI Nile Basin Initiative NEC Sudan National Electricity Corporation NELSAP Nile Equatorial Lakes Subsidiary Action Program NG Natural Gas NGP National Generation Plan Nom. Cap. Nominal Capacity NPV Net Present Value O OCGT Open Cycle Gas Turbine - Thermal Power Plant ODA Official Development Assistance OECD Organization of Economic Cooperation and Development OLADE Organización Latinoamericana de Energía (Latin American Energy

Organization) OLTC On-Load Tap Changers O&M Operation and Maintenance ONRD Office of Natural Resources Damage OPEC Organization of the Petroleum Exporting Countries OPEX Operating Expenditure OPTGEN Optimal Generation (Planning Model) P PF Plant Factor PPA Power Purchase Agreement PPE Personal Protective Equipment PSIP Power Sector Investment Plan PSMP Power System Master Plan Study pu Per Unit R RALF Regression Analysis Load Forecast RCC Regional Coordination Center RECO Rwanda Energy Corporation Ref Reference REGIDESO Régie de production Distribution d’Eau et d’Electricité RFP Request for Proposal RGP Regional Generation Plan RMO Regional Market Operator RMOC Regional Market Operation Center RoC Return on Capital RoCE Return on Capital Employed RoE Return on Equity ROR Run-Of-River RTL Rwandatel S.A. RW Rwanda RWASCO Rwanda Water Supply Corporation



S SAPP Southern African Power Pool SCS Self-Contained System (Ethiopia) SD Sudan SDDP Stochastic Dual Dynamic Programming SEACOM SEEE Society of Electrical and Electronics Engineers SIL Surge Impedance Loading SINELAC Société Internationale d’Électricité des Pays des Grands Lacs SNEL Société Nationale d’Électricité – République Démocratique du Congo SPV Special Project Vehicle SRMC Short Run Marginal Cost SSEA Strategic/Sectoral, Social and Environmental Assessment of Power

Development Options in the Nile Equatorial Lakes Region STPP Steam Thermal Power Plant SVC Static Var Compensator T TANESCO Tanzania Electric Supply Company Ltd TOR Terms of Reference TPP Thermal Power Plant TSO Transmission System Operator TZ Tanzania U UETCL Uganda Electricity Transmission Company UEGCL Uganda Electricity Generation Company Limited UG Uganda UIC Unlimited Interconnections UN United Nations UNCTAD United Nations Conference on Trade And Development USBR United States Bureau of Reclamation UTL Uganda Telecom Ltd W WACC Weighted Average Cost of Capital WB World Bank WBS Work Breakdown Structure WEF World Economic Forum Y yr Year

Final Master Plan Report Introduction May 2011


SECTION 1

Introduction

Final Master Plan Report 1-1 Introduction May 2011


1 INTRODUCTION

1.1 Study Objectives The objective of the study is to identify power generation and interconnection projects, at Master Plan level, to interconnect the power systems of EAPP and EAC countries in short-to-long term. The study also aims at developing common Transmission Interconnection Code in order to facilitate the integrated development and operations of the power systems of EAPP and EAC countries.

The study further aims at contributing to the institutional capacity building for the EAPP and EAC staff through training of counterpart staff. The development of institutional capacity will enable EAPP / EAC to implement the subsequent activities, including the updating of both the Master Plan and the Grid Code reports.

This study covers the following countries in alphabetical order: Burundi, Djibouti, Democratic Republic of Congo, Egypt, Ethiopia, Kenya, Rwanda, Sudan, Tanzania and Uganda.

1.2 Project Background On 24 February 2005, the Energy Ministers from seven (7) Eastern Africa countries, namely: Burundi, Democratic Republic of Congo (DRC), Egypt, Ethiopia, Kenya, Rwanda and Sudan signed an Inter-Governmental Memorandum of Understanding (MOU) for the establishment of the Eastern Africa Power Pool (EAPP). The signature of the MOU was followed by the signature of an Inter-Utility MOU by the Chief Executive Officers (CEOs)/Managing Directors of the countries’ nine (9) Power Utilities. This event heralded the formal launching of EAPP.

The EAPP member utilities are: REGIDESO (Burundi), SNEL (DRC), EEHC (Egypt), EEPCo (Ethiopia), KenGen and KPLC (Kenya), ELECTROGAZ (Rwanda), NEC (Sudan) and SINELAC (DRC, Rwanda and Burundi).

In further developments, EAPP has been adopted by the 11th Summit of the Common Market for Eastern and Southern Africa (COMESA) Authority of Heads of State and Government held in Djibouti from 15-16 November 2006 and has been considered as COMESA’s Specialized Institution for Electric Power.

Given that some member countries of EAC overlap with those of EAPP, these two institutions signed an MOU on September 2009, whereby EAPP and EAC agree to jointly implement the present Power Master Plan and Grid Code Study for which EAPP is designated as the Implementation Agency. In this document when reference is made to “EAPP countries” it is understood that this designates the group of ten countries mentioned above.

Countries in the region, by and large, have been planning and implementing the development of their power system in an isolated manner with a view to satisfying the national demand growth. Bilateral power exchange agreements exist between some countries in the Region. However, the volume of power exchange is not significant and exporting parties have frequently been unsuccessful in their commitments to deliver the power in accordance with their contractual obligations because of deficits in their systems.

The existing power interconnection projects include:

• DRC, Burundi, and Rwanda interconnected from a jointly developed hydro power station Ruzizi II, (capacity 45 MW) operated by a joint utility [SOCIETE D’ELECTRICITE DES PAYS DES GRAND LACS (SINELAC)];



• Cross-border electrification between Uganda and Rwanda, Tanzania and Uganda, and Kenya and Tanzania;

• Kenya – Uganda interconnection; and

• Egyptian power system interconnection through Libya to other Maghreb countries and Southern Europe; and through Jordan to Eastern Mediterranean.

Other ongoing power interconnection systems are shown in:Table 1-1

Power trading through common planning and implementation of regional generation and interconnection projects has been identified as one important strategy for tackling the problems associated with power supply shortages, low access, high cost and poor supply reliability. However, at present, the power interconnections within the region are limited for realization of shared benefits that would be generated through integrated development of their power systems.

Presently, Kenya, Tanzania and Uganda under the auspices of the East African Community (EAC), are developing plans to (i) interconnect and strengthen their power systems in order to share power supplies, and (ii) further extend the power system interconnections to countries outside EAC countries. The Master Plan which was finalized in March 2005 has identified regional generation and transmission projects for integrated development.

A series of studies have been completed in the last 5 years that cover opportunities for cross-border interconnections in the region. These include the EAPMP1, SSEA2, ENTRO3, Ethiopia-Djibouti Interconnection, and the 2004 World Bank Scoping Study4. Implementation planning is going ahead for the interconnection of the national grids for the five equatorial Lakes countries (Burundi, Kenya, Uganda, DRC, and Rwanda).

1 East Africa Power System Master Plan Study (Uganda, Kenya, Tanzania) 2 Stategic/Sectoral, social and Environmental Assessment of Power Development Options (Burundi, Eastern DRC, Kenya, Rwanda, Tanzania, Uganda) 3 Eastern Nile Power Trade Study (Egypt, Sudan, Ethiopia) 4 Joint UNDP/WB Energy Sector Management Assistance Program (ESMAP), Opportunities for Power Trade in the Nile Basin, Final Scoping Study, January 2004



Table 1-1 Ongoing Interconnection projects

From To Type / Length

Capacity (MW)

Earliest Year in

OperationStatus Comments

Tanzania Kenya 400 kV

2 circuits 260 Km

1520 2015

Ongoing FS, detailed design and tender

documents preparation

Bidding for line construction may start at the end of 2011.

Rusumo Rwanda 220 kV 1 circuit 115 Km

320 2015

FS completed Lines associated to the Rusumo Falls HPP connecting the project with the grids of Tanzania, Rwanda and Burundi. Rusumo Burundi

220 kV 1 circuit 158 Km

280 2015

Rusumo Tanzania220 kV 1 circuit 98 Km

350 2015

Ethiopia Kenya 500 kV-DC

bipole 1120 Km

2000 2016

Design and tender document preparation

study to start early 2011

New design study aims at highly optimistic completion of phase I (1000 MW) of the project by 2013 and phase II upgrade to 2000 MW by 2019.

Ethiopia Sudan 500 kV

4 circuits 570 Km

3200 2016 FS completed




Capacity (MW)

Earliest Year in

OperationStatus Comments

Egypt Sudan 600 kV-DC

bipole 1665 Km

2000 2016 FS completed

Uganda Kenya 220 kV

2 circuits 254 Km

300 2014 Under construction Runs from Lessos substation in Kenya to Bujagali substation passing through Tororo substation in Uganda, duplicating the existing 132kV line.

Uganda Rwanda 220 kV

2 circuits 172 Km

250 2014

Detailed and Tender Documents

preparation study starts in 2011

Line from Mbarara to Mirama (border Uganda) to Birembo/Kigali (Rwanda)

Rwanda DRC 220 kV 1 circuit 68 Km

370 2014 Under construction

Line between new substation at Kibuye Methane Gas plant in Rwanda and Goma (DRC), thus completing the loop around lake Kivu.

DRC Burundi 220 kV 1 circuit 105 Km

330

Expected in

2014

FS, detailed engineering and

tender documents preparation study to

start early 2011

Line from future substation Kamanyola/Ruzizi III (DRC) to Bujumbura (Burundi). Study Includes 220kV line between a new

substation in Bujumbura to Kiliba (DRC).

Burundi Rwanda 220 kV 330 2016 FS update to start early 2011

Line Rwegura (Burundi) – Kigoma (Rwanda), previous FS recommended 110kV. Feasibility Study update to re-examine 220kV option and re-route line to feed intermediate locations.



1.3 Content and objectives of the master plan report This Master Plan Report provides the findings from the Regional Power System Master Plan. The Interconnection Code (Grid Code) is part of a separate report.

The Master Plan first discusses all the input data necessary for the planning exercise: Demand Forecast (WBS 1100), Generation Supply analysis, including existing and future thermal, hydro and renewable energy projects, and planning criteria (WBS 1200). The existing transmission network data and models are compiled in WBS 1400 and common planning criteria and basic unit costs are developed for the candidate interconnection projects in WBS 1500.

A preliminary identification of the regional projects (generation and interconnections) is performed including a supply-demand analysis for each country and a regional interconnection plan is developed under WBS 1300. An estimation of the regional benefits of different scenarios is also performed.

Detailed system studies for each country and reinforcement needs are identified in WBS 2100 while other aspects of the projects such as the environmental impacts (WBS 2200), Cost Estimates (2300), Financial-Economic Analysis and risk assessment (WBS 2500) are presented in the report.

Finally an investment plan for the identified interconnection projects is developed in WBS 2600 and the analysis of institutional and tariff aspects as well as project funding requirements are included in WBS 2700 and WBS 2800 respectively.

An analysis of the requirements and recommendation for the location of the Regional Market Operator (RMOC) – RCC is carried out under WBS 2900.

Appendix A contains for the initial phase of development (2013-2017) the TOR, cost estimates and implementation schedules for the indentified projects.

Appendix B contains specific information and tables for particular sections of the report.



1.4 Organization of the report

EXECUTIVE SUMMARY

MAIN REPORT

1 INTRODUCTION

2 DEMAND FORECAST (1100)

3 GENERATION SUPPLY STUDY AND PLANNING CRITERIA (1200)

4 SUPPLY-DEMAND ANALYSIS AND PROJECT IDENTIFICATION (1300)

5 TRANSMISSION NETWORK STUDY (1400)

6 INTERCONNECTION STUDIES (1500)

7 REGIONAL MARKET OPERATIONS CENTRE LOCATION (2900)

8 SYSTEM STUDIES FOR EXPANSION PLAN (2100)

9 ENVIRONMENTAL IMPACT ASSESSMENT (2200)

10 COST ESTIMATES AND SCHEDULES (2300)

11 FINANCIAL AND ECONOMICAL EVALUATIONS – Risks and Benefits (2500)

12 DEVELOPMENT AND INVESTMENT PLAN (2600)

13 INSTITUTIONAL AND TARIFF ASPECTS (2700)

14 PROJECT FUNDING (2800)

15 CONCLUSIONS

APPENDICES

APPENDIX A – TOR, Cost Estimates and Implementation Schedules for Feasibility Study for Projects Identified for the Initial Phase Development (2013-2017)

APPENDIX B – General Appendices

Final Master Plan Report WBS 1100 Demand Forecast May 2011


SECTION 2

Demand Forecast WBS 1100



TABLE OF CONTENTS

1. DEMAND FORECASTING: GENERAL PRINCIPLES .............................................. 1-1 1.1 The Need for Demand Forecasting ............................................................................ 1-1 1.2 Demand Forecasting Techniques ............................................................................... 1-1

2. ADOPTED APPROACH TO DEMAND FORECASTING ........................................... 2-1 2.1 Data Collection ........................................................................................................... 2-1 2.2 Approach to Reviewing the Existing National Demand Forecasts .............................. 2-1 2.3 PB Independent Demand Forecasts .......................................................................... 2-2

3. REVIEW OF EXISTING NATIONAL DEMAND FORECASTS .................................. 3-1 3.1 Burundi ....................................................................................................................... 3-1 3.2 Djibouti ........................................................................................................................ 3-2 3.3 East DRC .................................................................................................................... 3-7 3.4 Egypt ........................................................................................................................ 3-10 3.5 Ethiopia ..................................................................................................................... 3-12 3.6 Kenya ....................................................................................................................... 3-14 3.7 Rwanda .................................................................................................................... 3-18 3.8 Sudan ....................................................................................................................... 3-20 3.9 Tanzania ................................................................................................................... 3-22 3.10 Uganda ..................................................................................................................... 3-23

4. INDEPENDENT PB DEMAND FORECASTS ............................................................ 4-1 4.1 Burundi ....................................................................................................................... 4-1 4.2 Djibouti ........................................................................................................................ 4-4 4.3 DRC ............................................................................................................................ 4-6 4.4 Egypt .......................................................................................................................... 4-8 4.5 Ethiopia ..................................................................................................................... 4-10 4.6 Kenya ....................................................................................................................... 4-12 4.7 Rwanda .................................................................................................................... 4-15 4.8 Sudan ....................................................................................................................... 4-18 4.9 Tanzania ................................................................................................................... 4-21 4.10 Uganda ..................................................................................................................... 4-23



LIST OF TABLES Table 3-1 Extended NELSAP Demand Forecast for Burundi (Base Case) ..................... 3-2 Table 3-2 LCEMP Demand Forecast (Base Case) .......................................................... 3-4 Table 3-3 LCEMP Demand Forecast (High Case) ........................................................... 3-5 Table 3-4 LCEMP Demand Forecast (Low Case) ............................................................ 3-6 Table 3-5 Extended NELSAP Demand Forecast for East DRC (Base Case) .................. 3-8 Table 3-6 Extended NELSAP Demand Forecast for East DRC (High Case) ................... 3-9 Table 3-7 Extended NELSAP Demand Forecast for East DRC (Low Case) ................. 3-10 Table 3-8 Extended EEHC Demand Forecast for Egypt (Base Case) ........................... 3-12 Table 3-9 Extended EEPCO Demand Forecast for Ethiopia (Base Case – Moderate I

Scenario) ....................................................................................................... 3-14 Table 3-10 Extended 2008 LCPDP Demand Forecast for Kenya (Base Case) ............... 3-16 Table 3-11 Extended 2009 LCPDP Demand Forecast (Base Case) ............................... 3-17 Table 3-12 Extended NELSAP Demand Forecast for Rwanda (Base Case) ................... 3-19 Table 3-13 Extended LTPSP Demand Forecast for Sudan (Base Case) ........................ 3-21 Table 3-14 Extended PSMP Demand Forecast for Tanzania (Base Case) ..................... 3-23 Table 3-15 PSIP Demand Forecasts for Uganda (Base, High and Low Cases) .............. 3-24 Table 4-1 PB Base, High and Low Demand Forecast for Burundi ................................... 4-2 Table 4-2 PB Base, High and Low Demand Forecast for Djibouti ................................... 4-4 Table 4-3 RSWI Base, High and Low Demand Forecast for East DRC ........................... 4-6 Table 4-4 PB Base, High and Low Demand Forecast for Egypt ...................................... 4-8 Table 4-5 PB Base, High and Low ICS Demand Forecast for Ethiopia ......................... 4-10 Table 4-6 PB SCS Demand Forecast for Ethiopia ......................................................... 4-12 Table 4-7 PB Base, High and Low Demand Forecast for Kenya ................................... 4-13 Table 4-8 PB Base, High and Low Demand Forecast for Rwanda ................................ 4-16 Table 4-9 PB Base, High and Low Demand Forecast for Sudan ................................... 4-19 Table 4-10 PB Base, High and Low Demand Forecast for Tanzania .............................. 4-21 Table 4-11 PB Base, High and Low Demand Forecast for Uganda ................................. 4-23

LIST OF FIGURES Figure 4-1 PB Peak Demand Forecast for Burundi (MW) ............................................. 4-3 Figure 4-2 PB Sent Out Generation Forecast for Burundi (GWh) ................................. 4-3 Figure 4-3 PB Peak Demand Forecast for Djibouti (MW) ............................................. 4-5 Figure 4-4 PB Sent Out Generation Forecast for Djibouti (GWh) ................................. 4-5 Figure 4-5 RSWI Peak Demand Forecast for East DRC (MW) ..................................... 4-7 Figure 4-6 RSWI Sent Out Generation Forecast for East DRC (GWh) ......................... 4-7 Figure 4-7 PB Peak Demand Forecast for Egypt (MW) ................................................ 4-9 Figure 4-8 PB Sent Out Generation Forecast for Egypt (GWh) .................................... 4-9 Figure 4-9 PB ICS Peak Demand Forecast for Ethiopia (MW) ................................... 4-11 Figure 4-10 PB ICS Sent Out Generation Forecast for Ethiopia (GWh) ........................ 4-11 Figure 4-11 PB Peak Demand Forecast for Kenya (MW) .............................................. 4-14 Figure 4-12 PB Sent Out Generation Forecast for Kenya (GWh) .................................. 4-14 Figure 4-13 PB Peak Demand Forecast for Rwanda (MW) ........................................... 4-17 Figure 4-14 PB Sent Out Generation Forecast for Rwanda (GWh) ............................... 4-17 Figure 4-15 PB Peak Demand Forecast for Sudan (MW) ............................................. 4-20 Figure 4-16 PB Sent Out Generation Forecast for Sudan (GWh) ................................. 4-20 Figure 4-17 PB Peak Demand Forecast for Tanzania (MW) ......................................... 4-22 Figure 4-18 PB Sent Out Generation Forecast for Tanzania (GWh) ............................. 4-22 Figure 4-19 PB Peak Demand Forecast for Uganda (MW) ........................................... 4-24 Figure 4-20 PB Sent Out Generation Forecast for Uganda (GWh) ............................... 4-24

Final Master Plan Report 1-1 WBS 1100 Demand Forecast May 2011


1. DEMAND FORECASTING: GENERAL PRINCIPLES A demand forecast is the prediction of demand for power (MW) and energy (GWh) into the future. The maximum power demand (MD) in a period is known as the peak demand, and this is usually the headline figure which is quoted when developing demand forecasts. It should be noted however, that in electrical systems with predominantly thermal capacity, it is more important for planning purposes to know the peak demand rather than the amount of electrical energy required, since the peak demand often sets the capacity expansion goal. On the other hand, for systems with large amounts of hydro-electric capacity, it is equally important to know the level of energy demand, as these systems may have energy limitations.

It is thus the usual practice in any detailed demand forecast to predict the level of energy demand first, and then derive the peak demand using appropriate load and coincidence factors.

1.1 The Need for Demand Forecasting A demand forecast is a primary requirement for electricity planning studies. Demand forecasts are needed for:

• Generation planning,

• Transmission planning,

• Distribution planning,

• Financial planning,

• Feasibility studies,

• Pricing and tariff setting, and,

• Operational planning (short-term).

Different demand forecasts are required for the short, medium or long term and for different levels of the system (e.g. generation, transmission substations, distribution substations and at consumer terminals).

Rigorous demand forecasting may be necessary for a number of reasons, such as:

• It is often essential for outside parties (e.g. bilateral and multilateral financiers, private sector investors and project shareholders) to be convinced of the reasonableness of future load growth and the corresponding investment plan before making a financial commitment.

• Large consumers are often more optimistic about future growth than is justified by the prevailing economic climate. This may result in an over-estimate of load with a consequent over-investment.

• In markets where demand is approaching saturation, judgements formed from buoyant market growth in the past may not be a good guide to growth in the future.

• Utilities will frequently over-estimate demand allowing for the time required to secure finance and the necessary project construction approvals.

1.2 Demand Forecasting Techniques The only certainty about a demand forecast is that it will not match the out-turn. To cover this eventuality it is essential to develop a demand forecasting technique that is appropriate and suitable to the objectives of the forecast. No technique can be considered incorrect for demand forecasting. The technique adopted will depend on the time frame under



consideration, the size of the system, the plant available and the data available. In other words the type of demand forecast technique adopted should fall in line with the requirements of the study and based on the availability of data.

There are four main demand forecasting techniques, namely:

• Intuitive based demand forecasting

• Extrapolation based demand forecast

• End user demand forecast

• Econometric demand forecasting

A general overview of each of these methods is detailed in the sub-sections below.

Intuitive The term intuitive forecasting can be used to describe methods which rely largely on experience and quick calculations using simple assumptions (i.e. the use of the immediate past performance and an assumption that the rates of change will continue unaltered in the near future).

The intuitive load forecast should not be entirely discounted, as it is after all in the background of reviewers’ minds when they appraise other peoples’ demand forecasts. In some instances, the lack of available data may make intuitive forecasting the only possible option. The forecast may be appropriate for minor developments, isolated systems and small Island utilities.

An alternative approach, but still within the intuitive forecasting framework, would be to apply a growth factor that is obtained for a country with similar economic characteristics. Indeed, it may be beneficial to compare load forecasts with the performance of a similar system in another part of the world at a comparable stage of development. This will particularly be the case where (i) there is little statistical information available on past loads, such as in new areas of supply, (ii) data errors that cannot be easily corrected, or, (iii) it becomes necessary to forecast on the results of direct enquiry and demographic and economic statistics.

Such forecasting is no more than guesswork, but the results can be used to cross-check on forecasts prepared by more scientific methods. Where a new system of forecasting is to be prepared, it is often helpful to make a comparison of the intuitive forecasts prepared in the past and subsequent performance.

Extrapolation Extrapolation techniques look at past trends in energy and power demand over time and, extend them into the future. Any time series may be decomposed into three elements:

• Trend

• Seasonal variation

• Serial dependency (auto-regression).

Trend is defined as “the long-term average growth and may be regarded in some way as an average increase in a time series”. Superimposed on this may be a seasonal variation. Seasonal in this sense is defined as “a cyclic variable that has roughly the same beginning and end values for a given period of time (similar to the properties of a sine wave)”. Such variations may be seen over a 24 hour period, a weekly period, an annual period, or even a longer period.



Finally there may be a dependency between successive values. For example, if the value in the previous period was high, the value in the current period may be high. Such behaviour could relate to the random use of batch processing equipment. This interdependency is known as auto-regression.

There are a wide range of techniques for analysing data on a time series basis including:

• Moving Average

• Exponential smoothing

• Autoregressive techniques

• Simple Regression

• ARIMA (autoregressive integrated moving average)

End User End-user demand forecast modelling draws on many utility forecasting methods. The distinguishing characteristic of end-user modelling is the detailed description of how energy is used. Such models usually begin by specifying uses for which energy is ultimately required, such as heating water, cooling buildings and cooking food. The model then describes, via mathematical equations and accounting identities, the types of energy-using equipment that businesses and households have, and how much energy is used by each type of equipment to satisfy the predetermined levels of end-use energy demanded. A large amount of survey data and statistics are needed by such a model. By summing up the units of equipment times the average energy used by each class of equipment, total energy demand by fuel type is revealed. Multiplying types of equipment by average use values is just an accounting framework, but even so, it can generate insights into the way energy is used now and in the future.

Optimisation end-user models are a step beyond accounting end-user models. By specifying an objective function (such as minimising cost) and identifying both the unit costs of using energy in the given processes and the constraints to the system, the accounting end-user model can be transformed into a device that will predict how customers will act (assuming that their objective function is properly specified), given the assumptions about costs and constraints. End-user models are often linked to econometric models.

End-user models are often weakest in predicting consumers' fuel-use decisions. With the available data, they can easily describe where the energy is being used and for what purposes but, without a theory to explain choices, they are limited in their ability to predict the future. The ideal end-user model (which is rarely achieved) would, for example, not only tell us the average watts of lighting energy in households, and how this amount has changed over time, but also what caused households and/or housing operators to make these changes.

End-user forecasting can be highly accurate, particularly for green-field developments, and for forecasts of residential demand. An extension of end-user demand forecasting is load-density-based forecasting, in which the maximum load in any area is based upon the surface area occupied by each consumer type and a power density (i.e. watts per square meter) associated with that consumer type. This can be especially useful for distribution planning. End-user forecasts also encompass developments in sectors such as industry and agriculture where consumption patterns can be established for, say, cement production or water pumping.



Econometric Analysis This class of model, like the time series model (extrapolation), uses historical data to predict the future. Econometric analysis however, attempts to go beyond time series models by explaining the causes of the identified trends. Econometric models postulate explicit causal relationships between the dependent variable (either energy or power) and independent variables (either economic (e.g. GDP), technological (e.g. number and type of appliances; industrial processes), demographic (e.g. population) or other variables (e.g. weather)). Assuming these relationships are true it should then be possible to determine the historical relationships between electrical demand and such parameters as GDP by sector, personal income, the price of electricity etc. Future levels of these economic variables are then forecast and used as inputs to determine future levels of consumption.

One advantage of econometric forecasting is the ease with which high and low scenario load forecasts can be derived and the logical basis on which the can be formed. This merely requires changes in the forecast rate of the input variables, e.g. economic growth and electricity price. A faster economic growth will produce a higher load forecast whilst the imposition of price increases will reduce forecast levels of energy demand.

Econometric modelling would be preferred to time series analysis. Even if both techniques could predict changes in demand with equal accuracy, the econometric model would be more valuable since it might help in understanding why changes in demand were occurring.

Top-down and Bottom-up Approaches An additional classification of demand forecast techniques is between bottom-up and top-down approaches. Most demand forecasting methodologies utilise a bottom-up approach. A bottom-up approach concentrates on predicting demand at the consumer level (i.e. electricity sales). This sales forecast may then be converted to a system power demand forecast at different voltage levels by summation of each individual consumer level sales forecast and the use of loss estimates and load factors (see Equation 2.1).

Using a top-down approach is generally not recommended. A top-down approach involves the estimate of demand at a generation level (i.e. forecasting MW sent out, GWh sent out). This technique includes implicit assumptions about the behaviour of losses in the future, and does not permit a breakdown by consumer sector.



2. ADOPTED APPROACH TO DEMAND FORECASTING The purpose of this report is to identify or provide an array of demand forecast scenarios (namely base, high and low scenarios) for each EAPP/EAC member country, suitable for deriving Master Plans for the EAPP/EAC member countries. In this sub-section we detail the approach adopted to achieve this objective. Our approach can be divided into three parts:

• Data collection

• Review of existing national demand forecast

• Derivation of independent demand forecast scenarios

We detail our approach to each of these parts in turn below.

2.1 Data Collection The first step in achieving the objective detailed above is to carry out an extensive data collection exercise. The data collection exercise comprised:

• A short visit to each country to meet with the utility representative(s) and to initiate the data collection. The visit to each country also allowed the Consultant to see at first hand the level of development in the country. Where data relating to demand forecasting was not readily available, requests were made for:

− Previous demand forecasts.

− Historic electrical data (hourly load data, loss data, peak demand, generation, sales data etc).

− Historic economic and demographic data (GDP, population etc).

− Economic and demographic forecast data (GDP, population etc).

− Any background information relating to topics such electrification, loss reduction etc.

• Following the visit to each country:

− A review of the data collected was undertaken.

− Desktop research was carried out to expand on the data made available in country.

− The Consultants (PB and SNC) databases were searched for information relating to the countries of the EAPP/EAC.

− Where gaps were identified we made requests for additional data.

2.2 Approach to Reviewing the Existing National Demand Forecasts The next step in determining base, high and low demand forecast scenarios for each EAPP/EAC country member is to identify the most recent existing national demand forecast available and review the adopted methodology, key assumptions and overall results. This review will allow us to form an opinion on the suitability of the forecast for use in the EAPP/EAC study.

The EAPP/EAC study horizon year is 2038 and most existing national demand forecasts do not extend this far into the future. As such, we have extended the existing national demand forecasts to cover the study horizon.

The process for reviewing the existing national demand forecast (for each country) is summarised follows:



• Identify most recent demand forecast available for each country

• Review the most recent demand forecast for:

− Methodology.

− Assumptions.

− Level of detail1.

− Magnitude of demand growth.

− Suitability for inclusion in the EAPP/EAC study, including a comparison with the current level of demand to ensure that the demand forecasted today is in line with the current level of demand.

• Extend the national forecast to cover the planning horizon of the study by either using the same methodology as used to develop the original forecast (if possible) or by using trend line analysis2 or growth rate extrapolation techniques.

• Offer our comments on the extended existing demand forecast, including the likelihood of this forecast being achieved and the constraints that may hinder its attainment.

2.3 PB Independent Demand Forecasts In addition to reviewing the most recent existing demand forecast for each country, we have developed independent base, high and low demand forecasts.

Our independent demand forecasts are based on our own assumptions and methodologies, utilising the data collected and analysed as part of the data collection process (see sub-section 2.1). Where data availability and quality permit, the independent demand forecasts are based on our econometric based Regression Analysis Load Forecast (RALF) model. The data available for some of the EAPP/EAC countries however is of poor quality, un-reliable and contains many gaps. If the data does not permit an independent econometric demand forecast to be developed, then we use a combination of growth rate analysis, electrification assumptions, population data and specific consumption assumptions to derive suitable independent demand forecasts3.

1 This typically includes identifying whether the forecast includes both an energy and power forecast, whether it is developed at a sales level, broken down by consumer category etc. 2 Trend Line Analysis is carried out using the Microsoft Excel trend line tool. A trend line can be added to any charted historic dataset (using a simple X Y Chart). A trend line equation and a R2 correlation statistic can also be displayed. The R2 statistic can be used to determine the reasonableness of the trend line fit to the historic data and the equation can be used to project future values. 3 A description of the methodologies used (RALF or other) are provided in the Appendices of those countries where these methodologies have been employed.



3. REVIEW OF EXISTING NATIONAL DEMAND FORECASTS In this section of the report we outline the existing national demand forecasts available for each member country of the EAPP/EAC. Each existing national demand forecast has been extended to cover the period to 2038. In the following sub-sections we detail the existing national demand forecast, covering the following:

• Who developed the forecast,

• When was the forecast developed,

• What methodology was employed,

• How we extended the forecast to cover the period to 2038,

• The extended forecast, and,

• Comments on the existing/extended demand forecast

Further details of each review are provided in the respective Appendices provided with this report.

3.1 Burundi The latest national demand forecast available for Burundi was produced by Fichtner and RSWI in October 2008 as part of the Nile Basin Initiative (NBI) study entitled ‘Nile Equatorial Lakes Subsidiary Action Program (NELSAP).

The Burundian NELSAP demand forecast was developed in tandem with demand forecasts for Tanzania and Rwanda. The objective of the demand forecast was to develop an end-user model, which focused on the structure of the different electricity consumer groups and their specific consumption. It should be noted, however, that some elements of trend-line and econometric techniques were also been taken into consideration.

As the NELSAP demand forecast only covered the period to 2025, we have extended the current national forecast to cover the period up to the planning horizon of this study. In order to extend the existing forecast we used trend line analysis to identify existing trends in generation sent out, sales and peak demand forecasts and used the resulting mathematical trend line formulas to project the forecast for the additional 13 years required. Several demand forecast scenarios were developed as part of the study.

Further details of the methodology and assumptions used in the derivation of the NELSAP demand forecast are provided in Appendix A.

The extended NELSAP base case demand forecast scenario is presented in Table 3-1 below.



Table 3-1 Extended NELSAP Demand Forecast for Burundi (Base Case)

We consider the assumed growth rates in peak demand, generation and sales to be very high, with average annual growth around 11 per cent per annum. An average annual increase of this size would require a significant amount of annual investment in generation, transmission and distribution.

The assumption that losses are to remain at around 26 per cent from 2015 onwards does not seem to reflect the most effective use of resources.

It is also a concern to see such a large growth in demand not reflected in a change in the make-up of demand. The load factor is assumed to fall from 36 per cent to around 30 per cent. It would be reasonable to expect that the load factor would increase as more connections are made to the system and the timing and type of demand begins to reflect that of other similarly sized economies.

A full description of our review of the NELSAP demand forecast is provided in Appendix A.

3.2 Djibouti The most recent Least Cost Electricity Master Plan (LCEMP) study for Djibouti was completed by PB in November 2009 and covers the period 2008 to 2038. The PB demand

Sales GenerationPeak

DemandLoad Factor Sales Generation

Peak Demand

(GWh) (GWh) (%) (GWh) (MW) (%) (%) (%) (%)

2008 63 27 30.0% 90 29

2009 86 31 26.5% 117 37 36.5% 30.0% 29.4%

2010 93 41 30.6% 134 43 35.2% 8.1% 14.5% 16.0%

2011 99 36 26.7% 135 44 34.9% 6.5% 0.7% 1.6%

2012 104 39 27.3% 143 47 34.8% 5.1% 5.9% 6.3%

2013 125 45 26.5% 170 56 34.5% 20.2% 18.9% 19.8%

2014 147 53 26.5% 200 66 34.5% 17.6% 17.6% 17.8%

2015 170 61 26.4% 231 77 34.2% 15.6% 15.5% 16.5%

2016 195 70 26.4% 265 89 34.0% 14.7% 14.7% 15.4%

2017 222 79 26.2% 301 102 33.8% 13.8% 13.6% 14.4%

2018 251 88 26.0% 339 116 33.5% 13.1% 12.6% 13.6%

2019 281 100 26.2% 381 131 33.3% 12.0% 12.4% 13.1%

2020 314 111 26.1% 425 147 33.0% 11.7% 11.5% 12.4%

2021 348 124 26.3% 472 165 32.8% 10.8% 11.1% 12.0%

2022 385 137 26.2% 522 184 32.5% 10.6% 10.6% 11.6%

2023 425 151 26.2% 576 204 32.2% 10.4% 10.3% 11.3%

2024 467 166 26.2% 633 227 31.9% 9.9% 9.9% 10.9%

2025 513 182 26.2% 695 251 31.6% 9.9% 9.8% 10.7%

2026 560 200 26.3% 760 274 31.6% 9.2% 9.3% 9.3%

2027 610 217 26.3% 827 300 31.5% 8.8% 8.9% 9.4%

2028 661 236 26.3% 898 327 31.4% 8.5% 8.5% 9.0%

2029 716 256 26.3% 972 355 31.2% 8.2% 8.2% 8.7%

2030 772 277 26.4% 1,049 385 31.1% 7.9% 7.9% 8.3%

2031 831 298 26.4% 1,129 415 31.0% 7.6% 7.7% 8.0%

2032 892 320 26.4% 1,213 448 30.9% 7.4% 7.4% 7.7%

2033 956 344 26.4% 1,299 481 30.8% 7.1% 7.2% 7.5%

2034 1,022 368 26.5% 1,389 516 30.8% 6.9% 6.9% 7.2%

2035 1,090 393 26.5% 1,482 552 30.7% 6.7% 6.7% 7.0%

2036 1,160 419 26.5% 1,579 589 30.6% 6.5% 6.5% 6.8%

2037 1,233 445 26.5% 1,679 628 30.5% 6.3% 6.3% 6.6%

2038 1,308 473 26.6% 1,781 667 30.5% 6.1% 6.1% 6.4%

Assumed Calender Year

Losses



forecast developed for the Djibouti LCEMP is derived using PB’s econometric based RALF model. Base, high and low demand forecast scenarios were developed for this study.

Further details of the methodology and assumptions used in the derivation of the LCEMP demand forecast are provided in Appendix B.

The base, high and low LCEMP demand forecasts are presented in Table 3-2, Table 3-3 and Table 3-4 below.



Table 3-2 LCEMP Demand Forecast (Base Case)



Table 3-3 LCEMP Demand Forecast (High Case)



Table 3-4 LCEMP Demand Forecast (Low Case)



3.3 East DRC The latest available demand forecast for the eastern region of the DRC is that produced by RSW International in October 2007 as part of the Nile Basin Initiative (NBI) Nile Equatorial Lakes Subsidiary Action Programme (NELSAP) feasibility study on the Interconnection of the Electricity Networks of the Nile Equatorial Lakes Countries.

The NELSAP study indentifies two key variables in the derivation of future power requirements in the DRC. These are:

• Consumer demand

• Power losses

By initially working out the level of consumer demand it is assumed that through the addition of losses and the application of a load factor, a peak demand forecast can be derived. As a consequence of the data available to RSW, the proposed consumer demand forecasting approach considers a mix of econometric and simplified analytical approaches to determining the level of consumer demand, including the introduction of key estimates based on its overall and regional experience, and also when necessary, simple common sense.

As the NELSAP demand forecast only covered the period to 2020, we have extended the current national forecast to the end of the planning horizon of this study. In order to extend the existing forecast we have used trend line analysis to identify existing trends in sales, sent out generation and peak demand forecasts and used the resulting mathematical trend line formulas to project the forecast for the additional 18 years required.

Details relating to the specific assumptions made for the base, high and low demand forecast scenarios are provided in Appendix C.

The base, high and low NELSAP demand forecasts are presented in Table 3-5, Table 3-6 and Table 3-7 below.

Projections of demand for the eastern region of DRC are very hard to develop given the lack of reliable and consistent historical data. The projected growth rates for the base, high and low scenarios are reasonable and not overly optimistic given the potential for development in the region.



Table 3-5 Extended NELSAP Demand Forecast for East DRC (Base Case)

Total Sales Losses Losses Generation Peak Demand Load Factor

(GWh) (GWh) (%) (GWh) (MW) (%)

1 2005 168.0 42.0 20.0% 210.0 50.0 47.9%

2 2006 176.4 43.1 19.6% 219.5 52.2 48.0%

3 2007 185.3 44.1 19.2% 229.4 54.5 48.1%

4 2008 194.7 45.2 18.8% 239.8 56.9 48.1%

5 2009 204.5 46.1 18.4% 250.7 59.4 48.2%

6 2010 214.9 47.1 18.0% 262.0 62.0 48.2%

7 2011 227.0 48.0 17.5% 275.0 65.1 48.2%

8 2012 239.9 48.8 16.9% 288.7 68.3 48.2%

9 2013 253.6 49.5 16.3% 303.1 71.7 48.3%

# 2014 268.2 49.9 15.7% 318.2 75.3 48.3%

# 2015 283.8 50.2 15.0% 334.0 79.0 48.3%

# 2016 300.5 51.8 14.7% 352.3 83.3 48.3%

# 2017 318.3 53.3 14.3% 371.6 87.8 48.3%

# 2018 337.3 54.6 13.9% 391.9 92.6 48.3%

# 2019 357.6 55.8 13.5% 413.4 97.7 48.3%

# 2020 379.3 56.7 13.0% 436.0 103.0 48.3%

# 2021 402.1 58.6 13.0% 460.7 108.7 48.4%

# 2022 426.4 60.6 12.4% 487.0 114.8 48.4%

# 2023 452.1 62.8 12.2% 514.9 121.4 48.4%

# 2024 479.3 65.3 12.0% 544.6 128.3 48.5%

# 2025 508.1 68.1 11.8% 576.1 135.6 48.5%

# 2026 538.4 71.2 11.7% 609.6 143.4 48.5%

# 2027 570.3 74.7 11.6% 645.0 151.6 48.6%

# 2028 604.0 78.5 11.5% 682.5 160.2 48.6%

# 2029 639.3 82.8 11.5% 722.1 169.4 48.7%

# 2030 676.4 87.5 11.5% 764.0 179.0 48.7%

# 2031 715.4 92.7 11.5% 808.1 189.1 48.8%

# 2032 756.2 98.3 11.5% 854.6 199.8 48.8%

# 2033 799.0 104.5 11.6% 903.5 211.0 48.9%

# 2034 843.7 111.2 11.6% 954.9 222.8 48.9%

# 2035 890.5 118.5 11.7% 1,009.0 235.1 49.0%

# 2036 939.3 126.3 11.9% 1,065.6 248.0 49.0%

# 2037 990.3 134.7 12.0% 1,125.0 261.5 49.1%

# 2038 1,043.4 143.8 12.1% 1,187.2 275.7 49.2%




Table 3-6 Extended NELSAP Demand Forecast for East DRC (High Case)


(GWh) (GWh) (%) (GWh) (MW) (%)

2005 168.0 42.0 20.0% 210.0 50.0 47.9%

2006 178.1 43.5 19.6% 221.6 52.7 48.0%

2007 188.9 45.0 19.2% 233.9 55.5 48.1%

2008 200.4 46.5 18.8% 246.9 58.5 48.2%

2009 212.7 47.9 18.4% 260.6 61.7 48.2%

2010 225.8 49.2 17.9% 275.0 65.0 48.3%

2011 240.7 50.8 17.4% 291.5 68.9 48.3%

2012 256.6 52.4 16.9% 309.0 73.0 48.3%

2013 273.8 53.7 16.4% 327.5 77.4 48.3%

2014 292.3 54.9 15.8% 347.2 82.1 48.3%

2015 312.2 55.8 15.2% 368.0 87.0 48.3%

2016 333.6 58.3 14.9% 391.9 92.6 48.3%

2017 356.7 60.6 14.5% 417.3 98.6 48.3%

2018 381.6 62.8 14.1% 444.4 105.0 48.3%

2019 408.5 64.8 13.7% 473.3 111.8 48.3%

2020 437.5 66.5 13.2% 504.0 119.0 48.3%

2021 468.2 69.4 13.0% 537.6 126.8 48.4%

2022 501.1 72.3 12.6% 573.4 135.1 48.4%

2023 536.3 75.4 12.3% 611.6 144.0 48.5%

2024 573.8 78.7 12.1% 652.5 153.5 48.5%

2025 613.7 82.4 11.8% 696.1 163.6 48.6%

2026 656.1 86.4 11.6% 742.5 174.4 48.6%

2027 701.1 90.7 11.5% 791.8 185.8 48.6%

2028 748.8 95.4 11.3% 844.2 197.9 48.7%

2029 799.3 100.5 11.2% 899.8 210.7 48.8%

2030 852.7 106.0 11.1% 958.6 224.2 48.8%

2031 909.0 111.9 11.0% 1,020.9 238.5 48.9%

2032 968.4 118.2 10.9% 1,086.6 253.5 48.9%

2033 1,031.0 125.1 10.8% 1,156.0 269.4 49.0%

2034 1,096.8 132.4 10.8% 1,229.1 286.1 49.0%

2035 1,165.9 140.2 10.7% 1,306.1 303.6 49.1%

2036 1,238.5 148.5 10.7% 1,387.0 322.0 49.2%

2037 1,314.6 157.4 10.7% 1,472.1 341.4 49.2%

2038 1,394.4 166.9 10.7% 1,561.3 361.6 49.3%




Table 3-7 Extended NELSAP Demand Forecast for East DRC (Low Case)

3.4 Egypt The latest national demand forecast available for Egypt was produced by EEHC in 2007 and estimates demand for electricity from 2008 to 20264.

The EEHC electricity demand forecast utilises the econometric based computer package E-views, focussing on regression analysis to determine electricity sales in each consumer category. The economic and demographic factors considered in the regression analysis are GDP/sector, electricity price/sector and population.

4 See Appendix D for a description of the transformation made to convert the financial information provided by EAPP into a calendar year format.


(GWh) (GWh) (%) (GWh) (MW) (%)

1 2005 168.0 42.0 20.0% 210.0 50.0 47.9%

2 2006 174.6 42.5 19.6% 217.1 51.7 48.0%

3 2007 181.5 43.0 19.1% 224.4 53.4 48.0%

4 2008 188.6 43.4 18.7% 232.0 55.2 48.0%

5 2009 196.1 43.8 18.3% 239.9 57.1 48.0%

6 2010 203.8 44.2 17.8% 248.0 59.0 48.0%

7 2011 213.4 44.7 17.3% 258.1 61.4 48.0%

8 2012 223.6 45.1 16.8% 268.7 63.9 48.0%

9 2013 234.3 45.4 16.2% 279.7 66.5 48.0%

# 2014 245.5 45.6 15.7% 291.1 69.2 48.0%

# 2015 257.4 45.6 15.0% 303.0 72.0 48.0%

# 2016 270.2 46.1 14.6% 316.4 75.3 48.0%

# 2017 283.8 46.5 14.1% 330.3 78.7 47.9%

# 2018 298.1 46.8 13.6% 344.9 82.3 47.8%

# 2019 313.3 46.8 13.0% 360.1 86.1 47.8%

# 2020 329.3 46.7 12.4% 376.0 90.0 47.7%

# 2021 346.5 46.5 13.0% 393.0 94.6 47.4%

# 2022 364.3 46.5 11.3% 410.8 99.2 47.3%

# 2023 383.0 46.4 10.8% 429.4 104.0 47.1%

# 2024 402.7 46.2 10.3% 448.9 109.1 47.0%

# 2025 423.3 46.0 9.8% 469.3 114.5 46.8%

# 2026 444.9 45.7 9.3% 490.6 120.2 46.6%

# 2027 467.4 45.4 8.8% 512.8 126.2 46.4%

# 2028 491.0 45.0 8.4% 535.9 132.5 46.2%

# 2029 515.6 44.5 7.9% 560.1 139.1 46.0%

# 2030 541.2 44.0 7.5% 585.1 146.0 45.7%

# 2031 567.9 43.3 7.1% 611.2 153.3 45.5%

# 2032 595.7 42.7 6.7% 638.3 160.9 45.3%

# 2033 624.6 41.9 6.3% 666.4 168.9 45.0%

# 2034 654.6 41.0 5.9% 695.6 177.3 44.8%

# 2035 685.7 40.1 5.5% 725.8 186.0 44.6%

# 2036 718.0 39.1 5.2% 757.1 195.1 44.3%

# 2037 751.5 38.0 4.8% 789.6 204.6 44.1%

# 2038 786.2 36.8 4.5% 823.1 214.5 43.8%




As the EEHC demand forecast only covered the period to 2026, we have extended the current national forecast to the end of the planning horizon of this study. In order to extend the existing forecast we have used trend line analysis to identify existing trends in sales, generation sent out and peak demand forecasts and used the resulting mathematical trend line formulas to project the forecast for the additional 12 years required. Further details of the methodology and assumptions used in the derivation of the EEHC demand forecast are provided in Appendix D.

The extended base case EEHC national demand forecast is presented in Table 3-8 below.

The EEHC demand forecast is econometric based and utilises the well-known E-views forecasting software. The E-views software is software is an excellent demand forecasting tool and thus we concur with the methodology adopted to derive the EEHC demand forecast.

The key assumptions of the EEHC demand forecast relate to the forecasts of GDP and population. The population forecast growth rate ranges from 1.8 per cent and 1.3 per cent per annum. We find this rate of growth to be reasonable and in line with the latest United Nations (UN) Population Division estimate. Of more significance to the forecast results are the sectoral GDP forecast assumptions. Total GDP is forecast to grow at a rate of 5.5 per cent per annum throughout the EEHC forecast period. At this rate of growth, GDP is expected to be around 2.6 times today’s value by 2026. We find this rate of overall growth to be plausible and not excessive given the current stature of the Egyptian economy and potential for further growth.

An average annual increase in demand of around 5 per cent per annum would require a reasonable but not unsustainable amount of annual investment in generation, transmission and distribution.

We find no issue with the EEHC demand forecast, although it should be noted that high and low demand forecasts were not provided.



Table 3-8 Extended EEHC Demand Forecast for Egypt (Base Case)

3.5 Ethiopia The most recent demand forecast available for Ethiopia is presented in EEPCO’s “Highlights on Power Sector Development Program” Report dated June 2008. It is assumed for this study that the Moderate I Scenario is the current base case national forecast5.

The Moderate I forecast is based on an econometric model which presents the relationships between electricity demand growth, electricity price in each tariff category and the level of economic activity. The econometric model contains three sub-forecasts (ICS, SCS and rural forecasts). The ICS forecast utilises assumptions relating to GDP and electrification rates. The SCS forecast has been based on trend analysis while the rural electrification forecasts are treated separately based on the Government electrification target. The sales forecasts are then combined with projected loss rates to produce forecasts of energy generation and through the use of average load factors, the capacity (MW) requirement to deliver the demanded energy was estimated. 5 We make this assumption on the basis that the forecast suggested in the Target Scenario is extremely high and assumes an annual average growth rate of 15.5 per cent over 20+ years. We do not believe this to be credible without the identification of a new and vast oil or gas reserve. The Moderate I scenario provides a demand forecast which is higher than the Moderate II forecast but significantly less than Target forecast.

Sales Generation Peak Demand

Load Factor Sales Generation Peak Demand

(GWh) (GWh) (%) (GWh) (MW) (%) (%) (%) (%)

2008 106,558 22,240 17.3% 128,798 21,000 70.0%

2009 117,920 19,135 14.0% 137,056 22,330 70.1% 10.7% 6.4% 6.3%

2010 125,536 20,220 13.9% 145,756 23,729 70.1% 6.5% 6.3% 6.3%

2011 133,559 21,352 13.8% 154,910 25,200 70.2% 6.4% 6.3% 6.2%

2012 142,000 22,532 13.7% 164,532 26,753 70.2% 6.3% 6.2% 6.2%

2013 150,876 23,762 13.6% 174,638 28,383 70.2% 6.3% 6.1% 6.1%

2014 160,190 25,041 13.5% 185,231 30,089 70.3% 6.2% 6.1% 6.0%

2015 169,965 26,369 13.4% 196,334 31,880 70.3% 6.1% 6.0% 6.0%

2016 180,241 27,752 13.3% 207,993 33,760 70.3% 6.0% 5.9% 5.9%

2017 191,043 29,171 13.2% 220,214 35,651 70.5% 6.0% 5.9% 5.6%

2018 202,398 30,626 13.1% 233,024 37,630 70.7% 5.9% 5.8% 5.6%

2019 214,333 32,137 13.0% 246,470 39,703 70.9% 5.9% 5.8% 5.5%

2020 226,881 33,707 12.9% 260,589 41,874 71.0% 5.9% 5.7% 5.5%

2021 240,076 35,339 12.8% 275,416 44,149 71.2% 5.8% 5.7% 5.4%

2022 253,956 37,036 12.7% 290,992 46,534 71.4% 5.8% 5.7% 5.4%

2023 268,558 38,800 12.6% 307,358 49,034 71.6% 5.7% 5.6% 5.4%

2024 283,920 40,633 12.5% 324,553 51,654 71.7% 5.7% 5.6% 5.3%

2025 300,086 42,540 12.4% 342,626 54,402 71.9% 5.7% 5.6% 5.3%

2026 317,100 44,523 12.3% 361,623 57,284 72.1% 5.7% 5.5% 5.3%

2027 335,626 45,662 12.0% 381,288 60,213 72.3% 5.8% 5.4% 5.1%

2028 354,876 47,114 11.7% 401,991 63,311 72.5% 5.7% 5.4% 5.1%

2029 375,198 48,454 11.4% 423,651 66,541 72.7% 5.7% 5.4% 5.1%

2030 396,638 49,663 11.1% 446,301 69,909 72.9% 5.7% 5.3% 5.1%

2031 419,248 50,724 10.8% 469,972 73,417 73.1% 5.7% 5.3% 5.0%

2032 443,075 51,619 10.4% 494,693 77,071 73.3% 5.7% 5.3% 5.0%

2033 468,168 52,330 10.1% 520,498 80,874 73.5% 5.7% 5.2% 4.9%

2034 494,577 52,839 9.7% 547,416 84,832 73.7% 5.6% 5.2% 4.9%

2035 522,350 53,128 9.2% 575,478 88,947 73.9% 5.6% 5.1% 4.9%

2036 551,537 53,180 8.8% 604,717 93,224 74.0% 5.6% 5.1% 4.8%

2037 582,186 52,976 8.3% 635,162 97,668 74.2% 5.6% 5.0% 4.8%

2038 614,346 52,499 7.9% 666,846 102,282 74.4% 5.5% 5.0% 4.7%

LossesAssumed Calender Year



Further details of the methodology and assumptions used in the derivation of the EEPCO demand forecast are provided in Appendix E.

As the EEPCO demand forecast only covered the period to 2030, we have extended the current national forecast to cover the whole of the planning horizon of this study. In order to extend the existing Moderate I forecast we have adopted generation and peak demand growth rate assumptions.

The extended EEPCO base case demand forecast (Moderate I scenario) is presented in Table 3-9 below.

We believe the econometric model used to derive the above forecast to be typical of most econometric models. Whilst we find no issue with the methodology adopted to derive the national demand forecast, it should be noted that we consider the resulting demand forecast to be high.

The assumed underlying GDP growth rate would result in a level of real GDP that is 5 times its current value in 2030, but almost 10 times its current value in 2038. Even in very favourable global and local market conditions the assumed level of GDP growth would be very difficult to achieve.

Peak demand is estimated to increase at an average annual rate of 10.6 per cent per annum between 2008 and 2038. An average annual increase in peak demand of this nature would require a significant amount of annual investment in generation, transmission and distribution.

A full description of the EEPCO demand forecast is provided in Appendix E.



Table 3-9 Extended EEPCO Demand Forecast for Ethiopia (Base Case – Moderate I Scenario)

3.6 Kenya In recent years the MoE in Kenya have developed annual demand forecasts as part of their Least Cost Power Development Plan (LCPDP). The two most recent forecasts are contained in the 2008 and the 2009 LCPDP. Base, high and low demand forecast scenarios were developed, but we focus our review on the base case scenario in each LCPDP study.

Generation Sent Out

Peak Demand

Load Factor Generation Growth Rate

Peak Demand Growth Rate

(GWh) (MW) (%) (%) (%)

2009 4,828 1,201 45.9%

2010 5,620 1,398 45.9% 16.4% 16.4%

2011 6,325 1,573 45.9% 12.5% 12.5%

2012 7,083 1,762 45.9% 12.0% 12.0%

2013 7,897 1,964 45.9% 11.5% 11.5%

2014 8,816 2,193 45.9% 11.6% 11.6%

2015 9,823 2,443 45.9% 11.4% 11.4%

2016 10,917 2,715 45.9% 11.1% 11.1%

2017 12,038 2,994 45.9% 10.3% 10.3%

2018 13,182 3,279 45.9% 9.5% 9.5%

2019 14,374 3,575 45.9% 9.0% 9.0%

2020 15,610 3,883 45.9% 8.6% 8.6%

2021 16,888 4,201 45.9% 8.2% 8.2%

2022 18,265 4,543 45.9% 8.2% 8.2%

2023 19,750 4,912 45.9% 8.1% 8.1%

2024 21,351 5,311 45.9% 8.1% 8.1%

2025 23,079 5,741 45.9% 8.1% 8.1%

2026 24,944 6,204 45.9% 8.1% 8.1%

2027 26,958 6,705 45.9% 8.1% 8.1%

2028 29,134 7,247 45.9% 8.1% 8.1%

2029 31,486 7,832 45.9% 8.1% 8.1%

2030 34,030 8,464 45.9% 8.1% 8.1%

2031 36,787 9,150 45.9% 8.1% 8.1%

2032 39,766 9,891 45.9% 8.1% 8.1%

2033 42,987 10,692 45.9% 8.1% 8.1%

2034 46,469 11,558 45.9% 8.1% 8.1%

2035 50,233 12,495 45.9% 8.1% 8.1%

2036 54,302 13,507 45.9% 8.1% 8.1%

2037 58,701 14,601 45.9% 8.1% 8.1%

2038 63,455 15,783 45.9% 8.1% 8.1%

Year

Moderate I



2008 LCPDP The demand forecast contained within the 2008 LCPDP covers the period 2008 to 2030. The projection of power and energy demand was made through the use of the Model for Analysis of Energy Demand (MAED). The MAED model is an end-use forecast model that is designed to evaluate medium and long-term demand for energy in a country (or in a region).

As the LCPDP demand forecast only covered the period to 2030, we have extended the current national forecast to the end of the planning horizon of this study. In order to extend the existing forecast we have used trend line analysis to identify existing trends in both the generation sent out and peak demand forecasts and used the resulting mathematical trend line formulae to project the forecast for the additional 8 years required.

The extended 2008 LCPDP base case demand forecast is presented in Table 3-10.

The MAED model used to derive the 2008 LCPDP demand forecast provides a robust end-user demand forecasting tool.

We understand that the underpinning assumption behind the MAED model is the GDP growth forecasts. In the base case, an unfaltering GDP growth rate of 10 per cent per annum for the years 2013 to 2030 is assumed. Even in very favourable global and local market conditions this level of GDP growth would be very difficult to achieve. Furthermore, historical analysis of GDP growth statistics in countries worldwide indicates that this level of sustained economic growth has rarely occurred and can rarely be sustained without (i) vast, new mineral reserves being discovered or, (ii) a significant increase in Foreign Direct Investment (FDI).

An average annual increase in demand of around 9 per cent per annum would also require a significant amount of annual investment in generation, transmission and distribution.

A full description of the 2008 LCPDP demand forecast is provided in Appendix F.



Table 3-10 Extended 2008 LCPDP Demand Forecast for Kenya (Base Case)

2009 LCPDP The demand forecast developed for the 2009 LCPDP covers the period 2010 to 2030. In contrast to the 2008 LCPDP, the projections of power and energy demand in the 2009 LCPDP were made through the use of the Microsoft E-views econometric software.

As the LCPSP demand forecast only covered the period to 2030, we have extended the current national forecast to the end of the planning horizon of this study. In order to extend the existing forecast we have maintained a constant growth rate in sales, generation and peak demand of 14.3 per cent per annum for the remainder of the planning period. The extended demand forecast (base case only) is presented in Table 3-11 below.

Generation Peak Demand Load Factor Generation Peak Demand

(GWh) (MW) (%) (%) (%)

2008 7,676 1,194 73.4%

2009 8,140 1,313 70.8% 6.0% 10.0%

2010 8,954 1,445 70.8% 10.0% 10.0%

2011 9,847 1,589 70.8% 10.0% 10.0%

2012 10,830 1,747 70.8% 10.0% 10.0%

2013 12,134 1,958 70.8% 12.0% 12.0%

2014 13,739 2,193 71.5% 13.2% 12.0%

2015 15,390 2,456 71.5% 12.0% 12.0%

2016 16,743 2,672 71.5% 8.8% 8.8%

2017 17,988 2,871 71.5% 7.4% 7.4%

2018 19,327 3,085 71.5% 7.4% 7.4%

2019 20,765 3,314 71.5% 7.4% 7.4%

2020 22,310 3,561 71.5% 7.4% 7.4%

2021 24,187 3,860 71.5% 8.4% 8.4%

2022 26,222 4,185 71.5% 8.4% 8.4%

2023 28,428 4,537 71.5% 8.4% 8.4%

2024 30,723 4,919 71.3% 8.1% 8.4%

2025 33,307 5,333 71.3% 8.4% 8.4%

2026 35,936 5,753 71.3% 7.9% 7.9%

2027 38,786 6,210 71.3% 7.9% 7.9%

2028 41,831 6,697 71.3% 7.9% 7.9%

2029 45,217 7,227 71.4% 8.1% 7.9%

2030 48,775 7,795 71.4% 7.9% 7.9%

2031 52,412 8,393 71.3% 7.5% 7.7%

2032 56,402 9,037 71.2% 7.6% 7.7%

2033 60,651 9,723 71.2% 7.5% 7.6%

2034 65,170 10,453 71.2% 7.4% 7.5%

2035 69,968 11,229 71.1% 7.4% 7.4%

2036 75,058 12,053 71.1% 7.3% 7.3%

2037 80,450 12,927 71.0% 7.2% 7.2%

2038 86,154 13,852 71.0% 7.1% 7.2%




Table 3-11 Extended 2009 LCPDP Demand Forecast (Base Case)

As previously stated, we believe that it is unrealistic to assume a five to seven fold increase in GDP between now and 2030 unless major new mineral reserves are discovered or FDI contributions increase manifold.

It should be noted that there is a considerable difference between the 2008 and the 2009 LCPDP demand forecasts. Although the key input assumptions remain largely unchanged, the 2009 LCPDP forecast is considerably higher than the 2008 LCPDP forecast. The marked difference in projected load levels can only be attributed to the change to the adopted forecasting methodology and model.

Furthermore, the out-turn demand for electricity in Kenya in 2009 indicates growth at a slower rate than that projected in the 2008 LCPDP. This would seem to indicate that the 2009 LCPDP forecast should have been more conservative with the assumptions. Our

Generation Peak Demand Load Factor Generation Peak Demand

(GWh) (MW) (%) (%) (%)

2009 7,391 1,205 70.0%

2010 7,838 1,278 70.0% 6.0% 6.1%

2011 8,292 1,352 70.0% 5.8% 5.8%

2012 8,916 1,454 70.0% 7.5% 7.5%

2013 9,692 1,581 70.0% 8.7% 8.7%

2014 10,935 1,783 70.0% 12.8% 12.8%

2015 12,495 2,038 70.0% 14.3% 14.3%

2016 14,278 2,328 70.0% 14.3% 14.2%

2017 16,315 2,661 70.0% 14.3% 14.3%

2018 18,643 3,040 70.0% 14.3% 14.2%

2019 21,303 3,474 70.0% 14.3% 14.3%

2020 24,342 3,970 70.0% 14.3% 14.3%

2021 27,815 4,536 70.0% 14.3% 14.3%

2022 31,783 5,183 70.0% 14.3% 14.3%

2023 36,318 5,923 70.0% 14.3% 14.3%

2024 41,500 6,768 70.0% 14.3% 14.3%

2025 47,421 7,733 70.0% 14.3% 14.3%

2026 54,186 8,837 70.0% 14.3% 14.3%

2027 61,917 10,097 70.0% 14.3% 14.3%

2028 70,751 11,538 70.0% 14.3% 14.3%

2029 80,846 13,184 70.0% 14.3% 14.3%

2030 92,380 15,065 70.0% 14.3% 14.3%

2031 105,560 17,214 70.0% 14.3% 14.3%

2032 120,620 19,670 70.0% 14.3% 14.3%

2033 137,829 22,477 70.0% 14.3% 14.3%

2034 157,493 25,683 70.0% 14.3% 14.3%

2035 179,963 29,348 70.0% 14.3% 14.3%

2036 205,638 33,535 70.0% 14.3% 14.3%

2037 234,976 38,319 70.0% 14.3% 14.3%

2038 268,500 43,786 70.0% 14.3% 14.3%




analysis of the results of the two forecasts shows that this is not the case and we would question the validity of this forecast.

A full description of the 2009 LCPDP demand forecast is provided in Appendix F.

3.7 Rwanda The latest national demand forecast available for Rwanda was produced by RSWI and Fichtner in October 2008 as part of the Nile Basin Initiative (NBI) Nile Equatorial Lakes Subsidiary Action Program (NELSAP) study on the Electricity Transmission Lines linked to the Rusumo Falls Hydro-Electric Generation Plant.

The Rwandan NELSAP demand forecast was developed in tandem with demand forecasts for Tanzania and Burundi. The objective of the demand forecast was to develop an end-user model, which focused on the structure of the different electricity consumer groups and their specific consumption. It should be noted, however, that some elements of trend-line and econometric techniques have also been taken into consideration.

As the NELSAP demand forecast only covered the period to 2025, we have extended the current national forecast to the end of the planning horizon for this study. In order to extend the existing forecast we have used trend line analysis to identify existing trends in the sent out generation and peak demand forecasts and used the resulting mathematical trend line formulas to project the forecast for the additional 13 years required.

Further details of the methodology and assumptions used in the derivation of the NELSAP demand forecast are provided in Appendix G.

We consider the assumed growth rates in peak demand and generation to be very high, with average annual growth around 11 per cent per annum. Growth rates of this magnitude require massive amounts of coordinated investment in infrastructure and while “technically” possible, in our view, we do not believe this is likely to be achieved under a base case scenario.

Given our concerns with the base case demand forecast detailed above, we have not reviewed the other demand forecast scenarios developed as part of the 2009 LCPDP.



Table 3-12 Extended NELSAP Demand Forecast for Rwanda (Base Case)

Generation Peak Demand Load Factor

(GWh) (MW) (%)1998 186.8 37.0 57.6%1999 189.7 37.6 57.6%2000 192.6 38.1 57.6%2001 195.5 38.7 57.6%2002 198.3 39.3 57.6%2003 201.2 39.9 57.6%2004 204.1 40.4 57.6%2005 207.0 41.0 57.6%2006 231.6 45.4 58.2%2007 256.2 49.8 58.7%2008 280.8 54.2 59.1%2009 305.4 58.6 59.5%2010 330.0 63.0 59.8%2011 386.2 73.4 60.1%2012 442.4 83.8 60.3%2013 498.6 94.2 60.4%2014 554.8 104.6 60.5%2015 611.0 115.0 60.7%2016 697.4 131.8 60.4%2017 783.8 148.6 60.2%2018 870.2 165.4 60.1%2019 956.6 182.2 59.9%2020 1043.0 199.0 59.8%2021 1161.8 224.8 59.0%2022 1280.6 250.6 58.3%2023 1399.4 276.4 57.8%2024 1518.2 302.2 57.3%2025 1637.0 328.0 57.0%2026 1780.5 355.8 57.1%2027 1922.5 385.7 56.9%2028 2070.7 417.0 56.7%2029 2225.0 449.7 56.5%2030 2385.4 483.8 56.3%2031 2552.0 519.3 56.1%2032 2724.7 556.1 55.9%2033 2903.6 594.3 55.8%2034 3088.6 633.9 55.6%2035 3279.7 674.9 55.5%2036 3477.0 717.3 55.3%2037 3680.4 761.0 55.2%2038 3890.0 806.1 55.1%

Year

Historic Data

NELSAP National Plan

PB Extension



3.8 Sudan In 2005, PB were commissioned with the task of developing a LTPSP study for the whole of Sudan, which included an extensive end-user survey based demand forecast.

A variety of methodologies have been utilised to derive the demand forecasts for the LTPSP study, primarily based around the results of the detailed market survey performed by NEC. Forecasts for the domestic and agricultural forecasts use end-use approaches. From the results of the household energy survey, average electricity consumption patterns were identified on a state by state and urban rural/basis for each of the 7 income categories identified in the survey. An end-use demand forecast model was developed to calculate changes in total domestic consumption as household income and electrification rates increase respectively.

The short-term demand forecast for the large commercial and industrial sector is based upon production output forecasts from existing NEC customers. In the medium-term the load from committed large commercial and industrial projects are added to the underlying growth of existing customers and in the long-term the energy and electricity requirements to serve the growing economy in Sudan are used as the driving parameters to estimate future electricity demands. Growth in demand for the small commercial and Government sectors are based upon estimates of customer numbers and specific consumption per customer.

The forecasts for each consumer category were developed on a state by state basis. The electricity forecasts for total generation (GWh) and peak demand (MW) at the sent-out generation level are derived from the application of power and energy losses to the total sector sales forecasts presented above and the application of appropriate coincident after diversity load factors.

Further details of the methodology and assumptions used in the derivation of the LTPSP demand forecast are provided in Appendix H.

As the LTPSP demand forecast only covered the period to 2030, we have extended the current national forecast to the end of the planning horizon for this study. In order to extend the existing forecast we have used trend line analysis to identify existing trends in both electricity sales and peak demand forecasts and used the resulting mathematical trend line formulae to project the forecast for the additional 8 years required.

The extended LTPSP base case demand forecast is presented below in Table 3-13.



Table 3-13 Extended LTPSP Demand Forecast for Sudan (Base Case)

The demand forecast developed as part of the LTPSP study was an end-user forecast based on an extensive survey. The survey results provided an indication of the patterns, requirements and uses of electricity in Sudan at the time. The end-user methodology adopted to develop the demand forecast is reasonable for determining the future load in Sudan.

A key component in determining the demand for electricity into the future however, is the electrification rate. At the time of the study, NEC declared that they would invest significantly in increasing the number of connections to the grid and this led to the assumption that 80 per cent of the country would be connected to the grid by 2025. As the LTPSP study specifically states,

“Achieving the high level of demand growth is heavily reliant on the successful completion of the stated electrification projects across the whole of the country. We note that the number of connections required on an annual basis are significantly higher than have been achieved historically. NEC are confident that they will be able to achieve these electrification rates and to fulfil the Government’s policy. Failure to complete these projects and/or lower growth rates in final connection to the distribution networks by households will inevitably lead to lower outturn levels of electricity demand than shown here.”

In the 5 years since the demand forecast was first developed, it is apparent that NEC have not reached the levels of electrification that were assumed in the study. While the level of growth experienced in Sudan is very high and commendable, this is significantly below the forecast figure and indicates that NEC fell short of its own targets.

Sales Generation Peak Demand Load Factor Sales Generation Peak Demand

(GWh) (GWh) (%) (GWh) (MW) (%) (%) (%) (%)

2006 6,371 2,067 24.5% 8,438 1,475 65.3%

2007 10,483 3,220 23.5% 13,704 2,244 69.7% 64.5% 62.4% 52.1%

2008 14,596 4,237 22.5% 18,833 3,013 71.4% 39.2% 37.4% 34.3%

2009 18,708 5,124 21.5% 23,832 3,781 71.9% 28.2% 26.5% 25.5%

2010 22,820 5,884 20.5% 28,704 4,550 72.0% 22.0% 20.4% 20.3%

2011 25,088 6,077 19.5% 31,166 4,979 71.5% 9.9% 8.6% 9.4%

2012 27,357 6,417 19.0% 33,774 5,407 71.3% 9.0% 8.4% 8.6%

2013 29,625 6,725 18.5% 36,350 5,836 71.1% 8.3% 7.6% 7.9%

2014 31,894 7,001 18.0% 38,895 6,264 70.9% 7.7% 7.0% 7.3%

2015 34,162 7,246 17.5% 41,408 6,693 70.6% 7.1% 6.5% 6.8%

2016 36,731 7,523 17.0% 44,254 7,153 70.6% 7.5% 6.9% 6.9%

2017 39,300 7,766 16.5% 47,066 7,614 70.6% 7.0% 6.4% 6.4%

2018 41,869 7,975 16.0% 49,844 8,074 70.5% 6.5% 5.9% 6.0%

2019 44,438 8,151 15.5% 52,589 8,535 70.3% 6.1% 5.5% 5.7%

2020 47,007 8,295 15.0% 55,302 8,995 70.2% 5.8% 5.2% 5.4%

2021 49,700 8,429 14.5% 58,129 9,437 70.3% 5.7% 5.1% 4.9%

2022 52,393 8,529 14.0% 60,923 9,879 70.4% 5.4% 4.8% 4.7%

2023 55,087 8,597 13.5% 63,684 10,321 70.4% 5.1% 4.5% 4.5%

2024 57,780 8,634 13.0% 66,414 10,763 70.4% 4.9% 4.3% 4.3%

2025 60,473 8,639 12.5% 69,112 11,205 70.4% 4.7% 4.1% 4.1%

2026 63,292 9,042 12.5% 72,334 11,741 70.3% 4.7% 4.7% 4.8%

2027 66,111 9,444 12.5% 75,556 12,276 70.3% 4.5% 4.5% 4.6%

2028 68,931 9,847 12.5% 78,778 12,812 70.2% 4.3% 4.3% 4.4%

2029 71,750 10,250 12.5% 82,000 13,347 70.1% 4.1% 4.1% 4.2%

2030 74,569 10,653 12.5% 85,222 13,883 70.1% 3.9% 3.9% 4.0%

2031 77,383 11,055 12.5% 88,437 14,327 70.5% 3.8% 3.8% 3.2%

2032 80,208 11,458 12.5% 91,666 14,847 70.5% 3.7% 3.7% 3.6%

2033 83,031 11,862 12.5% 94,893 15,372 70.5% 3.5% 3.5% 3.5%

2034 85,849 12,264 12.5% 98,113 15,902 70.4% 3.4% 3.4% 3.4%

2035 88,658 12,665 12.5% 101,323 16,437 70.4% 3.3% 3.3% 3.4%

2036 91,456 13,065 12.5% 104,521 16,977 70.3% 3.2% 3.2% 3.3%

2037 94,239 13,463 12.5% 107,702 17,522 70.2% 3.0% 3.0% 3.2%

2038 97,005 13,858 12.5% 110,863 18,072 70.0% 2.9% 2.9% 3.1%


Losses



3.9 Tanzania In December 2007 SNC published their Power System Master Plan (PSMP) study report. This study was carried out for TANESCO on behalf of The Government of the United Republic of Tanzania. In 2009, an updated PSMP demand forecast was developed by TANESCO experts, under the supervision of SNC during an ‘on-the-job’ training course.

For this study, we consider the regional extrapolation/trend line demand forecast to be the ‘official’ forecast of demand. The regional load forecast was carried out in four steps:

• Derive a forecast of sales for the load centres area using a trend-line approach in which the trends in number of customers and the unit consumption in each category of load are studied and projected;

• Assess the impact of the issues specific to Tanzania;

• Estimate the losses and derive the energy required;

• Estimate the load factors that would apply in an unconstrained system.

The process to be used for the trend-line forecast will consist of the following steps:

• For each category for which data are available, tabulate the number of customers, the sales and the unit consumption for the full historical period available (roughly twenty years)

• Plot the above data

• Review the data and the graphs derived from it to assess anomalies and trends

• Either correct anomalies or obtain explanations for them

• Project the number of customers for the period taking account of issues likely to have an impact on growth (e.g. rural electrification policies)

• Project the unit consumption for the same period taking account of issues likely to have an impact on growth (e.g. the removal of constraints on generation)

• Multiply the unit consumption in each year by the number of customers forecast for that year to obtain the estimated sales

Further details of the methodology and assumptions used in the derivation of the PSMP demand forecast are provided in Appendix I.

As the PSMP demand forecast only covered the period to 2033, we have extended the current national forecast to the end of the planning horizon for this study. In order to extend the existing forecast we have used trend line analysis to identify existing trends in both the generation sent out and peak demand forecasts and used the resulting mathematical trend line formulae to project the forecast for the additional 5 years required.

We believe the methodology employed to determine the PSMP demand forecast is robust and in line with demand forecasting best-practice.

The PSMP demand forecast projects an average annual increase in peak demand of around 7.2 per cent. An average annual growth rate of this figures results in a 7 fold increase over the 28 year period. Similar growth rates are projected for sent out generation. An average annual increase in peak demand/generation of this nature would require a significant amount of annual investment in generation, transmission and distribution. If such a large amount of investment is required to fund the new generation, transmission and distribution projects required in order to meet this demand, then less money would be available for investment in other sectors of the economy, and this in turn would cast doubts on the ability of other



sectors to grow at the rates required to achieve the high growth rates predicated in the demand forecast. It should be noted however, that the Government of Tanzania has identified 5 key areas of strategic importance (of which Energy Infrastructure is one) in its medium-term Public Investment Plan (MPIP) for the period 2009/10 to 2014/15. The MPIP highlights the importance of fast-tracking the flow of public investment into the energy infrastructure industry so as to stimulate increased participation of other key players in the Tanzanian economy. This suggest that Government will do all it can to ensure funds are available to allow the energy sector to develop in line with the demand forecast developed as part of the PSMP.

Table 3-14 Extended PSMP Demand Forecast for Tanzania (Base Case)

3.10 Uganda The latest demand forecast available for Uganda was developed by PB as part of the on-going Power Sector Investment Plan (PSIP) study. The PSIP demand forecast projects demand for electricity over the period 2008 to 2038 for three different scenarios; base, high and low. The PSIP demand forecast is derived using PB’s econometric based RALF model.

Generation Peak Demand Load Factor

(GWh) (MW) (%)

2010 5,293 895 67.5%

2011 5,773 981 67.2%

2012 6,439 1,103 66.7%

2013 7,081 1,213 66.6%

2014 7,489 1,285 66.5%

2015 8,135 1,398 66.5%

2016 8,987 1,542 66.5%

2017 9,895 1,698 66.5%

2018 10,704 1,839 66.5%

2019 11,326 1,945 66.5%

2020 11,994 2,061 66.4%

2021 12,701 2,182 66.5%

2022 13,440 2,311 66.4%

2023 14,398 2,479 66.3%

2024 15,245 2,628 66.2%

2025 16,145 2,783 66.2%

2026 17,112 2,953 66.1%

2027 18,116 3,131 66.0%

2028 19,379 3,353 66.0%

2029 20,536 3,558 65.9%

2030 21,745 3,770 65.8%

2031 23,042 4,002 65.7%

2032 24,449 4,254 65.6%

2033 26,164 4,532 65.9%

2034 27,917 4,838 65.9%

2035 29,854 5,168 65.9%

2036 31,978 5,527 66.1%

2037 34,311 5,918 66.2%

2038 36,873 6,344 66.4%




Further details of the methodology and assumptions used in the derivation of the PSIP demand forecast are provided in Appendix J.

The base, high and low PSIP demand forecasts are presented below in Table 3-15.

Table 3-15 PSIP Demand Forecasts for Uganda (Base, High and Low Cases)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2009 2784 541 58.7% 2877 561 58.5% 3397 597 65.0%2010 2901 570 58.1% 3026 596 58.0% 3982 702 64.8%2011 3012 597 57.6% 3188 633 57.5% 4564 805 64.7%2012 3121 623 57.2% 3371 673 57.2% 5146 908 64.7%2013 3203 643 56.9% 3560 715 56.8% 5663 998 64.8%2014 3279 662 56.5% 3788 764 56.6% 6165 1084 64.9%2015 3351 679 56.3% 4030 816 56.4% 6651 1167 65.1%2016 3419 695 56.2% 4288 871 56.2% 7122 1247 65.2%2017 3481 710 56.0% 4561 929 56.0% 7577 1324 65.3%2018 3540 724 55.8% 4851 990 55.9% 8018 1398 65.5%2019 3622 741 55.8% 5123 1045 56.0% 8518 1480 65.7%2020 3676 750 56.0% 5362 1091 56.1% 8977 1551 66.1%2021 3778 772 55.9% 5685 1158 56.0% 9537 1647 66.1%2022 3913 800 55.8% 6056 1233 56.1% 10178 1759 66.1%2023 4048 828 55.8% 6434 1310 56.1% 10831 1873 66.0%2024 4184 857 55.7% 6821 1389 56.1% 11497 1990 66.0%2025 4321 886 55.7% 7216 1470 56.0% 12175 2109 65.9%2026 4459 915 55.6% 7620 1552 56.0% 12867 2231 65.8%2027 4598 944 55.6% 8031 1636 56.0% 13570 2355 65.8%2028 4738 973 55.6% 8450 1722 56.0% 14287 2482 65.7%2029 4880 1003 55.5% 8878 1809 56.0% 15016 2612 65.6%2030 5022 1033 55.5% 9313 1898 56.0% 15757 2744 65.6%2031 5065 1032 56.0% 9754 1978 56.3% 16548 2883 65.5%2032 5246 1069 56.0% 10203 2069 56.3% 17348 3025 65.5%2033 5428 1107 56.0% 10659 2162 56.3% 18156 3168 65.4%2034 5611 1145 55.9% 11123 2257 56.3% 18972 3312 65.4%2035 5796 1184 55.9% 11594 2353 56.2% 19797 3459 65.3%2036 5982 1223 55.8% 12072 2450 56.2% 20629 3607 65.3%2037 6170 1262 55.8% 12559 2549 56.2% 21470 3757 65.2%2038 6358 1301 55.8% 13052 2650 56.2% 22319 3908 65.2%

PB High CasePB Base CasePB Low CaseYear



4. INDEPENDENT PB DEMAND FORECASTS In this section of the report we outline the independent PB demand forecasts developed specifically using the data made available for this study. Further details of each review are provided in the respective Appendices provided with this report.

4.1 Burundi In addition to reviewing the most recent national demand forecast available for Burundi, we have produced our own base; high and low national demand forecast scenarios. These scenarios are based upon our own assumptions and methodology, utilising the data collected/made available as part of this study.

Due to the lack of economic data as well as the unavailability of sales by consumer category, this forecast has been developed on the basis of the country electrification rate, an assumed level of specific consumption, an assumption relating to the number of persons per household and a population forecast provided by the UN.

High and low demand forecast scenarios have also been developed. These forecasts differ from the base case demand forecast having adopted different assumptions relating to the rate of electrification and population for the derivation of total sales.

Details of the methodology employed and any assumptions made are provided in Appendix A.

The base, high and low independent PB demand forecasts are presented in Table 4-1 and summarised in Figure 4-1 and Figure 4-2 below.



Table 4-1 PB Base, High and Low Demand Forecast for Burundi

(GWh) (MW) LF (%) (GWh) (MW) LF (%) (GWh) (MW) LF (%)2008 93.6 28.9 36.9% 93.6 28.9 36.9% 93.6 28.9 36.9%2009 98.2 29.6 37.9% 98.2 29.6 37.9% 98.2 29.6 37.9%2010 102.2 30.0 38.9% 102.2 30.0 38.9% 102.2 30.0 38.9%2011 119.9 34.3 39.9% 124.3 35.6 39.9% 132.8 38.0 39.9%2012 138.0 38.5 40.9% 146.9 41.0 40.9% 164.3 45.9 40.9%2013 156.4 42.6 41.9% 170.0 46.3 41.9% 196.5 53.5 41.9%2014 175.1 46.6 42.9% 193.6 51.5 42.9% 229.6 61.1 42.9%2015 194.2 50.5 43.9% 217.6 56.6 43.9% 263.4 68.5 43.9%2016 213.3 54.2 44.9% 242.2 61.6 44.9% 298.5 75.9 44.9%2017 232.7 57.9 45.9% 267.3 66.5 45.9% 334.4 83.2 45.9%2018 252.4 61.4 46.9% 292.8 71.3 46.9% 371.1 90.3 46.9%2019 272.3 64.9 47.9% 318.8 76.0 47.9% 408.6 97.4 47.9%2020 292.5 68.3 48.9% 345.2 80.6 48.9% 446.9 104.3 48.9%2021 312.3 71.4 49.9% 371.6 85.0 49.9% 485.9 111.2 49.9%2022 332.2 74.5 50.9% 398.3 89.3 50.9% 525.6 117.9 50.9%2023 352.4 77.5 51.9% 425.5 93.6 51.9% 566.0 124.5 51.9%2024 372.7 80.4 52.9% 453.0 97.7 52.9% 607.1 131.0 52.9%2025 393.1 83.3 53.9% 480.8 101.8 53.9% 648.9 137.4 53.9%2026 413.2 85.9 54.9% 508.4 105.7 54.9% 690.7 143.6 54.9%2027 433.4 88.5 55.9% 536.3 109.5 55.9% 733.1 149.7 55.9%2028 453.6 91.0 56.9% 564.4 113.2 56.9% 776.1 155.7 56.9%2029 474.0 93.5 57.9% 592.8 116.9 57.9% 819.7 161.6 57.9%2030 494.5 95.8 58.9% 621.5 120.5 58.9% 863.8 167.4 58.9%2031 514.7 98.1 59.9% 650.2 123.9 59.9% 908.5 173.1 59.9%2032 534.9 100.3 60.9% 679.0 127.3 60.9% 953.7 178.8 60.9%2033 555.1 102.4 61.9% 708.1 130.6 61.9% 999.4 184.3 61.9%2034 575.5 104.4 62.9% 737.5 133.8 62.9% 1,045.6 189.8 62.9%2035 595.9 106.5 63.9% 767.0 137.0 63.9% 1,092.4 195.2 63.9%2036 616.0 108.3 64.9% 796.9 140.2 64.9% 1,140.7 200.6 64.9%2037 636.1 110.2 65.9% 826.9 143.2 65.9% 1,189.5 206.1 65.9%2038 656.2 112.0 66.9% 857.1 146.3 66.9% 1,238.9 211.4 66.9%

PB Low Case PB Base Case PB High CaseYear



Figure 4-1 PB Peak Demand Forecast for Burundi (MW)

Figure 4-2 PB Sent Out Generation Forecast for Burundi (GWh)

0

50

100

150

200

250

2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037

Peak Dem

and (M

W)

PB Low Case PB Base Case PB High Case

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600

800

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2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037

Gen

eration (GWh)




4.2 Djibouti The most recent national demand forecast available for Djibouti was developed by PB in 2009 as part of the LCEMP study. The forecasts developed for the LCEMP study (as discussed in Section 5 and Appendix B of this report) are representative of PB’s independent view of electrical demand growth in Djibouti.

The base, high and low LCEMP demand forecasts are presented in Table 4-2 and summarised in Figure 4-3 and Figure 4-4 below.

Table 4-2 PB Base, High and Low Demand Forecast for Djibouti

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2005 210 50 47.9% 210 50 47.9% 210 50 47.9%2006 217 52 48.0% 220 52 48.0% 222 53 48.0%2007 224 53 48.0% 229 54 48.1% 234 56 48.1%2008 232 55 48.0% 240 57 48.1% 247 59 48.2%2009 240 57 48.0% 251 59 48.2% 261 62 48.2%2010 248 59 48.0% 262 62 48.2% 275 65 48.3%2011 258 61 48.0% 275 65 48.2% 291 69 48.3%2012 269 64 48.0% 289 68 48.2% 309 73 48.3%2013 280 66 48.0% 303 72 48.3% 328 77 48.3%2014 291 69 48.0% 318 75 48.3% 347 82 48.3%2015 303 72 48.0% 334 79 48.3% 368 87 48.3%2016 316 75 48.0% 352 83 48.3% 392 93 48.3%2017 330 79 47.9% 372 88 48.3% 417 99 48.3%2018 345 82 47.8% 392 93 48.3% 444 105 48.3%2019 360 86 47.8% 413 98 48.3% 473 112 48.3%2020 376 90 47.7% 436 103 48.3% 504 119 48.3%2021 393 95 47.4% 461 109 48.4% 538 127 48.4%2022 411 99 47.3% 487 115 48.4% 573 135 48.4%2023 429 104 47.1% 515 121 48.4% 612 144 48.5%2024 449 109 47.0% 545 128 48.5% 653 154 48.5%2025 469 115 46.8% 576 136 48.5% 696 164 48.6%2026 491 120 46.6% 610 143 48.5% 742 174 48.6%2027 513 126 46.4% 645 152 48.6% 792 186 48.6%2028 536 132 46.2% 682 160 48.6% 844 198 48.7%2029 560 139 46.0% 722 169 48.7% 900 211 48.8%2030 585 146 45.7% 764 179 48.7% 959 224 48.8%2031 611 153 45.5% 808 189 48.8% 1021 238 48.9%2032 638 161 45.3% 855 200 48.8% 1087 254 48.9%2033 666 169 45.0% 904 211 48.9% 1156 269 49.0%2034 696 177 44.8% 955 223 48.9% 1229 286 49.0%2035 726 186 44.6% 1009 235 49.0% 1306 304 49.1%2036 757 195 44.3% 1066 248 49.0% 1387 322 49.2%2037 790 205 44.1% 1125 262 49.1% 1472 341 49.2%2038 823 214 43.8% 1187 276 49.2% 1561 362 49.3%

PB High CasePB Base CasePB Low Case

Year



Figure 4-3 PB Peak Demand Forecast for Djibouti (MW)

Figure 4-4 PB Sent Out Generation Forecast for Djibouti (GWh)

0

50

100

150

200

250

300

2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038

Peak Dem

and (M

W)


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200

400

600

800

1000

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1400

1600

2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038

Gen

eration (GWh)




4.3 DRC The most recent national demand forecast available for East DRC was developed by RSWI in October 2007. Projections of demand for the eastern region of DRC are very hard to develop given the lack of reliable and consistent historical data. The projected growth rates assumed in the RSWI forecast for the base, high and low scenarios are reasonable and not overly optimistic given the potential for development in the region and therefore we see no need to produce an independent forecast of demand for the Eastern region of the DRC.

The base, high and low RSWI demand forecasts are presented in Table 4-3 and summarised in Figure 4-5 and Figure 4-6 below.

Table 4-3 RSWI Base, High and Low Demand Forecast for East DRC

Generation (GWh)

Peak Demand

(MW)

Load Factor (%)

Generation (GWh)

Peak Demand

(MW)

Load Factor (%)

Generation (GWh)

Peak Demand

(MW)

Load Factor (%)

2005 210 50 47.9% 210 50 47.9% 210 50 47.9%2006 217 52 48.0% 220 52 48.0% 222 53 48.0%2007 224 53 48.0% 229 54 48.1% 234 56 48.1%2008 232 55 48.0% 240 57 48.1% 247 59 48.2%2009 240 57 48.0% 251 59 48.2% 261 62 48.2%2010 248 59 48.0% 262 62 48.2% 275 65 48.3%2011 258 61 48.0% 275 65 48.2% 291 69 48.3%2012 269 64 48.0% 289 68 48.2% 309 73 48.3%2013 280 66 48.0% 303 72 48.3% 328 77 48.3%2014 291 69 48.0% 318 75 48.3% 347 82 48.3%2015 303 72 48.0% 334 79 48.3% 368 87 48.3%2016 316 75 48.0% 352 83 48.3% 392 93 48.3%2017 330 79 47.9% 372 88 48.3% 417 99 48.3%2018 345 82 47.8% 392 93 48.3% 444 105 48.3%2019 360 86 47.8% 413 98 48.3% 473 112 48.3%2020 376 90 47.7% 436 103 48.3% 504 119 48.3%2021 393 95 47.4% 461 109 48.4% 538 127 48.4%2022 411 99 47.3% 487 115 48.4% 573 135 48.4%2023 429 104 47.1% 515 121 48.4% 612 144 48.5%2024 449 109 47.0% 545 128 48.5% 653 154 48.5%2025 469 115 46.8% 576 136 48.5% 696 164 48.6%2026 491 120 46.6% 610 143 48.5% 742 174 48.6%2027 513 126 46.4% 645 152 48.6% 792 186 48.6%2028 536 132 46.2% 682 160 48.6% 844 198 48.7%2029 560 139 46.0% 722 169 48.7% 900 211 48.8%2030 585 146 45.7% 764 179 48.7% 959 224 48.8%2031 611 153 45.5% 808 189 48.8% 1021 238 48.9%2032 638 161 45.3% 855 200 48.8% 1087 254 48.9%2033 666 169 45.0% 904 211 48.9% 1156 269 49.0%2034 696 177 44.8% 955 223 48.9% 1229 286 49.0%2035 726 186 44.6% 1009 235 49.0% 1306 304 49.1%2036 757 195 44.3% 1066 248 49.0% 1387 322 49.2%2037 790 205 44.1% 1125 262 49.1% 1472 341 49.2%2038 823 214 43.8% 1187 276 49.2% 1561 362 49.3%

PB High CasePB Base CasePB Low Case

Year



Figure 4-5 RSWI Peak Demand Forecast for East DRC (MW)

Figure 4-6 RSWI Sent Out Generation Forecast for East DRC (GWh)

0

50

100

150

200

250

300

350

400

2005 2008 2011 2014 2017 2020 2023 2026 2029 2032 2035 2038

Peak Dem

and (M

W)

NP Base Case NP Low Case NP High Case

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2005 2008 2011 2014 2017 2020 2023 2026 2029 2032 2035 2038

Gen

eration (GWh)

NP Base Case NP Low Case NP High Case



4.4 Egypt EEHC provided a base case demand forecast which was deemed by PB to be reasonable. However, high and low demand forecast scenarios were not provided. Therefore we have produced our own independent base, high and low national demand forecast scenarios. These base, high and low scenarios have been developed using our own assumptions and methodology, utilising the data collected/made available as part of this study.

The PB demand forecasts developed for Egypt are derived using PB’s own econometric RALF model. Details of the RALF model methodology and any assumptions made are provided in Appendix D.


Table 4-4 PB Base, High and Low Demand Forecast for Egypt

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2007 119,920 18,500 74.0% 119920 18,500 74.0% 119920 18,500 74.0%2008 129,019 19,855 74.2% 129244 19,882 74.2% 129301 19,888 74.2%2009 138,043 21,269 74.1% 138749 21,354 74.2% 138925 21,375 74.2%2010 147,555 22,762 74.0% 148801 22,911 74.1% 149114 22,949 74.2%2011 155,948 24,056 74.0% 158939 24,462 74.2% 160571 24,706 74.2%2012 164,702 25,404 74.0% 169608 26,093 74.2% 172702 26,565 74.2%2013 173,827 26,809 74.0% 180827 27,806 74.2% 185538 28,530 74.2%2014 183,335 28,272 74.0% 192618 29,603 74.3% 199106 30,605 74.3%2015 193,237 29,795 74.0% 205001 31,489 74.3% 213439 32,794 74.3%2016 201,942 31,120 74.1% 217293 33,353 74.4% 228850 35,147 74.3%2017 211,552 32,608 74.1% 230819 35,430 74.4% 245824 37,766 74.3%2018 221,522 34,152 74.0% 245015 37,608 74.4% 263789 40,537 74.3%2019 231,862 35,753 74.0% 259906 39,892 74.4% 282790 43,467 74.3%2020 242,582 37,413 74.0% 275519 42,286 74.4% 302871 46,563 74.3%2021 251,968 38,855 74.0% 290830 44,624 74.4% 323881 49,799 74.2%2022 261,645 40,341 74.0% 306828 47,065 74.4% 346047 53,212 74.2%2023 271,620 41,873 74.1% 323538 49,613 74.4% 369418 56,809 74.2%2024 281,901 43,450 74.1% 340984 52,271 74.5% 394043 60,597 74.2%2025 292,494 45,075 74.1% 359192 55,043 74.5% 419974 64,584 74.2%2026 302,394 46,584 74.1% 377231 57,779 74.5% 446473 68,650 74.2%2027 312,313 48,104 74.1% 395681 60,586 74.6% 473932 72,874 74.2%2028 322,494 49,663 74.1% 414865 63,501 74.6% 502737 77,302 74.2%2029 332,941 51,263 74.1% 434804 66,529 74.6% 532938 81,943 74.2%2030 343,661 52,904 74.2% 455525 69,674 74.6% 564588 86,805 74.2%2031 353,018 54,334 74.2% 475660 72,731 74.7% 597226 91,831 74.2%2032 362,579 55,795 74.2% 496519 75,896 74.7% 631365 97,086 74.2%2033 372,350 57,287 74.2% 518124 79,172 74.7% 667059 102,578 74.2%2034 382,333 58,811 74.2% 540496 82,562 74.7% 704362 108,316 74.2%2035 392,532 60,367 74.2% 563657 86,069 74.8% 743331 114,308 74.2%2036 400,731 61,600 74.3% 586001 89,436 74.8% 784537 120,645 74.2%2037 409,074 62,853 74.3% 609080 92,910 74.8% 827569 127,259 74.2%2038 417,564 64,128 74.3% 632914 96,495 74.9% 872489 134,161 74.2%

PB High CaseYear

PB Low Case PB Base Case



Figure 4-7 PB Peak Demand Forecast for Egypt (MW)

Figure 4-8 PB Sent Out Generation Forecast for Egypt (GWh)

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

160,000

2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037

Peak Dem

and (M

W)


0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

1,000,000

2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037

Gen

eration (GWh)




4.5 Ethiopia In addition to reviewing the most recent demand forecast available for Ethiopia, we have produced our own demand forecast scenarios. These scenarios are based upon our own assumptions and methodology, utilising the data collected/made available as part of this study. In the following sub-sections we detail our alternative forecast.

The Ethiopian electrical system comprises of two systems. These are the ICS system and the SCS system. We have adopted different methodologies to determine the future level of demand in each of these systems. The ICS forecasts are derived using PB’s RALF model. The SCS forecast is derived separately from the ICS utilising a simplistic sales growth assumption to project sales into the future. A loss reduction programme has been identified and losses are then added to the sales forecast to determine the level of net generation. A peak demand forecast is determined through the application of an assumed system load factor.

Details of the model methodology and any assumptions made are provided in Appendix E.

The base, high and low ICS demand forecasts are presented in Table 4-5 and are summarised in Figure 4-9 and Figure 4-10 below. The SCS demand forecast is presented in Table 4-6.

Table 4-5 PB Base, High and Low ICS Demand Forecast for Ethiopia

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2008 3765 747 57.5% 3765 747 57.5% 3765 747 57.5%2009 4118 810 58.0% 4118 810 58.0% 4118 810 58.0%2010 4377 861 58.0% 4480 881 58.0% 4532 892 58.0%2011 4707 926 58.0% 4931 970 58.0% 5045 992 58.0%2012 5022 987 58.1% 5385 1058 58.1% 5574 1095 58.1%2013 5356 1051 58.2% 5879 1153 58.2% 6156 1207 58.2%2014 5722 1121 58.3% 6430 1259 58.3% 6811 1333 58.3%2015 6066 1186 58.4% 6979 1364 58.4% 7479 1462 58.4%2016 6431 1255 58.5% 7575 1478 58.5% 8214 1603 58.5%2017 6818 1329 58.6% 8223 1602 58.6% 9022 1757 58.6%2018 7228 1406 58.7% 8928 1736 58.7% 9911 1927 58.7%2019 7663 1489 58.8% 9693 1882 58.8% 10889 2113 58.8%2020 8125 1576 58.9% 10525 2040 58.9% 11964 2318 58.9%2021 8537 1655 58.9% 11328 2195 58.9% 13032 2525 58.9%2022 8969 1739 58.9% 12193 2363 58.9% 14196 2750 58.9%2023 9424 1827 58.9% 13124 2543 58.9% 15466 2995 58.9%2024 9902 1920 58.9% 14128 2737 58.9% 16850 3263 59.0%2025 10404 2017 58.9% 15209 2946 58.9% 18361 3554 59.0%2026 10867 2106 58.9% 16277 3152 59.0% 19890 3850 59.0%2027 11349 2200 58.9% 17421 3373 59.0% 21548 4170 59.0%2028 11854 2297 58.9% 18645 3609 59.0% 23346 4517 59.0%2029 12381 2399 58.9% 19958 3863 59.0% 25297 4893 59.0%2030 12931 2506 58.9% 21363 4134 59.0% 27413 5301 59.0%2031 13425 2601 58.9% 22732 4398 59.0% 29530 5709 59.0%2032 13937 2700 58.9% 24190 4680 59.0% 31814 6150 59.1%2033 14469 2803 58.9% 25742 4979 59.0% 34276 6624 59.1%2034 15021 2910 58.9% 27395 5298 59.0% 36932 7136 59.1%2035 15595 3021 58.9% 29155 5637 59.0% 39796 7687 59.1%2036 16190 3136 58.9% 31030 5999 59.1% 42885 8282 59.1%2037 16809 3255 58.9% 33028 6384 59.1% 46218 8924 59.1%2038 17451 3379 59.0% 35155 6794 59.1% 49813 9616 59.1%




Figure 4-9 PB ICS Peak Demand Forecast for Ethiopia (MW)

Figure 4-10 PB ICS Sent Out Generation Forecast for Ethiopia (GWh)

0

2,000

4,000

6,000

8,000

10,000

12,000

2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038

Peak Dem

and (M

W)


0

10,000

20,000

30,000

40,000

50,000

60,000

2008 2010 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030 2032 2034 2036 2038

Gen

eration (GWh)




Table 4-6 PB SCS Demand Forecast for Ethiopia

4.6 Kenya In addition to reviewing the most recent demand forecast available for Kenya, we have produced our own base, high and low national demand forecast scenarios. These scenarios are based upon our own assumptions and methodology, utilising the data collected/made available as part of this study.

The demand forecasts developed for Kenya are derived using PB’s RALF model. Details of the model methodology and any assumptions made are provided in Appendix F6.

The base, high and low PB demand forecasts are presented in Table 4-7 and summarised in Figure 4-11 and Figure 4-12 below

6 It should be noted that the PB high case is based on the GDP assumptions made in the Vision 2030 report and are considered to be too high for use in this study.

Year Sales (GWh)Generation

(GWh) Losses (GWh) Losses (%) Peak Demand

(MW) Load Factor (%)

2009 47.68 57.34 9.66 16.9% 11.38 57.5%2010 51.01 61.35 10.34 16.9% 12.17 57.5%2011 54.58 65.64 11.06 16.9% 13.02 57.5%2012 58.40 70.24 11.84 16.9% 13.94 57.5%2013 62.49 75.16 12.66 16.9% 14.91 57.5%2014 66.87 80.42 13.55 16.9% 15.96 57.5%2015 71.55 86.05 14.50 16.9% 17.07 57.5%2016 76.56 92.07 15.51 16.9% 18.27 57.5%2017 81.91 98.51 16.60 16.9% 19.55 57.5%2018 87.65 105.41 17.76 16.9% 20.91 57.5%2019 93.78 112.79 19.01 16.9% 22.38 57.5%2020 100.35 120.68 20.34 16.9% 23.94 57.5%2021 107.37 129.13 21.76 16.9% 25.62 57.5%2022 114.89 138.17 23.28 16.9% 27.41 57.5%2023 122.93 147.84 24.91 16.9% 29.33 57.5%2024 131.54 158.19 26.66 16.9% 31.39 57.5%2025 140.74 169.27 28.52 16.9% 33.58 57.5%2026 150.60 181.11 30.52 16.9% 35.93 57.5%2027 161.14 193.79 32.65 16.9% 38.45 57.5%2028 172.42 207.36 34.94 16.9% 41.14 57.5%2029 184.49 221.87 37.39 16.9% 44.02 57.5%2030 197.40 237.40 40.00 16.9% 47.10 57.5%2031 211.22 254.02 42.80 16.9% 50.40 57.5%2032 226.01 271.80 45.80 16.9% 53.93 57.5%2033 241.83 290.83 49.01 16.9% 57.70 57.5%2034 258.75 311.19 52.44 16.9% 61.74 57.5%2035 276.87 332.97 56.11 16.9% 66.06 57.5%2036 296.25 356.28 60.03 16.9% 70.69 57.5%2037 316.98 381.22 64.24 16.9% 75.64 57.5%2038 339.17 407.91 68.73 16.9% 80.93 57.5%



Table 4-7 PB Base, High and Low Demand Forecast for Kenya

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2008 6436 1072 68.5% 6436 1072 68.5% 6436 1072 68.5%2009 6220 1028 69.1% 6262 1035 69.1% 6561 1087 68.9%2010 6414 1062 69.0% 6533 1082 68.9% 7055 1172 68.7%2011 6772 1123 68.8% 6883 1142 68.8% 7702 1284 68.5%2012 7165 1190 68.8% 7327 1217 68.7% 8426 1407 68.3%2013 7535 1252 68.7% 7816 1301 68.6% 9311 1559 68.2%2014 7903 1314 68.6% 8340 1390 68.5% 10292 1728 68.0%2015 8262 1375 68.6% 8901 1485 68.4% 11379 1914 67.8%2016 8638 1438 68.6% 9452 1579 68.3% 12583 2122 67.7%2017 9032 1505 68.5% 10038 1679 68.3% 13918 2353 67.5%2018 9445 1575 68.5% 10662 1785 68.2% 15399 2609 67.4%2019 9876 1647 68.4% 11326 1898 68.1% 17040 2893 67.2%2020 10328 1724 68.4% 12031 2019 68.0% 18862 3210 67.1%2021 10802 1804 68.4% 12717 2136 68.0% 20882 3561 66.9%2022 11298 1888 68.3% 13443 2259 67.9% 23123 3952 66.8%2023 11817 1975 68.3% 14211 2390 67.9% 25611 4386 66.7%2024 12361 2067 68.3% 15024 2529 67.8% 28374 4870 66.5%2025 12930 2164 68.2% 15884 2676 67.8% 31442 5409 66.4%2026 13527 2265 68.2% 16709 2817 67.7% 34849 6008 66.2%2027 14151 2370 68.2% 17577 2965 67.7% 38635 6675 66.1%2028 14849 2491 68.1% 18545 3134 67.6% 42966 7448 65.9%2029 15581 2618 67.9% 19566 3312 67.4% 47794 8313 65.6%2030 16350 2751 67.8% 20646 3501 67.3% 53179 9281 65.4%2031 17068 2876 67.8% 21672 3680 67.2% 57980 10148 65.2%2032 17819 3006 67.7% 22750 3869 67.1% 63226 11097 65.0%2033 18603 3143 67.6% 23883 4068 67.0% 68959 12138 64.9%2034 19423 3286 67.5% 25073 4277 66.9% 75224 13279 64.7%2035 20279 3435 67.4% 26324 4497 66.8% 82074 14531 64.5%2036 21174 3592 67.3% 27492 4704 66.7% 87688 15560 64.3%2037 22110 3756 67.2% 28714 4919 66.6% 93695 16664 64.2%2038 23087 3927 67.1% 29990 5145 66.5% 100125 17848 64.0%

PB Low Case PB Base Case PB High CaseYear



Figure 4-11 PB Peak Demand Forecast for Kenya (MW)

Figure 4-12 PB Sent Out Generation Forecast for Kenya (GWh)

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4.7 Rwanda In addition to reviewing the most recent demand forecast available for Rwanda, we have produced our own base; high and low national demand forecast scenarios. These scenarios are based upon our own assumptions and methodology, utilising the data collected/made available as part of this study.

Due to the lack of economic data as well as the unavailability of sales by consumer category, the independent demand forecast has been developed on the basis of the country electrification rate, an assumed level of specific consumption, an assumption relating to the number of persons per household and a population forecast provided by the UN.

High and low demand forecast scenarios have also been developed. These forecasts differ from the base case demand forecast having adopted different assumptions relating to the rate of electrification and population for the derivation of total sales.

Appendix G provides a detailed description of the adopted methodology and assumptions used to determine the PB demand forecasts for Rwanda.

The base, high and low case demand forecast is presented in Table 4-8 and summarised in Figure 4-13 and Figure 4-14 below.



Table 4-8 PB Base, High and Low Demand Forecast for Rwanda

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2005 207 41 57.6% 207 41 57.6% 207 41 57.6%2006 213 42 57.6% 213 42 57.6% 213 42 57.6%2007 219 43 57.6% 219 43 57.6% 219 43 57.6%2008 230 46 57.6% 230 46 57.6% 230 46 57.6%2009 245 49 57.6% 245 49 57.6% 245 49 57.6%2010 266 53 57.6% 266 53 57.6% 266 53 57.6%2011 279 55 57.6% 286 57 57.6% 293 58 57.6%2012 293 58 57.6% 306 61 57.6% 320 63 57.6%2013 307 61 57.6% 327 65 57.6% 349 69 57.6%2014 321 64 57.6% 349 69 57.6% 378 75 57.6%2015 335 66 57.6% 372 74 57.6% 409 81 57.6%2016 350 69 57.6% 395 78 57.6% 441 87 57.6%2017 364 72 57.6% 419 83 57.6% 475 94 57.6%2018 379 75 57.6% 444 88 57.6% 510 101 57.6%2019 395 78 57.6% 469 93 57.6% 546 108 57.6%2020 410 81 57.6% 495 98 57.6% 583 115 57.6%2021 426 84 57.6% 521 103 57.6% 621 123 57.6%2022 441 87 57.6% 548 109 57.6% 661 131 57.6%2023 457 90 57.6% 576 114 57.6% 702 139 57.6%2024 473 94 57.6% 604 120 57.6% 743 147 57.6%2025 489 97 57.6% 633 125 57.6% 786 156 57.6%2026 506 100 57.6% 663 131 57.6% 831 165 57.6%2027 522 103 57.6% 693 137 57.6% 876 174 57.6%2028 539 107 57.6% 724 143 57.6% 923 183 57.6%2029 556 110 57.6% 756 150 57.6% 971 192 57.6%2030 574 114 57.6% 788 156 57.6% 1020 202 57.6%2031 591 117 57.6% 821 163 57.6% 1072 212 57.6%2032 609 121 57.6% 855 169 57.6% 1124 223 57.6%2033 627 124 57.6% 890 176 57.6% 1178 233 57.6%2034 645 128 57.6% 925 183 57.6% 1234 244 57.6%2035 664 132 57.6% 961 190 57.6% 1290 256 57.6%2036 683 135 57.6% 998 198 57.6% 1350 267 57.6%2037 702 139 57.6% 1036 205 57.6% 1412 280 57.6%2038 721 143 57.6% 1075 213 57.6% 1474 292 57.6%




Figure 4-13 PB Peak Demand Forecast for Rwanda (MW)

Figure 4-14 PB Sent Out Generation Forecast for Rwanda (GWh)

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4.8 Sudan Given the disparity between the most recent national demand forecast (as provided in the LTPSP study) and the current level of demand, we have developed new demand forecast scenarios (base, high and low) for Sudan. These forecasts have been developed so as to:

• Take into account the current level of load, and,

• Retain the electrification targets of NEC over a longer period of time so as to retain the ‘official’ national outlook.

In order to develop the PB base case demand forecast we have used trend line analysis to identify existing trends in the level of sales in each consumer category and used the resulting mathematical trend line formulae to project the forecast for the study period. We have applied the mathematical formulae presented in the trend line analysis above in order to derive estimates of sales in each consumer category.

In order to derive the level of generation (GWh sent out) we assume that losses fall from their current level of 20 per cent to 13 per cent in 0.5 per cent increments between 2010 and 2023. The level of losses is assumed to stay constant from 2023 onwards. In order to derive the peak demand forecast, we have assumed that the load factor will remain constant at 60.7 per cent.

In addition to the base case demand forecast detailed above we have developed a “high” case demand forecast. The key assumptions adopted for the high case demand forecast are as follows:

• Peak demand in 2038 is assumed to be the same as that achieved under the base case demand forecast scenario.

• Sent out generation in 2038 is assumed to be the same as that achieved under the base case demand forecast scenario.

• Linear interpolation is used to derive the level of peak demand and sent out generation between 2010 and 2038.

• Losses are assumed to fall from their current level of 20 per cent to 13 per cent in 0.5 per cent increments between 2010 and 2023, remaining constant thereafter.

In addition to the base and high demand forecast scenarios, we have developed a low demand forecast which follows the same methodology as detailed for the base case forecast above but we assume lower 2nd order historic polynomial relationships.

Appendix H provides a detailed description of the adopted methodology and assumptions used to determine the PB demand forecasts for Sudan.




Table 4-9 PB Base, High and Low Demand Forecast for Sudan

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2009 6,118 1,151 60.7% 6,118 1,151 60.7% 6,118 1,151 60.7%2010 6,621 1,246 60.7% 7,211 1,357 60.7% 9,541 1,795 60.7%2011 7,326 1,378 60.7% 8,264 1,555 60.7% 12,964 2,439 60.7%2012 8,071 1,519 60.7% 9,436 1,775 60.7% 16,387 3,083 60.7%2013 8,857 1,666 60.7% 10,733 2,019 60.7% 19,810 3,727 60.7%2014 9,681 1,821 60.7% 12,161 2,288 60.7% 23,232 4,371 60.7%2015 10,544 1,984 60.7% 13,723 2,582 60.7% 26,655 5,015 60.7%2016 11,445 2,153 60.7% 15,426 2,902 60.7% 30,078 5,659 60.7%2017 12,382 2,330 60.7% 17,273 3,250 60.7% 33,501 6,303 60.7%2018 13,356 2,513 60.7% 19,270 3,626 60.7% 36,924 6,947 60.7%2019 14,366 2,703 60.7% 21,421 4,030 60.7% 40,347 7,591 60.7%2020 15,411 2,899 60.7% 23,731 4,465 60.7% 43,770 8,235 60.7%2021 16,490 3,103 60.7% 26,204 4,930 60.7% 47,193 8,879 60.7%2022 17,603 3,312 60.7% 28,845 5,427 60.7% 50,616 9,523 60.7%2023 18,750 3,528 60.7% 31,657 5,956 60.7% 54,039 10,167 60.7%2024 20,044 3,771 60.7% 34,844 6,556 60.7% 57,462 10,811 60.7%2025 21,384 4,023 60.7% 38,248 7,196 60.7% 60,885 11,455 60.7%2026 22,770 4,284 60.7% 41,874 7,878 60.7% 64,308 12,099 60.7%2027 24,202 4,553 60.7% 45,731 8,604 60.7% 67,731 12,743 60.7%2028 25,680 4,831 60.7% 49,825 9,374 60.7% 71,154 13,387 60.7%2029 27,204 5,118 60.7% 54,164 10,190 60.7% 74,577 14,031 60.7%2030 28,774 5,414 60.7% 58,754 11,054 60.7% 78,000 14,675 60.7%2031 30,391 5,718 60.7% 63,603 11,966 60.7% 81,423 15,319 60.7%2032 32,054 6,031 60.7% 68,718 12,929 60.7% 84,846 15,963 60.7%2033 33,762 6,352 60.7% 74,105 13,942 60.7% 88,269 16,607 60.7%2034 35,517 6,682 60.7% 79,773 15,009 60.7% 91,692 17,251 60.7%2035 37,318 7,021 60.7% 85,727 16,129 60.7% 95,114 17,895 60.7%2036 39,165 7,369 60.7% 91,976 17,304 60.7% 98,537 18,539 60.7%2037 41,058 7,725 60.7% 98,525 18,537 60.7% 101,960 19,183 60.7%2038 42,997 8,090 60.7% 105,383 19,827 60.7% 105,383 19,827 60.7%




Figure 4-15 PB Peak Demand Forecast for Sudan (MW)

Figure 4-16 PB Sent Out Generation Forecast for Sudan (GWh)

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eration (GWh)




4.9 Tanzania In addition to reviewing the most recent national demand forecast available for Tanzania, we have developed our own base, high and low demand forecast scenarios. These scenarios are based upon our own assumptions and methodology, utilising the data collected/made available as part of this study.

The base case demand forecast developed for Tanzania is derived using PB’s RALF model. We have additionally developed high and low demand forecast scenarios. These scenarios have been developed using the same methodology as outlined for the PB base case demand forecast, with the exception that high and low GDP and population forecasts have been adopted respectively.

Appendix I provides a detailed description of the adopted methodology and assumptions used to determine the PB demand forecasts for Tanzania.

The base, high and low independent PB demand forecasts are presented below in Table 4-10 and Figure 4-17 and Figure 4-18 below.

Table 4-10 PB Base, High and Low Demand Forecast for Tanzania

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2008 4143 694 68.2% 4143 694 68.2% 4143 694 68.2%2009 4273 714 68.3% 4324 722 68.3% 4367 730 68.3%2010 4486 750 68.3% 4594 767 68.4% 4686 782 68.4%2011 4742 791 68.4% 4914 819 68.5% 5061 844 68.5%2012 5013 835 68.5% 5256 874 68.6% 5466 910 68.6%2013 5299 882 68.6% 5621 933 68.7% 5904 981 68.7%2014 5602 931 68.7% 6013 997 68.9% 6377 1058 68.8%2015 5900 980 68.7% 6431 1064 69.0% 6887 1141 68.9%2016 6236 1035 68.8% 6870 1136 69.1% 7430 1229 69.0%2017 6591 1093 68.9% 7339 1212 69.1% 8016 1325 69.1%2018 6967 1154 68.9% 7841 1293 69.2% 8648 1428 69.1%2019 7364 1218 69.0% 8377 1380 69.3% 9330 1539 69.2%2020 7707 1273 69.1% 8861 1458 69.4% 9969 1643 69.3%2021 8066 1331 69.2% 9374 1540 69.5% 10651 1753 69.4%2022 8442 1391 69.3% 9917 1628 69.6% 11381 1871 69.4%2023 8835 1455 69.3% 10492 1720 69.6% 12161 1998 69.5%2024 9247 1521 69.4% 11100 1818 69.7% 12995 2133 69.6%2025 9678 1590 69.5% 11744 1921 69.8% 13887 2277 69.6%2026 10130 1662 69.6% 12425 2030 69.9% 14840 2431 69.7%2027 10603 1738 69.6% 13146 2146 69.9% 15859 2596 69.7%2028 11098 1817 69.7% 13909 2268 70.0% 16949 2773 69.8%2029 11617 1900 69.8% 14717 2398 70.1% 18115 2961 69.8%2030 12038 1967 69.9% 15417 2509 70.1% 19170 3131 69.9%2031 12474 2036 69.9% 16150 2625 70.2% 20286 3310 70.0%2032 12927 2108 70.0% 16918 2747 70.3% 21469 3500 70.0%2033 13395 2182 70.1% 17724 2875 70.4% 22721 3702 70.1%2034 13881 2258 70.2% 18568 3009 70.4% 24047 3915 70.1%2035 14385 2338 70.2% 19452 3149 70.5% 25451 4140 70.2%2036 14911 2421 70.3% 20369 3295 70.6% 26924 4377 70.2%2037 15457 2507 70.4% 21329 3448 70.6% 28483 4629 70.2%2038 16023 2596 70.5% 22335 3608 70.7% 30134 4894 70.3%




Figure 4-17 PB Peak Demand Forecast for Tanzania (MW)

Figure 4-18 PB Sent Out Generation Forecast for Tanzania (GWh)

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4.10 Uganda The most recent national demand forecast available for Uganda was developed by PB as part of the PSIP study. The forecasts developed for the PSIP study (as discussed in Section 5 and Appendix J of this report) are representative of PB’s independent view of electrical demand growth in Uganda.

The base, high and low PSIP demand forecasts are presented in Table 4-11 and summarised in Figure 4-19 and Figure 4-20 below.

Table 4-11 PB Base, High and Low Demand Forecast for Uganda

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

Generation (GWh)

Peak Demand (MW)

Load Factor (%)

2009 2784 541 58.7% 2877 561 58.5% 3397 597 65.0%2010 2901 570 58.1% 3026 596 58.0% 3982 702 64.8%2011 3012 597 57.6% 3188 633 57.5% 4564 805 64.7%2012 3121 623 57.2% 3371 673 57.2% 5146 908 64.7%2013 3203 643 56.9% 3560 715 56.8% 5663 998 64.8%2014 3279 662 56.5% 3788 764 56.6% 6165 1084 64.9%2015 3351 679 56.3% 4030 816 56.4% 6651 1167 65.1%2016 3419 695 56.2% 4288 871 56.2% 7122 1247 65.2%2017 3481 710 56.0% 4561 929 56.0% 7577 1324 65.3%2018 3540 724 55.8% 4851 990 55.9% 8018 1398 65.5%2019 3622 741 55.8% 5123 1045 56.0% 8518 1480 65.7%2020 3676 750 56.0% 5362 1091 56.1% 8977 1551 66.1%2021 3778 772 55.9% 5685 1158 56.0% 9537 1647 66.1%2022 3913 800 55.8% 6056 1233 56.1% 10178 1759 66.1%2023 4048 828 55.8% 6434 1310 56.1% 10831 1873 66.0%2024 4184 857 55.7% 6821 1389 56.1% 11497 1990 66.0%2025 4321 886 55.7% 7216 1470 56.0% 12175 2109 65.9%2026 4459 915 55.6% 7620 1552 56.0% 12867 2231 65.8%2027 4598 944 55.6% 8031 1636 56.0% 13570 2355 65.8%2028 4738 973 55.6% 8450 1722 56.0% 14287 2482 65.7%2029 4880 1003 55.5% 8878 1809 56.0% 15016 2612 65.6%2030 5022 1033 55.5% 9313 1898 56.0% 15757 2744 65.6%2031 5065 1032 56.0% 9754 1978 56.3% 16548 2883 65.5%2032 5246 1069 56.0% 10203 2069 56.3% 17348 3025 65.5%2033 5428 1107 56.0% 10659 2162 56.3% 18156 3168 65.4%2034 5611 1145 55.9% 11123 2257 56.3% 18972 3312 65.4%2035 5796 1184 55.9% 11594 2353 56.2% 19797 3459 65.3%2036 5982 1223 55.8% 12072 2450 56.2% 20629 3607 65.3%2037 6170 1262 55.8% 12559 2549 56.2% 21470 3757 65.2%2038 6358 1301 55.8% 13052 2650 56.2% 22319 3908 65.2%




Figure 4-19 PB Peak Demand Forecast for Uganda (MW)

Figure 4-20 PB Sent Out Generation Forecast for Uganda (GWh)

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Final Master Plan Report WBS 1200 Generation supply study May 2011 & planning criteria


WBS 1200 Generation Supply Study

and Planning Criteria

Final Master Plan Report i WBS 1200 Generation supply study May 2011 & planning criteria


TABLE OF CONTENTS

1 SCOPE AND OBJECTIVES .................................................................................. 1-1 1.1 Objectives .............................................................................................................. 1-1 1.2 Scope of Study ....................................................................................................... 1-1 1.3 Covered Geographic area ...................................................................................... 1-3 1.4 Methodology .......................................................................................................... 1-5 1.4.1 Data completion and harmonization for new power options .................................. 1-6

2 DATA SOURCES .................................................................................................. 2-1 2.1 Primary reference reports ...................................................................................... 2-1 2.2 List of references.................................................................................................... 2-2

3 CRITERIA FOR GENERATION PLANNING ......................................................... 3-1 3.1 Scope ..................................................................................................................... 3-1 3.2 Economic criteria.................................................................................................... 3-1 3.2.1 Objective function................................................................................................... 3-1 3.2.2 Study period and reference year for discounting ................................................... 3-2 3.2.3 Discount rate .......................................................................................................... 3-2 3.2.4 Escalation .............................................................................................................. 3-2 3.2.5 Shadow pricing ...................................................................................................... 3-3 3.2.6 Cost of un-served energy ....................................................................................... 3-3 3.2.7 Allocation of costs for multipurpose projects .......................................................... 3-4 3.3 Generation planning criteria ................................................................................... 3-4 3.3.1 Reliability criteria and reserve ................................................................................ 3-4 3.3.2 Outage rates .......................................................................................................... 3-4 3.3.3 Plant service lives .................................................................................................. 3-5 3.3.4 Retirement of existing plant.................................................................................... 3-5 3.3.5 Rental units ............................................................................................................ 3-6 3.3.6 Operation, maintenance and other costs ............................................................... 3-6

4 EXISTING AND FUTURE GENERATION OPTIONS BY COUNTRY ................... 4-1 4.1 Hydrology and hydro generation analysis .............................................................. 4-1 4.1.1 Hydrology ............................................................................................................... 4-1 4.1.2 Calibration of hydro plants production .................................................................... 4-1 4.2 Total identified options by country .......................................................................... 4-2 4.3 Summary of present and future generation resources ......................................... 4-19

5 FUTURE HYDROELECTRIC OPTIONS ............................................................... 5-1 5.1 Identifications of new hydroelectric options ............................................................ 5-1 5.2 Capital costs for future hydro projects .................................................................... 5-4 5.2.1 Procedure for updating costs ................................................................................. 5-4 5.2.2 Mitigation costs ...................................................................................................... 5-8 5.2.3 Interest during construction .................................................................................... 5-9 5.3 Minimum lead times to on-power ......................................................................... 5-10 5.4 Primary screening of future hydro options ........................................................... 5-11 5.4.1 Rejected options .................................................................................................. 5-16 5.5 Future hydro generation costs ............................................................................. 5-18 5.6 Ranking by cost and earliest availability .............................................................. 5-24

Final Master Plan Report ii WBS 1200 Generation supply study May 2011 & planning criteria


6 FUTURE THERMAL OPTIONS ............................................................................. 6-1 6.1 Capital costs for future thermal projects ................................................................. 6-1 6.1.1 Generic capital costs .............................................................................................. 6-1 6.1.2 Interest during construction .................................................................................... 6-5 6.2 Minimum lead times to on-power ........................................................................... 6-6 6.3 Plant heat rates ...................................................................................................... 6-7 6.4 Fuel prices ............................................................................................................. 6-7 6.4.1 Oil ........................................................................................................................... 6-7 6.4.2 Natural Gas ............................................................................................................ 6-8 6.4.3 Coal ........................................................................................................................ 6-9 6.4.4 Geothermal .......................................................................................................... 6-10 6.4.5 Net calorific value ................................................................................................. 6-10 6.4.6 Fuel forecast ........................................................................................................ 6-10 6.5 Future thermal generation costs .......................................................................... 6-12 6.6 Thermal plant retirements .................................................................................... 6-17

7 IDENTIFICATION OF POTENTIAL REGIONAL PROJECTS ............................... 7-1

LIST OF FIGURES

Figure 1-1 Country resources and potential interconnections ......................................... 1-2 Figure 1-2 Eastern DRC study area ................................................................................ 1-5 Figure 4-1 Average annual hydro production per country ............................................... 4-2 Figure 6-1 Evolution of NG prices for different regions .................................................... 6-8 Figure 6-2 Fuel forecast ................................................................................................. 6-12

LIST OF TABLES

Table 2-1 List of project reports ...................................................................................... 2-1 Table 2-2 List of References .......................................................................................... 2-2 Table 3-1 Index values for escalating capital costs ........................................................ 3-3 Table 3-2 Selected outage rates for generation planning ............................................... 3-5 Table 3-3 Plant service lives ........................................................................................... 3-5 Table 3-4 Operation, maintenance and other costs ....................................................... 3-6 Table 4-1 Annual hydro production for identified options ............................................... 4-2 Table 4-2 Burundi Generation ........................................................................................ 4-4 Table 4-3 Djibouti Generation ......................................................................................... 4-5 Table 4-4 Eastern DRC Generation ............................................................................... 4-6 Table 4-5 Egypt Generation ........................................................................................... 4-7 Table 4-6 Ethiopia Generation ........................................................................................ 4-9 Table 4-7 Kenya Generation ........................................................................................ 4-11 Table 4-8 Rwanda Generation ..................................................................................... 4-13 Table 4-9 Sudan Generation ........................................................................................ 4-14 Table 4-10 Tanzania Generation .................................................................................... 4-16 Table 4-11 Uganda Generation ...................................................................................... 4-18 Table 4-12 Present and future potential generation resources ...................................... 4-19 Table 5-1 Typical cost values for projects ...................................................................... 5-2 Table 5-2 List of identified new hydro options ................................................................ 5-3 Table 5-3 Ethiopia previous estimated costs for hydro options (Costs in MUSD) .......... 5-6

Final Master Plan Report iii WBS 1200 Generation supply study May 2011 & planning criteria


Table 5-4 Sudan previous estimated costs for hydro projects (Costs in MUSD) ............ 5-7 Table 5-5 IDC - typical increments for hydro projects..................................................... 5-9 Table 5-6 IDC for hydroelectric projects (Interest rate = 10%) ..................................... 5-10 Table 5-7 Generic times for project activities ............................................................... 5-10 Table 5-8 Minimum on-power lead times for hydroelectric plants (years) .................... 5-11 Table 5-9 Classification of hydro resources ................................................................. 5-13 Table 5-10 Primary screening of future hydro options .................................................... 5-14 Table 5-11 Potential DRC sites for after 2017 ................................................................ 5-18 Table 5-12 EAPP Region Future Hydroelectric projects – Unit Generation costs .......... 5-20 Table 5-13 EAPP Hydro Options – Ranking by unit cost and earliest on-power ............ 5-25 Table 5-14 Total new hydro for the first two 5 year periods of the study (MW) .............. 5-28 Table 6-1 Comparative costs for coal fired STPPs - 2009 $ excluding IDC ................... 6-2 Table 6-2 Typical unit costs for STPP ............................................................................ 6-2 Table 6-3 Comparative costs for Geothermal, OCGT and CCGT - 2009 $, no IDC ....... 6-4 Table 6-4 Unit costs for Generic Thermal plants - 2009 $, no IDC ................................. 6-5 Table 6-5 Typical disbursement schedules during construction ..................................... 6-5 Table 6-6 Interest during construction - typical increments for thermal plants ............... 6-6 Table 6-7 Generic TPP Unit costs - $/kW with IDC ........................................................ 6-6 Table 6-8 Minimum on-power lead times for thermal plants ........................................... 6-7 Table 6-9 Heat Rates for different Thermal Plants ......................................................... 6-7 Table 6-10 Oil price projections - 2038 ............................................................................. 6-8 Table 6-11 NG price projections - 2038 ............................................................................ 6-9 Table 6-12 Coal price projections - 2038 .......................................................................... 6-9 Table 6-13 Typical net calorific values ........................................................................... 6-10 Table 6-14 Fuel Forecast ............................................................................................... 6-11 Table 6-15 Illustrative future unit generation costs in c/kWh, based on 75% CF ........... 6-13 Table 6-16 Thermal generation costs by country ........................................................... 6-14 Table 6-17 Existing and committed thermal retirements ................................................ 6-17

Final Master Plan Report 1-1 WBS 1200 Generation supply study May 2011 & planning criteria


1 SCOPE AND OBJECTIVES 1.1 Objectives The objectives of this program component are to:

• Update the available data on generation supply for each country, including the existing facilities, rehabilitation projects, ongoing plant construction, supply import and export, and any other stations that may be developed during the planning period (2013 to 2038).

• Establish a list of existing and potential energy sources suitable to meet the demand of the combined systems, including at least hydroelectric, thermal and geothermal sources.

• For each candidate plant, list information on capital costs (including environmental mitigation costs), operation and maintenance costs and earliest in service date

• For hydroelectric options, rank projects in accordance with attractiveness including cost.

• Explain the generation planning criteria such as reliability criteria, outage rates and service lives

• Provide a hydrology database for all the hydro sites used in the study

• Update the hydro energy capability of all the hydro plants considered in the study

The listing of existing, committed and future generation options will provide the basic data base for the supply-demand analysis (Module 1C-1300), and the subsequent generation/transmission financial and economic studies in phase II. Note this activity covers generation only. Transmission is dealt with in Module 1D.

1.2 Scope of Study The requirements for the generation supply study are defined in the list of objectives provided above.

The scope may be considered in two parts:

• The identification and data assembly for all existing generation plants, plants that are committed for the period up to January 2013 and future generation options that can be used to meet national load demands up to year 2038, on a country by country basis.

• The identification and data collection for projects, both existing and future, that may be used to meet the demand of combined systems.

The development of the data bases of country resources for the first part of the scope requirement has been based on the most recent master plans available, supplemented by any other recent presentations on behalf of the energy ministry or electric utility of each country. The initial listing of these resources was included in the Inception Report, and these have been reviewed by the national utilities and any comments or requested changes arising from that review have been incorporated in the listings included with this report. The updated country lists of existing and identified new options are provided in Section 4.2.

The identification of projects that could be part of a regional supply arises directly out of the first stage. Clearly any projects with the potential to provide regional supply, i.e. outside of the country of the project, will largely be defined by size. However a preliminary comparison between load demands and available indigenous resources for the planning period has



shown that, with the exception of Ethiopia, eventually the demand in each country will exceed local supply even without screening out higher risk projects.1

Thus the identification and eventual assessment of larger projects that could provide a contribution to a regional supply backbone, has to take into account timing, and the option of pre-building larger projects that could provide exports for a number of years. This, in turn, requires that generation plans for regional country groupings be evaluated, to determine the economics of any such pre-build strategies.

Figure 1-1 below provides an illustration of potential in-country resources as of year 2038, based on existing plant and new generation options based on indigenous resources only. This figure also indicates which countries may be expected to have a surplus of resources up to the end of the planning period.

For the generation supply study, the identification of these regional projects has been based solely on installed capacity. The criterion used has been to select projects with an installed capacity that is equal to or more than two years of load growth in the country of the project. These projects are listed in Section 7.

Figure 1-1 Country resources and potential interconnections

1 Projects with potential constraints for environmental, social or legal issues. i.e. excluding generation using imported fuels but including nuclear plants.

EGYPT62,200 MW

SUDAN15,300 MW

ETHIOPIA14,300 MW

DJIBOUTI200 MW

KENYA7,000 MW

UGANDA3,400 MW

TANZANIA6,100 MW

DRC

Countries with export potentialCountries with import needsPower transfer

between countries

RWANDA500 MW

DRC2100 MW

BURUNDI500 MW

Installed capacities based on current master plans for year 2030

Values are indicative and include presently planned transfers



1.3 Covered Geographic area

The study area covers the countries of the member utilities of the EAPP which are:

REGIDESO (Burundi), SNEL (DRC), EEHC (Egypt), EEPCo (Ethiopia), KenGen and KPLC (Kenya), ELECTROGAZ (Rwanda), NEC (Sudan) and SINELAC (DRC, Rwanda and Burundi). In addition EdD (Djibouti) is included.

The primary objective of the study is to determine the opportunities for and viability of regional supply through interconnections and power trading. In that context the existing, committed and planned interconnections are an important aspect of the study. These are:

Existing interconnections:

• DRC, Burundi, and Rwanda interconnected from a jointly developed hydro power station Ruzizi II, (capacity 45 MW) operated by a joint utility (SINELAC)

• Cross-border electrification between Uganda and Rwanda, Tanzania and Uganda, and Kenya and Tanzania

• Kenya – Uganda interconnection

• Egyptian power system interconnection through Libya to other Maghreb countries and Southern Europe; and through Jordan to Eastern Mediterranean

Ongoing projects in the region include:

A preliminary compilation of information has shown the following projects with tentative dates:

• Ethiopia-Kenya 500 KV HVDC: final feasibility study out. Commissioning 2013

• Ethiopia-Sudan 220 KV: commissioning end of 2010

• Ethiopia-Djibouti 283KM of 220 KV: commissioning by 2011

• Ethiopia-Sudan Sudan-Egypt 500 HVDC: feasibility study report has been prepared. Financings are being sought

• Kenya – Tanzania 400 KV / NELSAP: commissioning 2015

• Kenya-Uganda 220 KV / NELSAP: commissioning 2014

• Uganda–Rwanda 220 KV /NELSAP: commissioning 2014

• Rwanda-Burundi 220 KV / NELSAP: commissioning 2014

• Burundi-DRC 220 KV / NELSAP: commissioning 2014

• Rusumo Falls Project 63 MW: commissioning 2016

Planning initiatives

Presently, Kenya, Tanzania and Uganda, under the auspices of the East African Community (EAC), are developing plans to (i) interconnect and strengthen their power systems in order to share power supplies, and (ii) further extend the power system interconnections to countries outside EAC countries.



A series of studies have been completed in the last 5 years that cover opportunities for cross-border interconnections in the region. These include the EAPMP2 [7], SSEA3 [1,2], ENPTPS4 [10], Ethiopia-Djibouti Interconnection, and the 2004 World Bank Scoping Study5.

Implementation planning is going ahead for the interconnection of the national grids for the five equatorial Lakes countries (Burundi, Kenya, Uganda, DRC, and Rwanda).

DRC study area

The current study is considering generation sources within the EAPP that could provide either surplus generation or markets for other EAPP countries with surpluses.

The situation of the Congo is unique. Currently the DRC exports to the SAPP via Zambia from 220 kV lines from South Katanga. This supply is provided from Inga I and II, and from the three midsized hydro projects in South Katanga, that provide almost all their output of about 460 MW to Zambia / SAPP. By comparison the Eastern provinces of DRC are interconnected north south, and with Rwanda - to the Ruzizi plants. The most important of the existing and potential hydroelectric resources in the DRC are in the western part of the country and in South Katanga. The DRC provides major exports to Zambia and the SAPP from the Inga plants on the Congo River and hydro projects in South Katanga.

In the very long term there is the possibility that Grand Inga can be developed (44,000 MW) with the potential to supply the SAPP, the Mediterranean Power Pool along North Africa and the Northern part of the Nile basin among other regions. However this possibility cannot be considered sufficiently well defined to include Grand Inga supply as part of the current study. Irrespective of any technical and financing difficulties this project could not be brought into service within 20-25 years.

Given this situation, the part of the DRC that is considered relevant to the EAPP is considered to be limited to the parts of the DRC that are within the Nile basin. This definition has also been used in the previous SSEA study by SNC-Lavalin for the NBI/NELSAP, and the 2007 NBI interconnection study. These areas are shown in the figure overleaf as shaded, and are made up as follows:

• Oriental (eastern part)

• Kivu North

• Maniema (eastern part)

• Kivu South

• Katanga (northern part)

2 Uganda, Kenya and Tanzania 3 Burundi, Eastern DRC, Kenya, Rwanda, Tanzania and Uganda 4 Egypt, Sudan and Ethiopia 5Joint UNDP/WB Energy Sector Management Assistance Program (ESMAP), Opportunities for Power Trade in the Nile Basin, Final Scoping Study, January 2004



Figure 1-2 Eastern DRC study area

1.4 Methodology The generation supply study consists of four steps for each country:

• Identification of all existing generating plants, including basic identification information such as: name, type, installed capacity and (for hydro) energy generation capability.

• Identification of all identified future generation options, again including name, type, installed capacity and (for hydro) energy generation capability.

• Collection of plant data for existing and future plant options, as is required for generation planning purposes

• Harmonization of project information (e.g., to a common cost or reliability level) and preparation of the generation data base.

In the context of this study, existing plants include committed new plant to be commissioned by January 2013. The notion of future power options applies to the planning period of 2013 to 2038.

Required plant data (existing, committed and planned projects) for generation expansion modeling includes:

• Technical characteristics (forced outage rates, maintenance periods, heat rates of each plant or unit, reservoir characteristics, design heads, and long term inflows)

• Performance characteristics (nameplate and effective capacity, firm capacity under minimum reservoir operating levels, thermal efficiency, firm and average energy levels)

• Fixed and variable operating costs



• Capital costs for committed and planned projects, including construction schedules of disbursements

• Information on project level of preparation, including environmental approvals

1.4.1 Data completion and harmonization for new power options Data on new power options was harmonized to the extent feasible to improve the validity of the project and plan comparisons. This included the following elements:

Capital costs given in the previous studies were adjusted for inflation, using the indices provided in Section 3. For all projects the “overnight” cost i.e., excluding interest during construction, was to be used, and an amount for IDC was added. The IDC amount was determined as described in Section 3.

Mitigation costs were reviewed and harmonized. The estimates given in previous reports were reviewed. If mitigation costs are included, these were retained. Where no mitigation costs are included, then an amount equal to 5 % of the project cost was added. These were included in the confirmed capital costs.

Project lead times to on-power were taken from the reference reports, and reviewed/adjusted. If insufficient information was available, lead times were based on the planning criteria shown in Section 5.3 and 6.2, that relate plant size and level of preparation to overall lead time. It is essential that realistic lead times are used in developing new generation sequences.

Fixed and variable operation and maintenance costs were based on international experience from the SNC-Lavalin data base, as are included in the planning criteria.

Technical characteristics were obtained from previous reports (or from country electric utilities for existing plants), and are summarized in the tables included in Module 1C-1300

Performance characteristics will be obtained from previous reports (or from country electric utilities for existing plants), supplemented by SNC-Lavalin experience data from international sources.

Information on trans-border imports or exports was obtained from the country electric utilities, NELSAP, ENPTPS and the EAPP.

Hydro generation capability - The terms of reference require that "the results of the hydro systems energy capability for the region be determined by the review of each country´s hydrology". It is noted that this work for Tanzania was up to date. Also the previous studies for hydro projects in Ethiopia and Sudan are recent and used hydrology updated for those studies. In some cases missing periods of hydrological information were filled with the methodology described in Appendix B. For this generation supply study the generation estimates from previous reports were used. The later generation planning studies will use hydrologic sequences that are presently being updated.

Other renewable energy sources such as large solar or wind energy projects were included in the data base.

Project data for existing, committed and evaluated new power options were combined in the form of a catalogue, as is shown later in Module 1C - 1300. This is the data required for the SNC-Lavalin generation planning models (SDDP, OPTGEN)6 to be used in later activities.

6 A description of SDDP and OPTGEN can be found in the appendices of Module 1C – 1300.



2 DATA SOURCES 2.1 Primary reference reports During the Inception Phase data has been assembled from primary sources such as original project reports, secondary sources such as master plan studies, and as feedback from participating utilities.

Identified studies that contain key information for generation planning include the following:

Table 2-1 List of project reports Report Coverage

Ethiopia – Master Plan 2006 Ethiopia master plan of load forecast, generation and transmission

Ethiopia – Master Plan 2008Summary update

Ethiopia master plan of load forecast, generation and transmission

Ethiopia – Djibouti interconnection Planned supply from Ethiopia to Djibouti Ethiopia – Prefeasibility studies of Border, Mandaya, (included in ENPTPS –2007)7

Major hydro developments on the blue Nile

Ethiopia – Prefeasibility studies of Beko Abo and Karadobi hydro on Blue Nile Abay

Major hydro developments on the blue Nile

EAPMP, 2005 Uganda, Kenya, Tanzania and interconnections NELSAP ‐ SSEA . 2007 Uganda, Kenya, Tanzania, Burundi, Eastern DRC and RwandaNBI Preliminary Basin‐Wide Study, 2008 Nile basin countriesNELSAP ‐ Interconnections of the electricity networks of the Nile Equatorial countries. 2007

Equatorial Lakes countries

NELSAP ‐ Rusumo Falls feasibility study ‐ 2009 Rusumo Falls project, and alternative generation optionsNELSAP ‐ Rusumo Falls transmission studies Rusumo Falls project, transmission requirements

interconnection to Rwanda, Burundi and West Tanzania, centred on the Rusumo hydro project

EGL – Studies on Ruzizi III and Sisi 5 (Ruzizi 4) hydro sites (in progress)

Draft feasibility and prefeasibility studies on the these two projects respectively

Kenya Power System Master Plan December2008

Kenya new generation options

Uganda Power System Master Plan – 2009 Uganda new generation optionsUganda – Studies of Karuma hydro being done for the Ministry of Energy

Cost and generation data for the Karuma site downstream of Bujagali

Sudan – Hydro studies by Fichtner Prefeasibility studies of hydro sites on the Nile, in the South of Sudan

Sudan – Power System Master Plan Sudan new generation optionsTanzania Power System Master Plan – 2009 Tanzania new generation optionsRwanda – Power System Master Plan (in progress)

Rwanda new generation options

Blue Nile basin study ‐ USBR, 1964 – On request

Basin study with original information on site identification and selection, including the Mabil project

Awash IV feasibility study – Electroconsult, 2006

Project report

Genale III feasibility study – Lahmeyer, 2005 Project report

7 A further study on the development of these projects on the Blue Nile / Abbay rivers is about to start, (Joint Multipurpose Program JMP-1) and will provide additional information on these proposed projects



Report Coverage

Genale IV pre‐feasibility study ‐ Lahmeyer, 2006

Project report

Gojeb feasibility study ‐ H. Humphreys, 1997 Project reportGeba feasibility study – Norplan and Norconsult, 2005

Project report

Baro I&II feasibility study ‐ Lahmeyer, 2005 Project reportAleltu East feasibility study – Acres, 1995 Project reportAleltu basin study , 1994 . Not obtained Project reportChemoga Yeda Feasibility study – Lahmeyer, 2005

Project report

Halele Worabesa Stage I feasibility study ‐ Lahmeyer, 2000

Project report

Halele Worabesa Stage II feasibility study – Lahmeyer, 2005

Project report

2.2 List of references During the preparation of the data base for existing and new generation options a list of references were prepared, including the above reports, which are keyed by ID number to the project information provided in the country tables in Section 4.2.

This list of references follows in Table 2-2 below:

Table 2-2 List of References

References

1 SSEA 1 (2005)

2 SSEA II/III (2006)

3 PSMP Tanesco (2009)

4 Feasibility study Rusumo 2008

5 DRC/SSEA II report

6 Male Cifarha ‐ Les Resources Hydroeléctriques du Zaïre 1994

7 EAPMP

8 ENTRO ToR

9 NBI Preliminary Basin Study

10 ENTRO EDF Eastern Nile Power Trade Program Study 2007‐ including hydro prefeasibility studies M3 Vol 3

11 NBI Fichtner prefeasibility, Study on Electrical Transmission Lines Linked to Rusumo Falls Hydroelectric Generating Station, October 2008

12 EU‐EGL Fichtner Etude de faisabilité pour l´aménagement hydroélectrique de Ruzuzi III April 2009

13 EU‐EGL Fichtner Etude de préfaisabilité pour l´aménagement hydroélectrique de Sisi 5 June 2009

14 EEHC Annual report 2007/8

15 Ethiopia Central Statistics Agency ‐ Installed generating capacity and electricity production by station 2005/6

16 Hydropower of Ethiopia ‐ Status, potential and prospects ‐ Solomon Seyoum Hailu



References

17 Electrogaz 2009

18 MINIFRA semi annual report 2009

19 Sudan NEC 2008 Annual Report

20 Kenya country presentation at EAPP workshop Sept 09

21 Ethiopia country presentation at EAPP workshop Sept 09

22 Sudan NEC LTPSPS Generation data book (2007)

23 Feasibility study Rusumo Falls 2008 (draft)

24 Ethiopia Review of Power system Expansion Master Plan 2005

25 Prefeasibility studies of Border and Mandaya ‐ EdF/ENTRO Power Trade Study Module M5

26 Power projects proposed and under construction‐www.skyscrapercity.com

27 Kenya Least Cost Power Development Plan 2009‐30, Dec 2008

28 Kenya Least Cost Power Development Plan 2005‐25, 2004

29 East Africa business News Nov 27, 2009

30 Sudan NEC LTPSPS Generation plan report 5 (2007)

31 Karadobi Multipurpose project, pre‐feasibility study Norplan 2006

32 Genale 3D Multipurpose Project ‐ Feasibility study ‐ Lahmeyer 2007

33 Genale 6D Multipurpose Project ‐ Feasibility study ‐ Norplan 2009

34 Feasibility study of Chemoga Yeda I and 2 Lahmeyer 2006

35 Geba Hydroelectric Project ‐ Feasibility study ‐ Norplan 2005

36 Feasibility Study of Halele Werabesa Sate I hydroelectric project ‐ Lahmeyer 2000

37 Uganda ‐ Generation Plan (draft) Report, PB October 2009

38 Ethiopia Power System Expansion Master Plan Update 2006

39 Feasibility study of Gojeb Medium Hydropower Project, Humphreys, 1997

40 Beko Abo Multipurpose Project ‐ Reconnaissance Study, NORPLAN, 2007 (Nov)

41 Gibe IV project profile EEPCO, 2009

42 Feasibility Study of the Baro Multipurpose Project ‐ final report ‐ NORPLAN, September 2006

43 Gibe IV and V update report ‐ Pietrangeli /Salini June 2008

44 Aleltu Basin Study ‐ Acres International, 1994

45 Awash IV Feasibility Study ‐ ELC 2006

46 Ethiopia ‐ Investment Opportunities in Geothermal Energy Development in Six Selected Geothermal Projects, Ministry of Mines and Energy December 2008

47 EEPCo ‐ Highlights of power sector development program 2009‐2018, June 2008

48 Semliki hydro prefeasibility study, 2005

49 Hydropower in Ethiopia ‐ Staged construction of Tekeze Dam, Waterpower April 2009



References

50 Burundii country presentation at EAPP workshop Sept 09

51 NELSAP Interconnection study October 2007

52 Kenya ‐ Hydroelectric Cascades. Appendix to Least cost plan 2009‐30 (Ref 27)

53 Kenya TPP Characteristics ‐ KENGEN/KPLC meeting ‐ EAPP Inception Mission (2009)

54 Uganda River Nile Hydro Potential ‐ Uganda Electrical Generation Company ‐ Hydro Power Development Unit ‐ EAPP Inception Mission (2009)

55 Rwanda Expansion Plan (2002)

56 Gibe 3 Ethiopia Hydro Project ‐ Official Webpage ‐ EEPCo (2009)

57 Sudan NEC LTPSPS Hydrology report (2007)

58 Merowe: The Largest water resources project under construction in Africa ‐ Lahmeyer/Dams‐Sudan (2006)

59 EEHC Official E‐mail communications ‐ TPP and HPP characteristics (2009)

60 Djibouti Least Cost Electricity Master Plan (Final Report) ‐ PB ‐ November 2009

61 Uganda Potential Hydro Power Sites ‐ Final Report ‐ SWECO International (Dec. 2000)

62 Bujagali Hydro Power Project Social and Environmental Assessment ‐Main Report ‐ Burnside (2006)

63 EEPCO email 08‐Feb‐2010

64 Rapport définitif de faisabilité de l'aménagement de KABU 16 ‐ Vol. 1 ‐ SOGREAH (1995)

65 Etude de Préfaisabilité des aménagements hydro‐électriques Jiji et Mulembwe ‐ Vol. 1&2 ‐ BEROCAN (2000)

66 Kaganuzi multipurpose project ‐ Feasibility study ‐ Vol. III ‐ Draft Report ‐ NORCONSULT (1987)

67 Faisabilité détaillée de l'aménagement hydro‐électrique de Nyabarongo ‐ SOGREAH (1999)

68 NEC Sudan Projects Profile 2006‐2011 – Issued 2009 ‐ www.necsudan.com



3 CRITERIA FOR GENERATION PLANNING 3.1 Scope The characterization of project performance and cost has to reflect standardized criteria and parameters for hydro and thermal plants cost and performance, and for generation planning. These data are shown in the following subsections. Additional information used for the calculation of generation costs is provided in Sections 5 and 6.

Economic criteria • Reference year and study horizon

• Discount rates and escalation

• Cost of un-served energy

• Shadow pricing

Generation planning • System reliability criteria (e.g., LOLP/LOLE)

• Reserve margins

• Outage rates and maintenance schedules

• O & M costs, and other owners costs for the region

• Service lives

Hydroelectric plants: See Section 5 • Capital costs adjusted to a standard reference year

• Rated and firm capacity

• Firm and average energy

• Capital cost disbursement schedule

Thermal plants: See Section 6 • Unit costs for different plant types / sizes and fuel types

• Station service

• Heat rate

• Fuel sources and costs

• Fuel calorific value

3.2 Economic criteria 3.2.1 Objective function The general purpose of generation investment planning is to determine the least cost schedule of commissioning of new generation units over a given period of time within acceptable levels of reliability of power supply.

More precisely, the objective cost function is:

min [NPV(Investment costs + O&M costs + Fuel costs + Un-served energy cost + Externalities)]

where:



• NPV: Net Present Value over the planning period (2013-2038)

• Investment costs: generation and interconnection investment costs over the planning period

• O&M costs: O&M cost of generation and interconnection over the planning period

• Fuel costs: Fuel cost of generation (TPP) over the planning period

• Un-served energy cost: cost of un-served energy (i.e. unsupplied) energy over the planning period

• Externalities: Other costs or benefits such as mitigation costs, irrigation benefits, etc…

3.2.2 Study period and reference year for discounting All costs are to be expressed in terms of mid 2009 costs. No further escalation is applied to capital costs or operating costs for the base case. The identification and assessment of new power options to meet the forecast load growth covers the period 2013 to 2038.

3.2.3 Discount rate The discount rate may be considered as the time value of money, and is used to calculate the present value of a series of future costs. While the discount rate may be linked to borrowing costs, for the purpose of planning studies the selection of an appropriate value should reflect the opportunity cost of capital. The discount rate will therefore tend to be higher in regions or countries where capital is relatively scarcer.

The discount rate is also affected by the use of escalation in comparative studies8. The discount rate for comparisons would be approximately higher by the amount of cost inflation, than the discount rate used for an analysis at constant prices (i.e. a 10 % discount with constant prices would yield the same answer as, say, a nominal rate of 13 % if 3 % escalation were included in all future costs). It is noted that a discount rate of 12 % was used in the 2009 TANESCO PSMP update, and was used in the EAPMP and in the Kenya 2004 and 2008 Least Cost Plan. This rate was also used in the 2004 study on the Zambia-Tanzania-Kenya Interconnector. However the World Bank SSEA study for the East Africa region [1, 2] that ended in 2006 based all generation planning on a discount rate of 10 %.

The choice of discount rate is discretionary. Use of a higher discount rate will tend to favour thermal plants in cost comparisons with hydro due to their lower initial costs, but higher yearly operating costs, while lower discount rates would favour hydroelectric plants, where most of the expenditures are at the beginning of the project cycle. A real discount rate of 10% (i.e. excluding inflation) will be used in converting capital costs into equivalent annual costs over the life of an asset. In the context of this study, a discount rate of 10% will also be used for very preliminary comparisons of unit generation costs for initial screening of options.

3.2.4 Escalation Information on escalation may be taken from two sources: the US Department of Labour statistics and the USBR construction costs trends index. These provide similar results, as compared below:

8 Econometric Analysis of Fishers Equation – American Journal of Economics and Sociology, Jan 1, 2005, Peter Philips



Table 3-1 Index values for escalating capital costs US Dept Labour USBR

Year Generation Transmission Actual 2003=100

2003 100 100 250 100

2004 105.2 101.4 274 110

2005 121.6 101.3 288 115

2006 128.0 103.3 303 121

2007 132.0 104.7 316 126

2008 145.5 110.7 345 138

2009 133.8 (p) 113.2 (p) 329 132

The above sources are:

- The US Department of Labour Producer Price Index Industry Data for:

• Electric Power Generation

• Bulk Power Transmission and Control

- The US Bureau of Reclamation Construction Costs Trends – composite trend index for October of each year.

Capital cost adjustments for hydro and thermal projects will be based on the US Department of Labour indices. It is noted that TANESCO use 2.5 % per year to index or update project capital costs, to a reference planning year. Future fuel costs are from projections by the Energy Information Administration (Section 6.4).

3.2.5 Shadow pricing Shadow pricing is not used, as there is no restriction on currency trading. However differences in foreign exchange requirements between alternative plans should be identified.

3.2.6 Cost of un-served energy The cost of un-served energy depends on the perceived cost of outages (lost energy) to consumers. A typical value used in the East African region for planning studies has been 1.10 US$/kWh. This value is appropriate and will be used in the EAPP study.

It is noted that un-served energy is treated as part of the operating cost since it is modeled as an artificial thermal plant with high fuel cost and infinite capacity, and thus may affect the timing of new plant additions, and amount of reserve that provides the least cost plan. The assumption of a relatively high cost of un-served energy would lead to a requirement for more new generation to reduce operating costs.

In practice the development of alternative generation plans should require common reliability levels to be met, so un-served energy, if it exists should be similar for all alternatives, and thus this factor would not normally be a significant factor in comparisons of alternative generation plans.



3.2.7 Allocation of costs for multipurpose projects A number of identified hydropower options also have the potential for providing benefits from flow regulation, i.e. for flood control and irrigation.

Conventionally for some “economic” planning studies a credit is applied for such non power benefits. For this EAPP study, given the scarcity of estimates of potential benefits, or data from which these could be estimated, no credit will be given for secondary (non-power) benefits from multipurpose projects. It also has to be recognized that as benefits come from outside the electrical sector, it would be improbable that compensation for any such benefits would accrue to the operator of the power project.

However it may be noted that in an economic evaluation of multipurpose projects, an approximation for comparison purposes could be made by assuming that 50% of the cost of the dam would be shared, i.e., financed by some agency responsible for the irrigation scheme or civil protection aspects such as flood control.

3.3 Generation planning criteria 3.3.1 Reliability criteria and reserve For systems where hydro makes an important component of the supply balance, normally a generation reliability criteria based on energy is needed. The reason is that in a hydro-dominated system the installed capacity normally exceeds the peak load by more than 20-30% but the amount of firm energy is only slightly above the demand for energy. In this case a LOLP-based criterion will not capture the decrease in energy reserve over time.

The historical record of hydrology used in this study consists of 35 years of monthly values. The criteria used for hydro-dominated systems are based on probabilities. In the case of the simulations with historic monthly inflow records that are used for the present study, the criteria to be met for every month in the study period are the following:

• The probability of deficit must be less than 100%. This means that for a given month in the study period, not all of the hydro sequences examined may result in deficits, even if the deficits are small, and;

• The probability that in any month the deficit is greater than 2% of the energy demand should be less than 5%. This means that no more than 2 hydro sequences should produce deficits greater than 2% of the demand9. It is considered that deficits of 2% of the demand or lower can be managed by the system operator by making some operational adjustments in the system and the probability of this event occurring should be small (equal or less than 5%).

For thermal systems typically a maximum loss of load expectation (LOLE) of 5 days per year, and a reserve margin on installed capacity of not less than the size of the largest unit is used. These criteria are considered appropriate and will be retained for this study.

3.3.2 Outage rates The availability of generation for a plant is the result of the duration of planned or scheduled maintenance periods and forced outage rates. The following tabulations show the rates selected for this study. These are similar to those used in the EAPMP.

9 2 sequences represent 2/35 ~ 5%



Table 3-2 Selected outage rates for generation planning Generation type

Scheduled maintenance (weeks per year)

Forced outage Rate (% of time per year)

Availability factor (%)

Coal STPP 6 8 80

Oil STPP 4 7 80

OCGT 4 5 80

CCGT 3 5 80

MSD 5 8 75

LSD 4 8 75

Geothermal 2 6 80

Cogeneration 8 6 75

Nuclear 4 3 90

Hydroelectric 4 0 90

3.3.3 Plant service lives The following service lives will be used in determining average unit generation costs for preliminary comparisons, and for determining retirement dates for existing and future plant in the development of generation plans:

Table 3-3 Plant service lives Generation type Normal service life (years)

OCGT 20

CCGT 20

MSD 20

LSD 25

Coal and oil STPP 25

Geothermal 25

Cogeneration 25

Nuclear 40

Hydroelectric plant 5010

3.3.4 Retirement of existing plant Existing generating units are assumed to be retired at the end of their normal “economic” service life, except for hydroelectric plants, which are assumed to remain in service. Assumed retirement dates for existing thermal plants will be as indicated in the national plans, or if not indicated, will be based on the above table. Retirement dates for new thermal

10 Normally extended by major equipment replacement and maintenance



will be in accordance with the above table.11 For the generation planning model the default on-power month is January, and retirement month is December.

3.3.5 Rental units Emergency leased units will not be included as a generation resource.

3.3.6 Operation, maintenance and other costs Unit generation costs include allowances for operation and maintenance, interim replacement, and insurance. For thermal plants, the operation and maintenance cost is separated into fixed and variable components. For hydroelectric plant, all O and M cost is considered as fixed.

Interim replacement is an annual allowance to cover periodic replacement of major equipment items that have a shorter service life than the overall project, such as turbines in a hydroelectric project.

The allowances shown below will be used.

Table 3-4 Operation, maintenance and other costs Plant type Unit size

(MW) Fixed O&M(US$/kW/yr)

Variable O&M(US$/kWh)

Interim Replacement (%)

Insurance(%)

Coal STPP 100‐500 50 0.0065 0.35 0.25

Coal STPP 50 70 0.0065 0.35 0.25

Oil STPP 100‐500 30 0.0045 0.35 0.25

Oil STPP 50 35 0.0045 0.35 0.25

OCGT 60 10 0.0050 0.35 0.25

CCGT 3x60 20 0.0040 0.35 0.25

MSD 50 20 0.0120 0.35 0.25

LSD 50 9 0.0100 0.35 0.25

Geothermal 70 35 0.0045 0.35 0.25

Cogeneration 20 70 0.0065 0.35 0.25

Nuclear 1000 75 Incl. in fixed 0.35 0.25

Hydroelectric All 10 0 0.25 0.10

11 Service life for Nuclear plants is taken from UK experience and scheduled retirement dates – World Nuclear Association web site - Nuclear Power in the UK, November 2009



4 EXISTING AND FUTURE GENERATION OPTIONS BY COUNTRY 4.1 Hydrology and hydro generation analysis The hydro energy is one of the most important natural resources in the Eastern Africa, for that reason and in accord with the TOR and the inception report, it was necessary to do an in-depth analysis of the hydrology and the potential hydro generation for the existing and future projects.

4.1.1 Hydrology The terms of reference require that "the results of the hydro systems energy capability for the region be determined by the review of each country´s hydrology". It is noted that this work for Tanzania was up to 2006 for 35 years of hydrological information in m3/s for a monthly base (1972-2006). To have the hydrological information for the other countries in the same base a model developed by the Latin American Energy Organization (OLADE) called SUPER was used to fill up the missing information. The hydrological model of SUPER uses a mathematical representation of time series of inflows at different sites. The parameters for these series are estimated on the basis of historical records. A probabilistic representation of the inflows and their time and space dependencies can be achieved using the mean monthly flows, the standard deviations in monthly flows, correlation between stations in the same month, serial correlation for the same station and correlation between successive months for different stations. For these analyses the model uses the Matalas model and the Crosby and Maddock method.

Appendix B includes a description of the hydrological model while the inflows database for all the countries on a monthly basis for the period 1972-2006 is included in Appendix C.

4.1.2 Calibration of hydro plants production Using the hydrological information produced with the hydrological model of SUPER, simulations of the hydro generation were carried out using the SDDP model. Each hydro plant’s yearly production was calibrated; at the same time the firm energy production was obtained, considering the production in 5% of the driest hydrological series (also called 1 in 20).

The following Table 4-1 and the respective Figure 4-1 show a summary by country for the long term annual hydro production of the identified existing and committed hydro plants listed in Table 4-2 to Table 4-11. The potential annual hydro production for all the region is 167.8 TWh and the difference in relation with the references obtained from the studies of the projects and historical generation for the existing plants is only 1%. The firm energy is around 69% of the average generation. The total capacity is 32,319 MW, which means the average plant factor is around 59%. The potential of Ethiopia is around 46% of the whole region. The details by country and by hydro plant are included in Appendix D.



Table 4-1 Annual hydro production for identified options

Country MW Hydro generation in GWh

Average Reference Variation Firm %

Egypt 2902 13897 13932 ‐0.3% 13205 95%

Ethiopia 16204 76986 77588 ‐0.8% 53923 70%

Kenya 1300 6135 6093 0.7% 3573 58%

Burundi, Eastern DRC, Rwanda * 961 4620 4674 ‐1.2% 3628 79%

Sudan 4678 26393 26281 0.4% 22298 84%

Tanzania 3544 19722 19250 2.5% 13613 69%

Uganda 2730 20025 20218 ‐1.0% 20019 100%

EAPP 32319 167778 168036 ‐0.2% 130259 78%

* Rwanda, Burundi and East DRC are merged because of the shared Ruzizi projects.

Figure 4-1 Average annual hydro production per country

Values for the Firm Energy % for Uganda, Egypt and Sudan are high because hydro energy is available year-long, given the size of their reservoirs, be it natural or artificial. (e.g. Lake Victoria in Uganda, Aswan dam in Egypt)

4.2 Total identified options by country A listing has been prepared on a country by country basis of all the existing and identified future power options. These project lists are provided in Table 4-2 to Table 4-11 below.

The following may be noted:

• Projects less than 10 MW have been omitted

8%

46%

4%3%

16%

12%

12%

Egypt

Ethiopia

Kenya

Burundi, Eastern DRC, Rwanda

Sudan

Tanzania



• Emergency rental units have been omitted

• An existing or committed plant is defined as one which will be on-power in January 2013

• Plants due for retirement prior to January 2013 have been omitted

• On-power dates for committed projects have been taken from country master plans, and based on reviews of the Inception Report by participating utilities; these dates are believed to be up to date.

• On power dates for other projects have been based on the level of preparation of the project and size, as outlined in Sections 5.3 and 6.2.

In some cases the earliest on-power date is affected by other issues, as are shown in Section 5.4 so reference should be made to Table 5-10.

Some of the projects included in the listings may be considered less certain due to the need of further assessment; however, these have been included as the objective has been to provide a maximum listing of potential, however the comments in Table 5-10 should be noted.

• Projects that are mutually exclusive have been omitted (i.e., would be in conflict with a project in the listing (such as Masindi in Uganda)

• Hydro energy values are based on country level simulations carried out for this study. Downstream benefits from storage operation are not attributed

• Capital costs have been updated and harmonized

• Future project listings are not intended to suggest an order of preference for development

• Retirements of existing or committed thermal plants have not been taken into account, as these tables are intended as a catalogue of resources. Projected retirement dates for existing thermal are shown in Table 6-17.

• Based on the service lives assumed for this study, most thermal plant to be installed near the beginning of the planning period would be retired before the end of the planning period.

The References used for filling the following tables are all listed in Table 2-2.



Table 4-2 Burundi Generation

Plant Name

Nom. Energy

Plant Factor

Level Min. Earliest

Ref Cap. Avg. Firm of lead time year

MW GWh GWh Prep. (years) on power

Hydro Existing

Rwegura 18.0 70 59 0.44 1986 51

Mugere 8.0 31 26 0.44 1982 51

Ruvyironza 1.3 5 4 0.44 1984 51

Gikonge 0.9 3 3 0.44 1982 1

Nyemanga 2.8 11 9 0.44 1988 50

S/T 31.0 120 101

Thermal existing

Bujumbura 5.5 36 36 0.75 1996 1

Total Ex. 2012 36.5 156 115

Imports/Sharing Existing

Ruzizi II 12.0 83 83 1

S/T 12.0 83 83

Total Ex. Supply 2012 48.5 239 198

Hydro Future

Kabu 16 20.0 113 100 0.64 F 5 2015 1

Kagunuzi Complex 39.0 187 177 0.55 F 6 2016 1

Mpanda 10.0 40 34 0.46 F 6 2016 1

Mule 34 16.5 54 45 0.37 PF 6 2016 1

Jiji 03 15.5 40 33 0.29 PF 6 2016 1

Siguvyaye 90.0 510 486 0.65 F/D 6 2016 1

S/T 191.0 940 836

Imports/Sharing Future

Lake Kivu gas plant 2 66.7 438 438 0.75 F

Rusumo 20.0 49 43 0.28 F 5 2015 3,4,23

Ruzizi III 48.3 222 222 0.52 F 8 2018 1

Ruzizi IV 95.7 420 420 0.50 PF 9 2019

S/T 230.7 691 685

Total Fut. Options 421.7 2069 1959

Total Fut. Supply 470.1 2308 2157

Level of Preparedness - C: Construction; F: Feasibility; PF: Prefeasibility; REC: Reconnaissance; D: Design

Note: Negative Imports in the table represent Exports.



Table 4-3 Djibouti Generation

Plant Name Nom. Cap.

MW

Energy in GWh Plant

Factor

Level of

Prep. Min. lead time (years)

Earliest year on power

RefAvg. Firm

GWh GWh

Thermal Existing

Boulaos 108 662 662 0.7 60

Marabout 15 92 92 0.7 60

S/T 123 754 754

Total Ex. Supply 123 754 754

Thermal Future

Geothermal 20 60 420 420 0.8 60

Diesel 7 28 196 196 0.8 60

Diesel 12 84 589 589 0.8 60

OCGT 15 15 105 105 0.8 60

S/T 187 1310 1310

Imports/Sharing FutureEthiopia 100 350 350 0.80 2010

Total Fut. Options 287 1310 1310

Total Fut. Supply 410 2065 2065





Table 4-4 Eastern DRC Generation

Plant Name Nom. Cap. MW

Energy in GWh Plant

Factor

Level Of

Prep.

Min. lead time (years)


Ref Avg. Firm

GWh GWh

Hydro Existing

Tshopo 1 19 142 122 0.87

Ruzizi I 30 136 100 0.52

Ruzizi II 36 247 190 0.78

S/T 85 525 412

Thermal Existing

SNEL 18 53 53 0.34

S/T 18 53 53


Ruzizi I ‐14 ‐39 ‐39

Ruzizi II ‐24 ‐167 ‐167

S/T ‐38 ‐206 ‐206


Hydro Future

Piana Mwanga ‐ rehab 29 182 122 0.72 R 6 2017

Bendera 43 143 100 0.38 R 6 2017 2,5,6

Babeda I 50 341 190 0.78 R 6 2017 2,5,6

Bengamisa 48 363 135 0.86 R 6 2017 2,5,6

Mugomba 40 163 107 0.47 R 6 2017 2,5,6

Semliki 28 118 262 0.48 R 6 2017 2,5,6,48

Ruzizi III 145 664 306 0.52 F 6 2016 2,5,6

Ruzizi IV (Sisi 5C) 287 1249 121 0.50 PF 9 2019 2,5,6

Wannie Rukula 668 R 9 2019 2,5,6

S/T 1338 3222 1342


Lake Kivu gas Plant 2 67 438 438 0.75 F 2

Ruzizi III ‐97 ‐444 ‐840 F 8 2018 2,5,6

Ruzizi IV ‐191 ‐840 ‐840 PF 9 2019 2,5,6

S/T ‐221 ‐846 ‐1242



Level of Preparedness - C: Construction; F: Feasibility; PF: Prefeasibility; REC: Reconnaissance; D: Design Note: Negative Imports in the table represent Exports.



Table 4-5 Egypt Generation

Plant Name Nom.

Cap. MW

Energy in GWh

PF Level Of

Prep.

Min. Lead time (years)


Ref Avg. Firm

GWh GWh

Hydro Existing

Aswan 1 322 1512 1434 0.54 10,14

High Aswan 2,100 9921 9425 0.54 10,14

Aswan II 270 1770 1695 0.75 10,14

Esna 86 411 384 0.55 10,14

Naga Hamadi 64 19 13 0.03 10,14

Diamata 20 88 88 0.50 2012

S/T 2862 13722 13039

Wind/Solar Existing

Wind Zafarana total 305 830 830 0.30 2008 14

Solar 100 613 613 0.70 2009 14

S/T 405 1443 1443

Thermal Existing

Total thermal 2009 19,062 133586 133586 0.80 2009

Sidir Khir CCGT 750 5256 5256 0.80 2010

Nobaria 3 CCGT 750 5256 5256 0.80 2010 9,10,14

Kurimat 3 CCGT 750 5256 5256 0.80 2010 9,10,14

Tebbin STPP 700 4906 4906 0.80 2010 9,10

Atf CCGT 750 5256 5256 0.80 2010

Cairo West STPP 700 4906 4906 0.80 2011

Nowebaa CCGT 750 5256 5256 0.80 2012

Abu Kir STPP 1,300 9110 9110 0.80 2012

Banha CCGT 750 5256 5256 0.80 2012

S/T 26262 184044 184044


Lybia ‐150 ‐800 ‐800 10,14

Jordan ‐500 ‐800 ‐800 10,14

S/T ‐650 ‐1600 ‐1600

Net Ex. Supply 28879 197609 196926

Hydro Future

Assiut 40 175 166 0.50 D 2015 14

S/T 40 175 166

Wind/Solar Future

Wind Zafarana total 7,530 19,789 19,789 0.30 2008 14,59

S/T 7530 19789 19789

Thermal Future

Ain Sokhna STPP 1,300 9110 9110 0.80 2014 59

Qassasen CCGT 1,250 8760 8760 0.80 2014 59

Qassasen CCGT 250 1752 1752 0.80 2015 59

Giza North CCGT 1,000 6132 6132 0.70 2013 59

Giza North CCGT 500 3066 3066 0.70 2014 59

Suez STPP 650 4555 4555 0.80 2014 59

Helwan south STPP 1,300 9110 9110 0.80 2015 59

Helwan south STPP 1,300 9110 9110 0.80 2017 59

Qena STPP 650 4555 4555 0.80 2015 59

Qena STPP 650 4555 4555 0.80 2016 59

Damietta West 1 CCGT 1,500 10512 10512 0.80 2017 59

Damietta West 2 CCGT 1,500 10512 10512 0.80 2019 59



Plant Name Nom.

Cap. MW

Energy in GWh

PF Level Of

Prep.

Min. Lead time (years)


Ref Avg. Firm

GWh GWh

Safaga STPP 1,300 9110 9110 0.80 2018 59

Steam 650 MW 16,250 113880 113880 0.80 2019‐2027 59

Combined cycle 8,250 57816 57816 0.80 2019‐2027 59

Dabaa nuclear 5,000 39420 39420 0.90 2018‐2027 59

S/T 42650 301957 301957


Total Fut. Supply 79099 519531 518838





Table 4-6 Ethiopia Generation

Plant Name

Nom

Cap.

MW

Energy in GWhPlant

Factor

Level of

Prep.



Ref Avg. Firm

GWh GWh

Hydro Existing

Tis Abbay 1 11 35 24 0.35 1964 10,15,38

Tis Abbay 2 73 417 237 0.65 2001 10,15,38

Finchaa 134 760 548 0.65 1973 ‐ 2003 10,15,38

Gilgel Gibe 1 192 878 587 0.52 2004 10,15,38

Malka Wajana 153 437 254 0.33 1988 10,15,38

Awash 1 43 100 64 0.27 1960 10,15,38

Awash 2 32 138 89 0.49 1966 10,15,38

Awash 3 32 152 98 0.54 1971 10,15,38

Gibe II 420 1914 1279 0.52 2009 10,47

Beles 460 2134 1684 0.53 2010 10,15,21,47

Tekeze I 300 1390 785 0.53 2009 10,47,49

S/T 1851 8356 5650

Wind Existing

Ashegoda wind 120 526 526 0.50 2,7

Adana 51 223 223 0.50

S/T 171 749 749

Thermal Existing

Dire Dawa Diesel 44 289 289 0.75 15

Awash 7 Diesel 35 230 230 0.75 15

Kaliti Diesel 14 92 92 0.75 15

Aluto Geothermal 7 48 48 0.75 10

Small diesel 57 250 250 0.50 15

S/T 157 909 909


Sudan 120 1900 1900 2010 20

S/T 120 1900 1900


Hydro Future

Gibe III 1,870 6087 3881 0.37 C 2013 10,21,26,47

Gibe IV 1,468 5644 3611 0.44 C 5 2015 41,10,47

Halele Worabesa 422 2215 1204 0.60 F 8 2014 10,47

Chemoga‐Yeda 280 1384 840 0.56 D 6 2016 10,26,47

Geba I & II 372 1802 1329 0.55 F 8 2018 10,47

Genale 3D 258 1228 855 0.54 D 6 2015 10,26

Baro 1 and 2 + Genji 900 4522 3546 0.57 D 6,7 2016, 2017 10,42,47

Mandaya 2,000 11950 8834 0.68 PF 9 2019 10,25

Border 1,200 6331 5789 0.60 PF 9 2019 10,25,47

Gibe V 662 1882 1202 0.32 PF 9 2019 43, 47

Beko Abo 2,100 10825 7300 0.59 R 9 2019 8

Karadobi 1,600 8784 6081 0.63 F 8 2018 10

Genale 6D 246 1609 1114 0.75 D 6 2016 10,26

Gojeb 150 526 373 0.40 D 6 2016 10



Plant Name Nom.

Cap. MW

Energy in GWhPlant

Factor

Level of

Prep.



Ref Avg. Firm

GWh GWh

Tekeze II 450 1758 990 0.45 PF 9 2019 47

Aleltu East 186 885 619 0.54 F 8 2018 10

Aleltu West 265 1028 598 0.44 PF 9 2019 10

Awash 4 38 166 106 0.50 F 6 2016 10

S/T 14467 68627 48272

Thermal Future

Aluto Langano geothermal 75 493 493 0.75 PF 6 2016 46

Tendaho geothermal 100 657 657 0.75 PF 8 2018 46

Corbetti geothermal 75 493 493 0.75 PF 8 2018 46

Abaya geothermal 100 657 657 0.75 PF 8 2018 46

Tulu Moye geothermal 40 263 263 0.75 PF 8 2018 46

Dofan Fantale geothermal 60 394 394 0.75 PF 8 2018 46

S/T 450 2957 2957


Djibouti ‐100 ‐350 ‐350 0.80 2010

Sudan ‐1200 ‐7,000 ‐7,000 2010 21

Kenya ‐2,000 ‐14,000 ‐14,000 2013

S/T ‐3300 ‐21,350 ‐21350







Table 4-7 Kenya Generation

Plant Name Nom.

Cap. MW

Energy in GWhPlant Factor

Level of Prep.



Ref Avg. FirmGWh GWh

Hydro ExistingMisc plants 10 27Tana 20 37 23 0.21 1932‐55 27,2,7,52Wanji 7 37 26 0.61 1952 27,2,7,52Kambaru 94 460 240 0.56 1974 27,2,7Gitaru 225 892 461 0.45 1978 27,2,7Kindaruma 40 168 87 0.48 1968 27,2,7Masinga 40 191 92 0.55 1981 27,2,7Kiambere 164 916 486 0.63 1988 27,2,7,52Sondu Miriu 60 404 330 0.77 2008 27,2,7,52Turkwell 106 437 281 0.47 1991 27,2,7,52Sangoro 21 143 117 0.78 C 2011 20Kindaruma U3 25 105 54 0.48 C 2012 20Tana ‐ Extension 10 26 16 0.30 C 2010 27

S/T 823 3816 2214 Wind Existing

Ngong 20 88 88 0.50 2012

S/T 20 88 88 Thermal Existing

Olkaria 1 45 355 355 0.90 1981 27Olkaria 2 105 828 828 0.90 2003 27OrPower 4a 13 102 102 0.90 2000 27OrPower 4b 35 276 276 0.90 2008 20Olkaria 3 geothermal 35 230 230 0.75 2010 27

Kipevu 1 Diesel 75 526 526 0.80 1999 27Kipevu new GT 60 394 394 0.75 1987/1999 27Nairobi Fiat 13 91 91 0.80 1999 2,20,27Diesel 120 788 788 0.75 2010 20Iberafrica IPP 56 368 368 0.75 2000 27Athi river diesel IPP (Thika) 240 1577 1577 0.75 2012 20

Rabai diesel IPP 89 585 585 0.75 2009 20Iberafrica 3 IPP 53 348 348 0.75 2009 20Tsavo IPP 74 519 519 0.80 2001 27Cogen 26 0 0 0.00 2001 20Aggreko IPP 60 394 394 0.75 27

S/T 1100 7380 7380 Total Ex. Supply 1916 11283 9681




Energy in GWhPlant Factor

Level of Prep.




Hydro FutureMutonga 60 336 198 0.64 F 6 2016 27Low Grand Falls 140 707 415 0.58 F 7 2017 27Magwagwa 120 525 345 0.50 F 7 2017 2Total Ewaso Ngiro 180 568 306 0.36 F 7 2017

Karura 56 184 95 0.37 PF 6 2016

S/T 556 2319 1359 Wind Future

Turkana wind 300 1314 1314 0.50 2013 20Aeolus Wind 160 700 700 0.50 2013 Osiwo wind 50 219 219 0.50 2013 20Karura 56 182 182 0.37

S/T 406 1715 1715 Thermal Future

Geothermal Fut. Res. 2800 18396 18396 0.75 27 Olkaria 4 & 5 geothermal 140 920 920 0.75 2014 27

Mombasa Coal 1200 8410 8410 0.80 Cogen 126 828 828 0.75

S/T 4266 28553 28553 Imports/Sharing Future

Ethiopia Phase 1 1000 7008 7008 0.80 2013 27

Ethiopia Phase 2 1000 7008 7008 0.80 2013 27

Tanzania ‐200 ‐1403 ‐1403 0.80 2015 27

S/T 1600 9810 98210

Total Fut. Options

7188 43097 41777

Total Fut. Supply

8805 54380 51818





Table 4-8 Rwanda Generation


Energy in GWh Plant

Factor Level of Prep.




Hydro ExistingMukungwa 12.5 57 57 0.52 1982 1,51 Ntaruka 11.3 51 51 0.52 1959 1,51 Gihiria 1.8 8 8 0.52 1985 1,51 Gisenyi 1.2 5 5 0.52 1969 1,51 Small/mini hydros 10.0 46 46 0.52 2 2012 18

S/T 37 168 168 Thermal Existing

Gatsata 4.7 31 31 0.75 1975 51 Jabana 7.8 51 51 0.75 51 Mukungua 4.5 30 30 0.75 2006 51 New Diesel 20.0 131 131 0.75 2009 17 RIG Kivu gas pilot 4.5 30 30 0.75 2009 17

S/T 42 273 273

Imports/Sharing Existing Ruzizi I 14.0 124 124 1 Ruzizi II 12 83 83 1 Uganda 1 3 3

S/T 27 210 210

Total Ex. Supply 105 650 650 Hydro Future

Nyabarongo 27.8 150 129 0.62 D 4 2014 1,51 Rukarara I 9.5 42 42 0.50 F 4 2014 18

S/T 37 192 170 Thermal Future

Biomass/peat 50.0 329 329 0.75 F 2013 18 Kivu gas Plant 1 100.0 657 657 0.75 F 2013 29

S/T 150 986 986 Imports/Sharing Future

Kivu gas Plant 2 (shared) 66.7 438 438 0.75 F 2015

Rusumo 20.0 49 43 2015 3,4,23Ruzizi III 48.3 222 222 0.52 F 8 2018 2,5,6 Ruzizi IV 89.0 373 373 0.48 PF 9 2019 2,5,6

S/T 223.7 1082 1076



Level of Preparedness - C: Construction; F: Feasibility; PF: Prefeasibility; REC: Reconnaissance; D: Design Note: Negative Imports in the table represent Exports.



Table 4-9 Sudan Generation


Energy in GWh

Plant Factor

Level Of

Prep.


Earliest Year on power

Ref Avg. Firm

GWh GWh

Hydro Existing

Rosieres 280 1948 1716 0.79 1971 10,19

Sennar 15 52 46 0.40 1962 10,19

Kashm El Girba 18 80 80 0.51 1965 10,19

Jebel Aulia 30 131 119 0.50 2003 10,19

Merowe 1250 5701 4771 0.52 2009

Sennar extension 50 174 153 0.40 C 2011 22

Rosieres/Dinder 135 939 827 0.79 C 2012 19,22

S/T 1778 9026 7711

Thermal Existing

Dr. Sharif 1 STPP 60 420 420 0.80 1985 10,19

Dr. Sharif 2 STPP 120 788 788 0.75 1994 10,19

Khartoum North OCGT 50 329 329 0.75 1992 22

Khartoum North STPP 160 1051 1051 0.75 22

Khartoum North STPP 200 1314 1314 0.75 2008 22

Garri 1 CCGT 220 1445 1445 0.75 2003 10,19

Garri 2 CCGT 240 1577 1577 0.75 2008 22

Garri 4 STPP 100 657 657 0.75 2007 22

Kilo MSD 40 263 263 0.75 2007 22

Atbara MSD 13 88 88 0.75 2003 19

Kassala 1‐5 STPP 50 329 329 0.75 2007 30

Kosti 1&2 STPP 250 1643 1643 0.75 2010 30

Al Fula 1&2 STPP 270 1774 1774 0.75 2010 30

Kosti 3&4 STPP 250 1643 1643 0.75 2010 22

Al Fula 3&4 STPP 270 1774 1774 0.75 2010 22

S/T 2293 15094 15094


Ethiopia ‐120 ‐1900 ‐1900 2010 20

S/T ‐120 ‐1900 ‐1900




Energy in GWh

Plant Factor

Level Of

Prep.


Earliest Year on power

Ref Avg. Firm

GWh GWh

Total Ex. Supply 3951 22220 20905

Hydro Future

Rumela 30 83 79 0.31 C 2013 9,10,30

Sabaloka 90 670 546 0.85 PF 2017 9

Shereiq 315 1962 1695 0.71 F 6 2016 9,10,30

Kagbar 300 1413 1186 0.54 F 8 2018 9,10,30

Dal 1 (Low) 340 1968 1698 0.66 PF 8 2018 9,10,30

Dagash 285 1503 1294 0.60 PF 9 2019 9,10,30

Fula 1 720 4134 3382 0.66 PF 9 2020 9,10,30

Shukoli 210 1443 1209 0.78 PF 9 2020 9,10,30

Lakki 210 1443 1209 0.78 PF 9 2020 9,10,30

Bedden 400 2748 2287 0.78 PF 9 2020 9,10,30

S/T 2900 17367 14587

Thermal Future

Port Sudan 1‐3 STPP 405 2838 2838 0.80 2013 22.3

Garri 3 1‐3 STPP 405 2838 2838 0.80 2013 22,30

Garri 3 U4 STPP 135 946 946 0.80 2013 22,30

El Bagair 1&2 STPP 270 1892 1892 0.80 2013 22,30

El Bagair 3&4 STPP 270 1892 1892 0.80 2013 22,30

Crude fired 2 x 238 476 3336 3336 0.80 6 2016 30

Crude fired 3 x 475 1425 9986 9986 0.80 6 2016 30

CCGT 3 x 208 624 4373 4373 0.80 3 2013 30

CCGT 4 x 342 1368 9587 9587 0.80 3 2013 30

CCGT 4 x 458 1832 12839 12839 0.80 3 2013 30

S/T 7210 50528 50528


Ethiopia 1200 7000 7000 20

S/T 1200 7000 7000







Table 4-10 Tanzania Generation


Energy in GWh

Plant Factor

Level of

Prep.



RefAvg. Firm

GWh GWh

Hydro Existing

Mtera 80 335 218 0.48 1988 3

Kidatu 204 909 646 0.51 1975 3

Hale 21 81 54 0.44 1967 3

Kihansi 180 663 491 0.42 2000 3

Pangani Falls 68 289 192 0.49 1995 3

Nyumba ya Mungu 8 34 21 0.48 1968 3

S/T 561 2311 1622

Thermal Existing

Songas 1 42 276 276 0.75 3

Songas 2 120 788 788 0.75 3

Songas 3 40 263 263 0.75 3

Ubongo GT 100 657 657 0.75 3

Tegeta IPTL 100 657 657 0.75 3

Tegeta GT 45 296 296 0.75 2009 3

Mwanza 60 420 420 0.80 2010 3

Ubongo EPP 100 657 657 0.75 2011 3

Cogen 37 243 243 0.75 2011 3

S/T 644 4257 4257

Total Ex. in 2012 1205 6569 5879

Hydro Future

Ruhudji 358 1928 1377 0.61 F/D 6 2016 3

Rusumo 63 444 419 0.80 F 6 2016 3

Kakono 53 404 416 0.87 PF 6 2016 3

Songwe Bigupu 34 153 107 0.51 PF 6 2016 3

Songwe Sofre 157 780 512 0.57 PF 9 2019 3

Songwe Manolo 149 736 494 0.56 PF 8 2020 3

Masigira 118 664 519 0.64 PF 8 2018 3

Mpanga 144 955 698 0.76 PF 8 2018 3

Taveta 145 850 657 0.67 PF 8 2020 3

Rumakali 222 1475 988 0.76 F 8 2018 3

Ikondo 340 1832 1393 0.62 PF 9 2019 3

Stieglers Gorge 1200 6674 4410 0.63 PF 9 2019 3

S/T 2941 16895 11991

Thermal Future




Energy in GWh

Plant Factor

Level of

Prep.



RefAvg. Firm

GWh GWh

Kiwira 200 1402 1402 0.80 2013 3

GWh GWh

Kinyerezi 240 1577 1577 0.75 2013 3

Mnazi Bay 300 1971 1971 0.75 2017 3

Ngaka 400 2803 2803 0.80 2024 3

Mchuchuma 400 2803 2803 0.80 2025 3

S/T 1540 10556 10556


From Ethiopia (through Kenya) 200 1489 1489 0.85 2014 3

From Zambia 200 1489 1489 0.85 2015 3







Table 4-11 Uganda Generation


Energy in GWh

Plant Factor

Level of Prep.



RefAvg. Firm

GWh GWh

Hydro Existing

Misc plants 15 0.00 37

Nalubaale 180 767 766 0.49 37

Kira 11‐15 200 747 747 0.43 37

Bujagali 1‐5 250 1970 1966 0.90 C 2011 37

Small hydros(commited) 50 0.00 C 2011 37

S/T 695 3485 3480

Thermal Existing

Kakira 17 112 112 0.75 2,7

Namanve 50 329 329 0.75

Invespro HFO IPP 50 329 329 0.75 2010

Electromax IPP 10 66 66 0.75 2009

S/T 127 834 834


Hydro Future

Karuma high 700 5512 5512 0.90 F 8 2018 37

Murchison Falls high 750 5904 5903 0.90 PF 9 2019 37

Isimba 100 788 788 0.90 PF 6 2016 37

Ayago 550 4336 4336 0.90 PF 9 2019 37

Small hydro candidates 37 PF 6 2016 37

S/T 2137 16540 16540

Thermal Future

Kampala steam 56 392 392 0.8 6 2016 37

Tallow steam 53 371 371 0.8 6 2016 37

Tallow GT 57 399 399 0.8 6 2016 37

Tallow CCGT 185 1296 1296 0.8 6 2016 37

Tallow diesel 10 70 70 0.8 6 2016 37

Geothermal 33 231 231 0.8 6 2016 37

S/T 394 2761 2761







4.3 Summary of present and future generation resources Based on the project listings in the previous section, the total resources in each country for 2013 and 2030 may be summarized as shown below. The resources are limited to resources as presented in the master plans for each country. Demands are taken from the Module 1A-1100 report.

This table provides a clear indication that Ethiopia, and possibly the DRC will be significant net exporters. The Uganda resource total includes a number of hydro projects on the Nile. The DRC is a special case. As was noted in Section 1, this study is only considering resources in the Eastern part of the country. However the DRC total undeveloped resources may be in the order of 60,000 MW. Unfortunately this potential has not been assessed to a level where it may be incorporated into the planning process.

Table 4-12 Present and future potential generation resources

COUNTRY

Existing FUTURE TOTAL DEMAND SURPLUS

2012 2013‐2030 2030 2030 2030

MW MW MW MW MW

Burundi 49 422 470 385 86

Djibouti 123 187 310 198 112

East DRC 74 1,117 1,191 179 1,012

Egypt 25,879 46,570 72,449 69,909 2,540

Ethiopia 2,179 13,617 15,796 8,464 7,332

Kenya 2,051 6,288 8,339 7,795 544

Rwanda 103 411 514 484 30

Sudan 3,951 11,310 15,261 11,054 4,207

Tanzania 1,205 4,881 6,086 3,770 2,316

Uganda 822 2,531 3,353 1,898 1,455

TOTAL 36,436 87,334 123,769 104,136 19,633



5 FUTURE HYDROELECTRIC OPTIONS 5.1 Identifications of new hydroelectric options Potential hydroelectric projects in each country have been identified in country generation expansion plans, as a result of previous studies at the reconnaissance, prefeasibility and feasibility levels. These projects are all listed in the previous section in the country project listings. However relatively recent master plans were only available for certain countries, and for the other countries the candidate lists were made up from other sources, as listed in Section 2.

In general it has been assumed that projects listed in master plans have been judged as potentially acceptable in terms of costs and social and environmental potential impacts. However it has to be recognized that some projects will require further assessment before they can be included in short or mid-term plans. To take this into account the screening process described in Section 5.4 has proposed that projects needing further assessment should be considered for implementation after 2018. Similarly a number of the identified projects are at a very preliminary stage of preparation, and would consequently need long lead times for implementation. This fact has also been taken into account, in prioritizing future developments.

Hydropower planning consists of the steps required to identify and evaluate potential hydroelectric sites, and then to arrange implementation of a selected hydroelectric project. This can include upgrades of existing projects, as well as new plants. The hydropower planning and implementation process therefore comprises the following steps:

• Identification and inventory of potential sites

• Reconnaissance investigation of selected sites

• Prefeasibility study of preferred sites

• Feasibility studies of best sites

• Design and tender documents

• Construction

Usually identification and inventory activities will go ahead quite separately from the power system studies that are used to define future new generation needs. By comparison, all later stages of hydroelectric project planning are closely related to the overall power system planning process.

The project evaluation studies leading up to the project commitment at each stage includes the full range of activities needed to define the project scheme, to estimate generation benefits, and to evaluate the project. The difference between each phase is the level of effort applied to each phase, in terms of engineering and extent of field investigations and, to a large degree, the accuracy of the estimated project costs is directly related to the extent of the field investigations.

While much may be made of the need for optimization studies to define the project size (e.g. dam height and installed capacity), the economics of a reasonably, if sub-optimal, scheme will only differ marginally from the estimated economic viability of the ideal project. It is instructive to compare the level of generally accepted levels of expenditures, and resulting contingency allowances with the amount of field investigations in the various study phases. This indicates the importance of assessing the actual level of preparation of a project, and the level of confidence in the results.



Table 5-1 Typical cost values for projects

Cost Element REC PF F Total

Contingency allowances %* 25 10‐15 8‐10 ‐‐

Accuracy % 35 15 8 ‐‐

Filed investigation costs as % of cost of each study phase ** 14 42 47 ‐‐

Field investigation cost as % of total study costs estimates ** 3 12 24 39

Study cost as % of total capital 0.4 0.6 1.1 2.1

Level of Prep ‐ C: Construction; F: Feasibility; PF: Prefeasibility; REC: Reconnaissance; D: Design

*Indicated contingency allowances are percentages of total costs for construction, engineering and construction supervision.

**Based on approximate cost of field investigations

The list of identified future hydro options is provided in Table 5-2 below. (The level of preparedness is taken from the reference reports.)



Table 5-2 List of identified new hydro options

Country Name

Installed Average Firm Level

Country Name

Installed Average Firm Level

Capacity Energy Energy of Capacity Energy Energy of

(MW) (GWh) (GWh) Prep. (MW) (GWh) (GWh) Prep.

Burundi

Jiji 03 15.5 40 33 PF

Kenya

Mutonga 60 336 198 F

Kabu 16 20 113 100 F Low Grand Falls

140 707 415 F

Kaganuzi A 34 98.00 PF Magwagwa 120 525 345 F

Kaganuzi Complex

39 187 177 F Total Ewaso Ngiro

180 568 306 F

Mpanda 10 40 34 F

Karura 56 184 95 PF

Mule 34 16.5 54 45 PF

Siguvyaye 90 510.00 486 F/D Rwanda Nyabarongo 27.8 150 129 D

East DRC

Piana Mwanga 29 182 122 REC

Sudan

Sabaloka 90 670 546 PF

Bendera 43 143 100 REC Shereiq 315 1962 1695 F

Babeda I 50 341 190 REC Kagbar 300 1413 1186 F

Bengamisa 48 363 135 REC Dal 1 (Low) 340 1968 1698 PF

Mugomba 40 163 107 REC Dagash 285 1503 1294 PF

Semliki 28 118 262 REC Fula 1 720 4134 3382 PF

Ruzizi III 145 664 306 F Shukoli 210 1443 1209 PF

Ruzizi IV (Sisi 5C)

287 1249 121 PF Lakki

210 1443 1209 PF

Wannie Rukula 668 REC Bedden 400 2748 2287 PF

Egypt Assiut 40 175 166 D

Tanzania

Ruhudji 358 1928 1377 F/D

Ethiopia

Gibe III 1,870 6087 3881 C Rusumo 63 444 419 F

Gibe IV 1,468 5644 3611 C Kakono 53 404 416 PF

Halele Worabesa

422 2215 1204 F Songwe Bigupu 34 153 107 PF

Chemoga‐Yeda 280 1384 840 D Songwe Sofre 157 780 512 PF

Geba I & II 372 1802 1329 F Songwe Manolo 149 736 494 PF

Genale 3D 258 1228 855 D Masigira 118 664 519 PF

Baro 1 and 2 + Genji

900 4522 3546 D Mpanga 144 955 698 PF

Mandaya 2,000 11950 8834 PF Taveta 145 850 657 PF

Border 1,200 6331 5789 PF Rumakali 222 1475 988 F

Gibe V 662 1882 1202 PF Ikondo 340 1832 1393 PF

Beko Abo 2,100 10825 7300 R Stieglers Gorge 1200 6674 4410 PF

Karadobi 1,600 8784 6081 F

Uganda

Karuma high 700 5512 5512 F

Genale 6D 246 1609 1114 D Murchison Falls high

750 5904 5903 PF

Gojeb 150 526 373 D Isimba 100 788 788 PF

Tekeze II 450 1758 990 PF Ayago 550 4336 4336 PF

Aleltu East 186 885 619 F

Aleltu West 265 1028 598 PF

Awash 4 38 166 106 F



5.2 Capital costs for future hydro projects Capital costs for hydro projects were taken from the most recent master plan or project study report. It was always assumed that the most recent report provides the best information, even if there are significant differences with previous reports. Costs were updated as is described in Section 5.2.1. These estimates were checked to determine if they included IDC and environmental mitigation costs. Where mitigation costs were not included in the basic project construction cost estimate, an allowance was added, as outlined in Section 5.2.2. Allowances for interest during construction were added, where not included in the basic previous estimate, as outlined in Section 5.2.3.

It may be noted that relatively detailed cost estimates were only available for some projects. Particularly cost estimates were available for most of the Ethiopian hydro projects and for the Dal scheme in Sudan. Summary estimates for the projects in Kenya, Tanzania and Uganda studied for the EAPMP were available. Studies for the projects in Burundi and Rwanda were generally available. For the SSEA study some of the project costs were re-estimated, including:

• Kabu 16 and Mpanda in Burundi

• Nyabarongo in Rwanda

• Igamba 2 in Tanzania

Cost breakdowns for these projects were available.

For the Eastern DRC projects the only data available was that provided in the compendium by Male Cifarha [6]. The cost estimates for the projects for the Ethiopia MoWR and ENPTPS are mostly recent and are relatively consistent. The estimates for the EAPMP were reviewed as part of the 2006 SSEA study and all those estimates are considered to be reasonable and consistent. No assessment could be made of the estimates for the DRC and Burundi, Rwanda projects, other than those referred to above. In any case these estimates are old, and more modern design concepts could change the costs significantly.

5.2.1 Procedure for updating costs Information on the projects being assessed is provided in the various study reports done previously. These various studies are at different levels of engineering development, and were done at different times in the past. Also in some case the documentation on these projects is not complete.

Built into these estimates are possibilities for different criteria or approaches to have been used, such as application of contingencies, environmental mitigation, and overheads such as owner’s costs. It is assumed that in accordance with normal practice for “economic” assessment of projects with the expectation of public sector implementation, taxes and duties have not been included.

For the purpose of making the comparisons in this assessment, it was necessary to compare projects with all capital costs adjusted to a common reference year, 2009. Ideally all project costs would be re-estimated using standard criteria, however this was not practical because of the incomplete reference material, and because some 80 projects were in the initial list of new hydro options. Consequently costs were adjusted using the escalation indices provided in Section 3.2.4.



Burundi Costs for all projects were obtained from the SSEA study, and were referenced to 2004 prices. These were generally reviewed for the SSEA study, and some were re-estimated as noted above. All costs were escalated from 2004 to 2009

Eastern DRC Projects The most important DRC new hydro options are the proposed Ruzizi III and Ruzizi IV (Sisi 5) projects. Both of these have very current studies, and these cost estimates were used without modification. For the DRC projects, costs as of 1990 were provided for most of these sites in the Cifarha 1994 report [6]. The ONRD12 estimates include a 20% provision for contingencies, and 15% for owner’s costs. Estimates are provided for various transmission alternatives; however these are not directly included in the capital cost estimates. The Sicai-Tractionel study13 included 10% for contingencies, and a further 30% is added for “complementary” costs. No reference is given to transmission costs. The SEEE/Inter G14 estimates include transmission, but do not refer to overheads or contingencies.

It was assumed that none of the DRC estimates included interest during construction, or an allowance for environmental or mitigation costs. With regard to mitigation costs, no specific major potential environmental risks were stated or indicated in the supporting reports. The capital costs shown in the original DRC source reports were escalated to 2004 for the SSEA study, and now have been further escalated to 2009. It should be noted that all the reference studies, except for Ruzizi III and Ruzizi IV are very preliminary and old. Additionally application of escalation to adjust costs for a long period can only give a general approximation of equivalent current costs.

Egypt The only new hydro project scheduled for after 2013 in Egypt is the 40 MW Assiut barrage. No cost data was obtained for this project, so a proxy value of 3000 $/kW was assumed. It is noted that this project is primarily for level control on the Nile, and thus will not be part of a prioritized or optimized generation scheduling process.

Ethiopia Almost all of the projects are listed in the 2006 master plan, and were then referred to in the EEPCo 2008 planning report [47]. Project costs provided in the 2008 report were taken to be at 2007 price levels and were escalated to 2009. In view of the number of potential hydro developments in Ethiopia, their importance in any future regional power market, and the number of available reports, a comparison was made of the alternative estimates shown in Table 5-3 below. These costs exclude interest during construction. It should be noted that the 2008 report showed generation and transmission costs separately. It is therefore assumed that with the exception of plant connections to the grid, transmission costs are not included in these costs.

12 Étude du système électroénergétique de la Province du Kivu, Energoprojekt y ONRD, 1972 13 Reconnaissance des ressources hydro-électriques dans le nord-est, Vol. 2 – esquisses d’aménagements, SICAI- Tractionel,

Juin 1972 14 Études inventaires des sites hydrauliques en vue de leur équipement avec des mini ou microcentrales hydro-électriques au

Zaïre, S.E.E.E – O.C.C.R.-INTER G



Table 5-3 Ethiopia previous estimated costs for hydro options (Costs in MUSD)

Project

Installed 2008 ENTRO

MoWR

MoWR Other

Ref/year Report Capacity Highlight EDF Report Reference

(MW) Report 2007 date costs

Border 1200 1626 1481

Mandaya 2000 2640 2472

Beko Abo 2100 2838 2007

Karadobi 1600 2040 2232 2006

Gibe III 1870 1704 2205

Gibe IV 1468 2214 2100 2214 EEPCo Gibe IV project profile ‐ 2009

Gibe V 662 879

Halele Worabesa

422 507 217 stage

1

Feasibility study Halele Worabesa

Stage 1‐ Lahmeyer 2000

Chemoga‐Yeda 280 403 465 391 Feasibiility study Chemoga Yeda ‐ Lahmeyer 2006

Aleltu East 186 438 438 379 Aleltu basin study ‐ Acres 1994

Aleltu West 265 561 561

Baro 1 and 2 + Genji

900 976 976 2006

Gojeb 153 288 268

Geba I & II 372 535 379

excl TL 286 2005

Genale 3D 258 304 272

excl TL 308

excl TL 2007

Genale 6D 246 383 363 exc TL

470 2009

Tekeze II 450 435

Awash 4 38 49 49

Capital costs in the current study are shown in bold



Kenya The Low Grand Falls and Mutonga projects were included in the latest Kenya master plan of 200815. Costs are assumed at 2008 price levels which are the same as 2009 prices, so no adjustment was made. The Magwagwa and Ewaso Ngiro projects were included in the EAPMP, and so were escalated from 2004 to 2009.

Rwanda The Nyabarongo site was originally studied in 1999 by Sogreah. For the SSEA study costs were escalated to 2004. For the current study theses costs were further escalated to 2009.

Sudan The cost data for the Sudan projects was available from the following sources:

• Costs for the Sabaloka, Fula 1, Shukoli, Lakki, Bedden and Rumela were updated to 2006 prices from the NEC LTPPS 2003 data book by the ENPTPS. These costs were then further escalated to 2009 for this study.

• Costs for the Shereiq, Dagash and Kagbar projects were taken from the NEC Generation Plan of 2006 were used for the ENPTPS, with some adjustments. These have been escalated from 2006 to 2009 for this study.

• The cost for the low Dal scheme was taken from the prefeasibility study of the Dal project undertaken as part of the ENPTPS. That cost has been updated to 2009 for this study.

These costs are compared below, and exclude interest during construction and allowances for mitigation costs.

Table 5-4 Sudan previous estimated costs for hydro projects (Costs in MUSD)

Project MW ENTRO EdF 2007 NEC Hydrology data book 2007 NEC Generation plan report 2007

Sabaloka 90 596 523

Shereiq 315 1190 826 876

Dagash 285 1048 719 800

Kagbar 300 1125 379 Stage 1 861

Dal 1 (low) 340 1113 846 955

Fula 1 720 1319 1157

Shukoli 210 420 368

Lakki 210 429 376

Bedden 400 880 772

Rumela 30 193 169

15 Kenya least cost power development plan, 2009-2030, December 2008



Tanzania All the hydroelectric options presented in this study were taken from the 2009 Tanzania PSMP [3]. As these costs are at 2008/9 price levels no further adjustment was made.

Uganda The cost estimates for the candidate Uganda projects were originally developed in the 1997 Uganda hydro study16. The project costs were re-estimated as part of the EAPMP [7]. At that time a number of sites were being considered, some of which were mutually exclusive (i.e., Masindi and the main stream Nile projects – Karuma, Ayago and Murchison Falls). Also since then, studies have now considered larger projects for Karuma, Ayago and Murchison Falls. The Isimba site has been considered for development as well.

The Uganda 2009 master plan [37] includes a number of small hydro projects, however only four larger projects are considered, (e.g., more than 30 MW), i.e.

• Murchison Falls 750 MW

• Ayago 550 MW

• Karuma 700 MW

• Isimba 100 MW

The plan refers to the Bugumira 110 MW project however notes that it would not be built if Isimba goes ahead, so it is not considered in this study. The total project costs given in the generation plan are at 2008/9 price levels so have not been adjusted further.

5.2.2 Mitigation costs Mitigation or environmental costs will typically cover land purchase, resettlement costs, relocation/replacement of roads, bridges and buildings in the reservoir area and in the immediate project area. The extent of the mitigation requirements will vary with the type and size of hydro project as well as local land use and population concentrations. Where project cost estimates were available, these were reviewed to determine if mitigation costs had been included, as a specific cost element. The approach to correcting for mitigation costs was to either include the mitigation cost amount from the previous estimate, or where no such allowance was made, to add a contingency amount.

The 2004 EAPMP study that covered Tanzania, Uganda and Kenya included an allowance for mitigation costs for all projects, based on the estimates and scope provided in the original reference reports. These costs were then escalated to 2004 for the EAPMP analyses. These escalated 2004 costs have been retained, when not superseded by more recent studies.

For Uganda some costs have been updated for the 2009 Master Plan, and these costs are understood to exclude mitigation costs. An adjustment has been applied accordingly. For those Uganda projects not included in the master Plan, the EAPMP costs which included a mitigation allowance were used. For Tanzania the recent new master plan was based on costs escalated from the EAPMP, and thus included allowances for mitigation costs. For Kenya project costs both from the EAPMP or the 2008 Master Plan included mitigation costs. For Ethiopia, it is understood that all project costs include mitigation costs the project cost estimates used in the Sudan 2008 Master Plan are understood to exclude mitigation costs, so an allowance was added.

For the projects in Burundi, East DRC and Rwanda, project costs were escalated from those shown in the 2006 SSEA study. Some of the original reference project reports showed some

16 Kennedy and Donkin – Uganda Electricity Board Hydropower Development Master Plan .- 1997



allowance for mitigation measures, while others have stated that any such costs would be covered by the civil works contingency amount. In the latter cases the civil works contingency amount was usually about 25%, which is relatively high. Normally civil works contingencies will be in the order of 15%, although higher amounts would be included if there are major underground works. A contingency of 25% on civil works typically would correspond to about 15-18% of the overall project cost. By comparison, aside from special situations, mitigation costs could range from 1- 2% for a run of the river project to 5-8% of total project cost for a project with a significant upstream reservoir area.

For the purpose of the earlier SSEA study and this EAPP study it was assumed that the civil works contingency will cover routine mitigation costs for run of the river and projects with pondage. For reservoir projects a further 5% has been added. This applies to the following SSEA sites:

• Burundi: Mpanda, Kaganuzi, Kakono, Mule, Siguvyaye.

• All DRC projects.

• Rwanda: Nyabarongo.

The 5% amount was calculated on the total project cost, exclusive of IDC, and has been added to the total cost with IDC for the calculation of unit generation costs. The mitigation amounts, where added to the project cost, as shown later in Table 5-12.

5.2.3 Interest during construction For the preliminary ranking of new power options, capitalized costs (i.e., including interest during construction assuming a 10 % interest rate) were used.

In many case the previous project estimates are presented as project costs without financing costs during construction. For these projects, and to provide a measure of standardization, standard IDC factors were used. These were a function of project size and thus construction period, and assumed the disbursement schedules shown in Table 5-6 below. The corresponding IDC factors are as follows:

Table 5-5 IDC - typical increments for hydro projects Years of construction % of total cost

2 10.65

3 15.68

4 18.05

5 24.24

In the case of Uganda, the project costs already included IDC, however only the total cost was available, so that corresponding total cost was retained.



Table 5-6 IDC for hydroelectric projects (Interest rate = 10%)

2 YEAR PROGRAM 3 YEAR PROGRAM

Time Factor

% Cost With TimeFactor

% Cost With

Years per year Interest Years per year Interest

Year 1 3.5 1.395965 0 0 3.5 1.395965 0 0

Year 2 2.5 1.269059 0 0 2.5 1.269059 30 38.07176

Year 3 1.5 1.15369 55 63.45294 1.5 1.15369 40 46.14759

Year 4 0.5 1.048809 45 47.1964 0.5 1.048809 30 31.46427

TOTAL 100 110.6493 100 115.6836

IDC 10.64933 15.68362

4 YEAR PROGRAM 5 YEAR PROGRAM

Time Factor

% Cost With TimeFactor

% Cost With

Years per year Interest Years per year Interest

Year 1 3.5 1.395965 10 13.95965 4.5 1.535561 10 15.35561

Year 2 2.5 1.269059 25 31.72647 3.5 1.395965 20 27.91929

Year 3 1.5 1.15369 40 46.14759 2.5 1.269059 20 25.38117

Year 4 0.5 1.048809 25 26.22022 1.5 1.15369 30 34.61069

Year 5 0.5 1.048809 20 20.97618

TOTAL 100 118.0539 100 124.2429

IDC 18.05392 24.24294

5.3 Minimum lead times to on-power Based on the review of the available study reports, approximate lead times for each new project have been estimated. These are based on the indicated level of preparedness of each project in the reference reports, and the following generic times for each of the individual activities leading up to implementation and on-power.

Table 5-7 Generic times for project activities

Activity Time in months

Prefeasibility study, following a reconnaissance level project identification 6‐12

Feasibility study (including consultant selection) 12‐24

Feasibility study update (where required) 6‐12

Environmental study and approval 12

Preparation of IPP process and tendering (where applicable) 12

Project financing (IPP or public ownership) 12

Final design (including consultant selection) – depending on size/complexity 12‐18

Tendering 6‐12

Construction (depending on size/complexity) 36‐60



Actual times will vary considerably, depending on environmental approval process, private or public ownership, commitment of the host government, feasibility of financing, size and complexity of the project, and the extent to which activities may be fast tracked (i.e., carried out in parallel, such as final design and preparation of the EIA).

Corresponding total minimum lead times to on power, as a function of plant size and level of preparedness, corresponding to the above time allowances, and result in the following minimum time frames, expressed in years.

Table 5-8 Minimum on-power lead times for hydroelectric plants (years) Present project status Project preparation Tender/Construction Total

Reconnaissance/Preliminary

less than 100 MW 3 3 6

100 to 150 MW 4 4 8

more than 150 MW 4 5 9

Prefeasibility


100 to 150 MW 3 5 8


Feasibility


100 to 150 MW 2 5 7


Design/tender documents


100 to 150 MW 1 4 5


These values allow no margin for delays between successive development stages. They also do not provide for additional delays for approval and financing activities. At least one year should be added to the above values for any project that is not being fast tracked.

5.4 Primary screening of future hydro options In Sections 4.2 and 4.3 the full range of previously identified regional resources that might be available to meet the needs of the region have been identified. In this section this list of options is screened to ensure that:

• any long lead times are identified

• projects with a need for further assessment are identified

• projects with insufficient information, or at a minimal level of preparation are screened out.

• conclusions of previous studies such as the SSEA for East Africa countries are taken into account.



The objective is to ensure that project scheduling (current candidate for 2013 to 2017 or long term) is respected and that non qualifying projects are not included. This screening has noted previously identified environmental and social issues, however has provided no independent assessment. This is therefore a primary screening.

Approach The initial step was to compile a long list of all identified specific power development options and, in the case of thermal options, potentially appropriate generic options, as is shown above. The assessment has been limited to projects that are not yet fully committed. Projects such as Bujagali that are under construction are not assessed. The resulting long list of new power options is shown in Table 5-2. This table includes alternatives for some hydroelectric sites (that are mutually exclusive, such as Masindi and Ayago in Uganda, and the Kabu / Kaganuzi alternatives in Burundi).

Screening Criteria Four basic screening criteria have been adopted, as follows:

• Availability of data (prefeasibility level or better), to provide an adequate basis for evaluation. In applying this criterion it is important to remember that a site discarded due to lack of sufficient information may still provide potential for development and, depending on other factors, should be investigated further.

• Options would be retained, for which residual environmental or socio-economic impacts are considered tolerable and in compliance with national laws and international conventions. One sensitive aspect to this qualification is the question of sites located in national parks or game reserves. The screening has included sites in the parks or reserves; as such development could be permissible under present national laws.17 However, development in National Parks or Game reserves would contravene the Algiers Convention, which is either signed by or in force in each of the countries of the region.

• High unit costs: Where the unit cost of hydro generation has been determined as too high and thus definitively uneconomic. However recognizing that the criterion should be the cost of alternative diesel burning imported LFO, this upper limit would be in the order of 20 c/kWh, at least for smaller hydro projects in the Eastern DRC, Rwanda, Burundi region, and this value has been assumed.

• Minimum size of project should be greater or equal to 10 MW for Rwanda, Burundi and Eastern DRC and greater or equal to 30 MW for the other countries. The 10 MW criterion refers to the minimum size that could have some impact on power supply for a neighbouring country and thus reflects regional nature of the study context. The 30 MW criterion is applied to the larger generating countries, and is the minimum value used in master plan studies in Kenya and Tanzania. These criteria were also used in the SSEA NELSAP study.

Failure to meet any of these criteria would result in an identified project being eliminated from the overall project candidate list under this screening. The status of environmental and social impact assessments of power options has been done at scoping level. Details of the Environmental and Social Impact Assessment (ESIA) will need to be undertaken during the feasibility study.

17 There have been situations in the region where the designation of National Park has been downgraded to game preserve

due to population pressures.



Table 5-10 shows projects assigned to the following groups:

• In - i.e. available for scheduling at any time after the minimum on power date

• After 2017 – a potential future candidate for which level of preparedness is insufficient at this time, or for which the reference source document / master plan has indicated the project to be a long term option

• After 2020 – a special case that refers to expected interconnection of South Sudan areas into the system by about year 2020

• Out – for projects that have been clearly assessed as uneconomic, or which would be in conflict with other projects, or which are deemed to need further assessment.

This primary screening process has therefore classed potential future hydro resources as follows:

Table 5-9 Classification of hydro resources Classification MW

Total hydro resource – excluding redundancies 26,778

Excluded 1,308

Net available 25,473

Available for 2013‐2017 9,918

Available after 2017 or 2020 15,554



Table 5-10 Primary screening of future hydro options

Name NOM. CAP (MW)

PREVIOUS STUDY Excludes planning/basin studies IN A

MP? SCREEN RESULT

Comment / previous assessment

LVL YEAR SOURCE

BURUNDI

Kabu 16 20 F 1995 SOGREAH N/A IN Being prepared for financing

Kagunuzi A 34 REC 1987 NORCONSULT N/A OUT environment

Mule 34 17 PF 2000 SOGREAH N/A OUT high cost

Siguvyaye 90 F 1980 ITS N/A > 2017 considered for IPP

Kaganuzi Complex 39 F 1987 NORCONSULT N/A OUT conflicts with Kabu 16, and impacts

Jiji 03 16 PF 2000 SOGREAH N/A OUT high cost

Mpanda 10 PF 1997 HYDROPLAN N/A IN considered for IPP

EAST DRC

Wannie Rukula 688 REC 1972 SICAI TRACTIONEL N/A > 2017 insufficient data available and long lead time

Piana Mwanga 38 REC 2004 N/A > 2017 insufficient data available and long lead time REHAB

Kyimbi Bender II 43 REC 2004 RSW N/A > 2017 insufficient data available and long lead time REHAB

Bangamisa 48 REC 1982 OCCR SEEE N/A > 2017 insufficient data available and long lead time

Babeda 1 50 REC 1972 SICAI TRACTIONEL N/A > 2017 insufficient data available and long lead time

Semliki 28 REC 1972 ONRD N/A > 2017 insufficient data available and long lead time

Sisi 5C 287 PF 2009 FICHTNER N/A IN for regional supply

Mugomba 40 REC 1972 ONRD N/A > 2017 insufficient data available and long lead time

Ruzizi III 145 F 2009 FICHTNER N/A IN for regional supply

EGYPT

ETHIOPIA

Mabil 1200 REC 1984 USBR > 2017 optimum Abbay cascade being studied JMP 1

Mandaya 2000 PF 2007 EDF/SCOTT WILSON MP IN midterm plan + Optimum being studied JMP

Halele Worabesa 422 F 2005 LAHMEYER MP IN midterm plan

Genale 6D 246 F 2009 LAHMEYER MP IN long term indicative plan

Karadobi 1600 PF 2006 NORPLAN MP > 2017

long term indicative plan + JMP 1 study

Tekaze II 450 MP > 2017 long term indicative plan

Genale 3D 258 F 2007 LAHMEYER MP IN midterm plan

Beko Abo 2100 REC 2007 NORPLAN > 2017

preliminary study and subject to JMP 1

Gibe III 1870 C EEPCo MP IN midterm plan

Border 1200 PF 2007 EDF/SCOTT WILSON MP > 2017

long term indicative plan + JMP study

Chemoga‐Yeda 280 F 2006 LAHMEYER MP IN midterm plan

Geba I & II 372 F 2005 NORCONSULT MP IN midterm plan

Awash 4 38 F 2006 ELECTROCONSULT IN

planned for local supply so not in power trade program

Gibe IV 1468 2009 EEPCO MP IN midterm plan

Baro 1 and 2 + Genji 900 F 2006 NORPLAN MP > 2017 long term indicative plan

Gibe V 662 EEPCo MP > 2017 long term indicative plan

Aleltu West 265 ACRES MP > 2017 long term indicative plan



Name NOM. CAP (MW)


MP? SCREEN RESULT


LVL YEAR SOURCE

Gojeb 153 F 1997 HUMPHREYS MP IN was to be IPP

Aleltu East 186 F 1995 ACRES MP > 2017 long term indicative plan

KENYA

Magwagwa 120 F 1991 NIPPON KOIE > 2017 Information has to be updated before in plan

Low Grand Falls 140 F 1998 NIPPON KOIE MP IN in current master plan

Mutonga 60 F 1998 NIPPON KOIE MP IN in current master plan

Ewaso Ngiro 180 F/D 2000 KNIGHT PIESOLD > 2017 environmental issues to be clarified

RWANDA

Nyabarongo 28 F 1999 SOGREAH N/A

SUDAN

Shukoli 210 1993 ACRES MP > 2017 Southern region ‐ wait for interconnection

Lakki 210 1993 ACRES MP > 2017 Southern region ‐ wait for interconnection

Bedden 400 1993 ACRES MP > 2017 Southern region ‐ wait for interconnection

Fula 1 720 1993 ACRES MP > 2017 Southern region ‐ wait for interconnection

Shereiq 315 F 1999 HYDROPROJECT MP IN in NEC 2008 annual report for before 2030

Dal 1 (low) 340 1993 ACRES MP > 2017 in NEC 2008 annual report for before 2030

Dagash 285 1993 ACRES MP > 2017 in NEC 2008 annual report for before 2030

Kagbar 300 F 1997 HYDROPROJECT MP IN in NEC 2008 annual report for before 2030

Sabaloka 90 1993 ACRES > 2017 study by GIBB in 1977

Rumela 30 F 1982 SOGREAH MP IN priority project

TANZANIA

Stieglers Gorge 3 300 PF 1984 NORPLAN MP AFTER 2017

Major project, environmental issues, PF only

Igamba Falls (Stage 2)* 8 D CURRENT MCC MP IN

Kakono (High) 53 PF 1976 NORCONSULT MP > 2017 Old study, PF only, long lead time

Stieglers Gorge 2 600 PF 1984 NORPLAN MP > 2017 Major project, environmental issues, PF only

Mpanga 144 PF 1997 SWEDPOWER/NORCONULT MP > 2017 Old study, PF only, long lead time

Ruhudji 358 F CURRENT IPP MP IN

Masigira 118 PF 1997 SWEDPOWER/NORCONULT MP > 2017 PF only, long lead time

Rumakali 222 F 1997 SWEDPOWER/NORCONULT MP > 2017 PF only, long lead time

Stieglers Gorge 1 300 PF 1984 NORPLAN MP > 2017 major project, environmental issues, PF only

Songwe Manolo 149 PF 2003 NORPLAN MP > 2017 International ‐ no sponsor

Songwe Sofre 157 PF 2003 NORPLAN MP > 2017 International ‐ no sponsor

Ikondo 340 PF 1984 NORCONSULT MP > 2017 old preliminary study

Taveta 145 PF 1984 NORCONSULT MP > 2017 old preliminary study

Rusumo Falls (Full) 63 F 2010 SNC MP IN committed



Name NOM. CAP (MW)


MP? SCREEN RESULT


LVL YEAR SOURCE

Songwe Bipugu 34 PF 2003 NORPLAN MP > 2017 International ‐ no sponsor

Luiche 15 REC 1983 NORCONSULT OUT lack of info

Kinansi II 120 PF 1997 SWEDPOWER/NORCONULT OUT high cost

UGANDA

Murchison base 222 PF 1997 KENNEDY AND DONKIN > 2017 PF only, long lead time, env issues

Kalagala 1‐7 315 PF 1998 LAHMEYER OUT not acceptable if Karuma built

Murchison High 750 MP > 2017 alternative to Murchison base

Ayago South 234 PF 1997 KENNEDY AND DONKIN > 2017 PF only, long lead time, env issues

Karuma low 200 F 1997 KENNEDY AND DONKIN MP IN

Masindi ‐1 360 PF 1997 KENNEDY AND DONKIN OUT Environmental impacts

Isimba 100 F MP IN

Masindi ‐ 2 360 PF 1997 KENNEDY AND DONKIN OUT Environmental impacts

Ayago North+South 550 1997 KENNEDY AND DONKIN MP > 2017 PF only, long lead time, env issues

kalagala 8‐10 135 PF MP OUT not acceptable if Karuma built

Karuma ( high alternative) 700 Under study MP IN alternative to Karuma low

Small hydro 60 MP IN Com mitted

MP: Master Plan; LVL: Level Level of Preparedness - C: Construction; F: Feasibility; PF: Prefeasibility; REC: Reconnaissance; D: Design IPP: Independent Power Producer; JMP: Joint Multipurpose project

5.4.1 Rejected options Further information on the rejected or excluded options is provided as follows:

Burundi Kaganuzi A and Kaganuzi Complex: The project (both options would involve a diversion on the Kaburantwa river and power facilities on the Kaganuzi river. The Kaburantwa project would divert a maximum of 8m3/s from the Kaburantwa River. This compares with the 10.6 m3/s average flow at the downstream Kabu 16 site on this river. Consequently this diversion for either of the Kaganuzi options would both eliminate the Kabu 16 site, and would reduce the Kaburantwa river average flow to 20% of its present average.

The Kaganuzi A project would develop the most head, and therefore would provide the maximum use of the hydroelectric resource. However the Kaganuzi C scheme would supply irrigation water to the Imbo plain. The Kaganuzi C project was considered ready for final design and the Kaburantwa project had been studied in detail. Little information is available on Kaganuzi A. Both Kaganuzi options would require the Kaburantwa diversion to be viable. The Kaganuzi complex (i.e., Kaganuzi C and Kaburantwa) has been rejected because of the major environmental and social risk from the required diversion of the Kaburantwa River. However with an indicated firm energy cost of over 10 cents/kWh, after allowing a credit for its multipurpose function, it is unlikely that the project would be economic, at least in a regional context.



This option was studied originally by Lahmeyer in 1983 and then by Norconsult, as described in their report of 198718. Hydroplan also studied it in an undated report.19

Tanzania Kihansi II: This project would be a 2 x 60 MW addition to the existing project lower Kihansi project, together with the construction of an upstream storage dam. The combined powerhouse addition and upstream storage project was not listed as a candidate in the EAPMP. However the Upper Kihansi storage project, was assessed.

This project was reassessed in the 2009 Tanzania power system master plan, and both energy benefits and capital costs were re-estimated. The project was found to be very costly as there was insufficient water to take full benefit from the improved flow regulation and increased turbine capacity.

Uganda Kalagala: The project would be located on the Victoria Nile 25 km downstream of Owen Falls and also downstream of the proposed Bujagali project. The project would be a conventional run of river development comprising 7 45 MW units (315 MW) in a first phase, and a further 3 units (135 MW) in the second stage for a total capacity of 450 MW.

The project could provide low cost energy, at an average cost in the order of 4 cents/kWh, and firm energy would be relatively high, due to the regulating effect of Lake Victoria. The project has been studied to the prefeasibility level20, and a preliminary assessment of environmental potential impacts has been prepared21.

It has long been recognized that development of the three projects of Bujagali, Kalagala and Karuma would result in a major risk to tourism, as well as resulting in other significant social and environmental impacts. Consequently recent planning has assumed that either, but not both, Kalagala and Karuma could be constructed. In line with this concept, in 2002 the Uganda Government signed an offset agreement with the World Bank, as part of the agreements related to the Bujagali project, which set aside the Kalagala project to protect its natural habitat, environmental and spiritual values and for tourism development22.

Consequently the Kalagala project has not been considered as a candidate for inclusion in any portfolios to meet future loads.

Masindi 1-2: The Masindi scheme consists of two 360 MW stages, to divert flow from the Nile downstream of Lake Kyoga to Lake Albert, some 200 km downstream. This project would therefore provide a major reduction in flows of the Nile between these two points, and has therefore been rejected because of major environmental / social risk. This project would also displace the Ayago and Murchison Falls hydro options. It would therefore be a trade-off between reduced Nile flows through the park, and possible new infrastructure construction in the park.

18 Norconsult, Kagunuzi Multipurpose Project, Feasibility Study, Volume III, Hydropower Scheme, Draft Report, African

Development Bank, February 1987 19 Hydroplan Ingenieur-Gesellschaft mbh/Fichtner Beratende Ingenieure, Étude finale de faisabilité du projet hydroagricole et

hydroélectrique de Kaganuzi C, Rapport préliminaire de Seconde Phase, Tome I, Rapport de synthèse et volets hydro-agricole, organisationnel, électrique et économique, République du Burundi, Ministère de l’Énergie et des Mines, Ministère de l’Agriculture et de l’Élevage

20 Kennedy and Donkin, (Uganda) Hydropower development master plan, 1997 21 ESG International Inc., WS Atkins (Epsom UK), Bujagali Hydropower Project - Environmental Impact, prepared for AES

Nile Power, March 2001 22 IBRD/IDA Management report and recommendation in response to the inspection panel investigation report, Uganda, Third Power Project, fourth Power Project and Bujagali Hydropower project, June 2002, and Annex 2 letter from the Minister of Finance, Planning and Economic Development to the World Bank, June 4, 2002



The indicated cost of firm energy is 6 cents/kWh or more, and may be significantly higher depending on the construction time, primarily to complete the 70 km power tunnels. Information on the project is limited, and for this reason it was not considered in the EAPMP.

Options delayed due to insufficient data This situation primarily relates to identified sites in the Eastern DRC. With the exception of Ruzizi IV (Sisi 5C) and two rehabilitation projects, these sites have only been evaluated at a reconnaissance level, and these studies were prior to 1980 [6].

Based on the very preliminary data available, eight sites were recommended for further study in the 2006 SSEA study, of which the Ruzizi IV (Sisi 5C) site has been subject to more detailed studies.

For the current study the remaining seven projects are classified as potential sites for after 2017. In any case the minimum lead times to on power would achieve the same result. The total installed capacity of these sites would be 935 MW. These sites include:

Table 5-11 Potential DRC sites for after 2017

DRC Projects MW

Wannie Rukula 688

Piana mwanga 38

Kyimbi Benera II 43

Bengamisa 48

Babeda 50

Semliki 28

Mugomba 40

5.5 Future hydro generation costs For the purpose of comparing alternative new generation options, unit capacity ($/KW) and energy (US$/MWh) costs have been estimated using a simplified economic analysis. The capital cost includes interest during construction, which is a function of the scheduling of capital expenditures during construction, the length of the construction period, and the discount rate (Planning criteria in Section 3). The unit cost of capacity is estimated from the capital cost, including interest during construction, and the nominal plant installed capacity. (Note that the firm capacity of the plant, especially for run of the river hydroelectric projects may be significantly lower).

Average annual costs over the life of the project are calculated for the capacity component, using the parameters outlined in the planning criteria and assuming uniform annual payment of capital and interest. Unit energy costs ($/MWh) are calculated from capital charges and variable operation and maintenance costs.

The total cost of energy generation is a function of plant capacity factor and combines the fixed annual capacity component ($/kW-year/hours of operation) with the variable energy component (cents/kWh). In the case of the hydroelectric option the plant capacity factor, and thus average hours of operation, is defined.

This procedure does not take into account any future escalation operating costs. The calculation of unit generation costs for hydroelectric projects is shown in Table 5-12 that follows23 24. The above procedure is useful in comparing relative plant costs, however for 23 Table 5.12 shows relatively high unit costs for the Mpanda 10 MW project in Burundi and the Nyabarongo 27.8 MW project in Rwanda. The source references for these costs are given in Tables 4.2 and 4.8 respectively. For both these projects the



hydroelectric projects this does not take into account different plant capacity factors (CF) - derived as:

CF (%) =

100

Table 5-12 provides a listing of all identified hydro projects, including some of those shown as excluded in Table 5-10. This is to provide a complete listing of comparative costs. However in the ranking of projects by costs and on power date shown in Table 5-13 these excluded projects are not shown.

The parameters used to calculate hydro generation costs are provided in the planning criteria given in Section 3. These parameters, as related to this study to establish overall new generation resources, include:

• Adjustment of capital cost to a common reference year (2009)

• Allocation of costs for multipurpose projects (no adjustment used for this study)

• Service lives

• Operation, maintenance and other costs

• Construction period and interest during construction

project costs were re-estimated in 2004 as part of the SSEA 1 study using quantities from the original reports. Also in both cases the costs included transmission to the grid, which is the conventional procedure for hydro. In the case of Mpanda the transmission cost was 5% of the total, while for Nyabarongo the transmission cost was 10 % of the total. 24 The unit cost shown in Table 5.12 for the Sabaloka 90 MW project in Sudan is also relatively high. Capital cost was taken from the 2008 NBI Preliminary Basin-wide Study, however is essentially the same as that shown in the EDF Power Trade Study (see Module 3, Volume 4,, which were escalated to 596 MUSD in 2006 prices, based on the 2003 NEC LTPPS. Costs include transmission, however while no cost breakdown was identified, the EDF report states that transmission costs to connect to the grid were included however for all projects this cost was less than 4 % of the total project cost.



Table 5-12 EAPP Region Future Hydroelectric projects – Unit Generation costs

Name

Generation Investment Costs Annual Costs (MUSD) Unit Prices

Inst Cap. MW

Avrg Energy GWh

Orig cost MUSD

Price Year

Esc. Index 2009

Esc to Dec. 09 MUSD

Const Years

IDC %

Cost w/ IDC

MUSD

Env. Mitigation MUSD

Total Cost MUSD

Amort O & M Insurance +Interim Repl.

Total Energy cost

c/kWh

Invest Cost $/kW

BURUNDI

Jiji 03 16 40 42.20 2004 127.2 53.67 3 15.68 62.09 2.68 64.78 6.53 0.08 0.23 6.84 17.09 4179

Kabu 16 20 113 38.34 2004 127.2 48.76 3 15.68 56.41 2.44 58.85 5.94 0.10 0.21 6.24 5.52 2943

Kaganuzi A 34 98 50.85 2004 127.2 64.68 3 15.68 74.82 3.23 78.05 7.87 0.17 0.27 8.32 8.49 2296

Kaganuzi Complex 39 187 136.12 2004 127.2 173.13 3 15.68 200.28 8.66 208.94 21.07 0.20 0.73 22.00 11.76 5357

Mpanda 10 40 42.66 2004 127.2 54.26 3 15.68 62.77 2.71 65.48 6.60 0.05 0.23 6.88 17.21 6548

Mule 34 17 54 33.00 2004 127.2 41.97 3 15.68 48.56 2.10 50.65 5.11 0.08 0.18 5.37 9.94 3070

Siguvyaye 90 510 280.00 2004 127.2 356.13 4 18.05 420.43 17.81 438.23 44.20 0.45 1.53 46.18 9.06 4869

EAST DRC

Piana Mwanga 29 182 35.00 2004 127.2 44.52 3 15.68 51.50 2.23 53.72 5.42 0.15 0.19 5.75 3.16 1853

Bendera 43 143 52.06 2004 127.2 66.22 3 15.68 76.60 3.31 79.91 8.06 0.22 0.28 8.55 5.98 1858

Babeda I 50 341 101.42 2004 127.2 129.00 3 15.68 149.23 6.45 155.68 15.70 0.25 0.54 16.50 4.84 3114

Bengamisa 48 363 100.34 2004 127.2 127.62 4 18.05 150.66 6.38 157.04 15.84 0.24 0.55 16.63 4.58 3272

Mugomba 40 163 71.20 2004 127.2 90.56 4 18.05 106.91 4.53 111.44 11.24 0.20 0.39 11.83 7.26 2786

Semliki 28 118 34.50 2004 127.2 43.88 4 18.05 51.80 2.19 54.00 5.45 0.14 0.19 5.78 4.89 1928

Ruzizi III 145 664 394.47 2009 100.0 394.47 4 18.05 465.69 19.72 485.41 48.96 0.73 1.70 51.38 7.74 3348

Ruzizi IV (Sisi 5C) 287 1249 482.85 2009 100.0 482.85 4 18.05 570.02 24.14 594.17 59.93 1.44 2.08 63.44 5.08 2070

Wannie Rukula 688 6000 1184.69 2004 127.2 1506.81 4 18.05 1778.84 75.34 1854.19 187.01 3.44 6.49 196.94 3.28 2695

EGYPT

Assiut 40 175 120.00 2004 127.2 152.63 4 18.05 180.18 7.63 187.81 18.94 0.20 0.66 19.80 11.31 4695

ETHIOPIA

Gibe III 1870 6087 1704.00 2007 101.4 1727.17 5 24.24 2145.89 0.00 2145.89 216.43 9.35 7.51 233.29 3.83 1148

Gibe IV 1468 5644 2214.00 2007 101.4 2244.11 5 24.24 2788.15 0.00 2788.15 281.21 7.34 9.76 298.31 5.29 1899

Halele Worabesa 422 2215 507.00 2007 101.4 513.90 4 18.05 606.67 0.00 606.67 61.19 2.11 2.12 65.42 2.95 1438



Name


Inst Cap. MW

Avrg Energy GWh

Orig cost MUSD

Price Year

Esc. Index 2009

Esc to Dec. 09 MUSD

Const Years

IDC %

Cost w/ IDC

MUSD


Total Cost MUSD


Total Energy cost

c/kWh

Invest Cost $/kW

Chemoga‐Yeda 280 1384 403.00 2007 101.4 408.48 4 18.05 482.23 0.00 482.23 48.64 1.40 1.69 51.72 3.74 1722

Geba I & II 372 1802 535.00 2007 101.4 542.28 4 18.05 640.18 0.00 640.18 64.57 1.86 2.24 68.67 3.81 1721

Genale 3D 258 1228 304.00 2007 101.4 308.13 4 18.05 363.76 0.00 363.76 36.69 1.29 1.27 39.25 3.20 1410

Baro 1 and 2 + Genji 900 4522 976.00 2006 104.5 1020.21 4 18.05 1204.40 0.00 1204.40 121.47 4.50 4.22 130.19 2.88 1338

Mandaya 2000 11950 2640.00 2007 101.4 2675.90 5 24.24 3324.62 0.00 3324.62 335.32 10.00 11.64 356.95 2.99 1662

Border 1200 6331 1626.00 2007 101.4 1648.11 5 24.24 2047.66 0.00 2047.66 206.53 6.00 7.17 219.69 3.47 1706

Gibe V 662 1882 879.00 2007 101.4 890.95 5 24.24 1106.95 0.00 1106.95 111.65 3.31 3.87 118.83 6.31 1672

Beko Abo 2100 10825 2838.40 2006 104.6 2968.97 5 24.24 3688.73 0.00 3688.73 372.04 10.50 12.91 395.45 3.65 1757

Karadobi 1600 8784 2040.00 2007 101.4 2067.74 5 24.24 2569.03 0.00 2569.03 259.11 8.00 8.99 276.10 3.14 1606

Genale 6D 246 1609 383.00 2007 101.4 388.21 4 18.05 458.30 0.00 458.30 46.22 1.23 1.60 49.06 3.05 1863

Gojeb 150 526 288.00 2007 101.4 291.92 3 15.68 337.70 0.00 337.70 34.06 0.75 1.18 35.99 6.84 2251

Tekaze II 450 1758 435.00 2007 101.4 440.92 4 18.05 520.52 0.00 520.52 52.50 2.25 1.82 56.57 3.22 1157

Aleltu East 186 885 438.00 2006 104.5 457.84 4 18.05 540.50 0.00 540.50 54.51 0.93 1.89 57.34 6.48 2906

Aleltu West 265 1028 561.00 2006 104.5 586.41 4 18.05 692.28 0.00 692.28 69.82 1.33 2.42 73.57 7.16 2612

Awash 4 38 166 49.00 2006 104.5 51.22 3 15.68 59.25 0.00 59.25 5.98 0.19 0.21 6.37 3.84 1559

KENYA

Mutonga 60 336 235.30 2008 100.0 235.30 3 15.68 272.20 0.00 272.20 27.45 0.30 0.95 28.71 8.54 4537

Low Grand Falls 140 707 460.90 2008 100.0 460.90 4 18.05 544.11 0.00 544.11 54.88 0.70 1.90 57.48 8.13 3887

Magwagwa 120 525 294.50 2004 127.2 374.57 4 18.05 442.20 0.00 442.20 44.60 0.60 1.55 46.75 8.90 3685

Karura 56 184 196.00 2009 100.0 196.00 3 15.68 226.74 0.00 226.74 22.87 0.28 0.79 23.94 13.01 4049

Ewaso Ngiro 180 568 312.00 2004 127.2 396.83 5 24.24 493.04 0.00 493.04 49.73 0.90 1.73 52.35 9.22 2739

RWANDA

Nyabarongo 28 150 96.75 2004 127.2 123.06 3 15.68 142.35 6.15 148.50 14.98 0.14 0.52 15.64 10.42 5342

SUDAN

Sabaloka 90 670 596 2006 104.5 623.00 4 18.05 735.47 31.15 766.62 77.32 0.45 2.68 80.45 12.01 8518

Shereiq 315 1962 876 2006 104.5 915.68 5 24.24 1137.67 0.00 1137.67 114.74 1.58 3.98 120.30 6.13 3612



Name


Inst Cap. MW

Avrg Energy GWh

Orig cost MUSD

Price Year

Esc. Index 2009

Esc to Dec. 09 MUSD

Const Years

IDC %

Cost w/ IDC

MUSD


Total Cost MUSD


Total Energy cost

c/kWh

Invest Cost $/kW

Kagbar 300 1413 763 2006 104.5 797.56 5 24.24 990.92 39.88 1030.80 103.97 1.50 3.61 109.07 7.72 3436

Dal 1 (low) 340 1968 1113 2007 101.4 1128.58 5 24.24 1402.18 0.00 1402.18 141.42 1.70 4.91 148.03 7.52 4124

Dagash 285 1503 800 2006 104.5 836.24 5 24.24 1038.97 41.81 1080.78 109.01 1.43 3.78 114.21 7.60 3792

Fula 1 720 4134 1319 2006 104.5 1378.75 5 24.24 1713.00 68.94 1781.94 179.72 3.60 6.24 189.56 4.59 2475

Shukoli 210 1443 420 2006 104.5 439.03 4 18.05 518.29 21.95 540.24 54.49 1.05 1.89 57.43 3.98 2573

Lakki 210 1443 429 2006 104.5 448.43 4 18.05 529.39 22.42 551.82 55.66 1.05 1.93 58.64 4.06 2628

Bedden 400 2748 880 2006 104.5 919.86 5 24.24 1142.87 45.99 1188.86 119.91 2.00 4.16 126.07 4.59 2972

Rumela 30 83 193 2006 104.5 201.74 3 15.68 233.38 10.09 243.47 24.56 0.15 0.85 25.56 30.79 8116

TANZAN IA

Ruhudji 358 1928 494.74 2008 100.0 494.74 5 24.24 614.68 0.00 614.68 62.00 1.79 2.15 65.94 3.42 1717

Kinansi II 120 69 191.91 2008 100.0 191.91 3 15.68 222.01 0.00 222.01 22.39 0.60 0.78 23.77 34.45 1850

Masigira 118 664 208.67 2008 100.0 208.67 4 18.05 246.34 0.00 246.34 24.85 0.59 0.86 26.30 3.96 2088

Rumakali 222 1475 458.90 2008 100.0 458.90 5 24.24 570.15 0.00 570.15 57.50 1.11 2.00 60.61 4.11 2568

Mpanga 144 955 248.96 2008 100.0 248.96 4 18.05 293.91 0.00 293.91 29.64 0.72 1.03 31.39 3.29 2041

Stiegler Gorge 1 300 2230 872.68 2008 100.0 872.68 5 24.24 1084.24 0.00 1084.24 109.36 1.50 3.79 114.65 5.14 3614

Stiegler Gorge 2 600 1506 310.91 2008 100.0 310.91 5 24.24 386.28 0.00 386.28 38.96 3.00 1.35 43.31 2.88 644

Stiegler Gorge 3 300 1523 254.87 2008 100.0 254.87 5 24.24 316.66 0.00 316.66 31.94 1.50 1.11 34.55 2.27 1056

Igamba Falls (Stage 2)* 8 65 11.30 2004 127.2 14.37 3 15.68 16.63 0.00 16.63 1.68 0.04 0.06 1.78 2.73 2078

Igamba Falls 980 m 80 494 404.00 2004 127.2 513.85 4 18.05 606.62 0.00 606.62 61.18 0.40 2.12 63.71 12.90 7583

Ikondo 340 1842 640.88 2009 100.0 640.88 3 15.68 741.39 0.00 741.39 74.78 1.70 2.59 79.07 4.29 2181

Taveta 145 850 379.88 2009 100.0 379.88 3 15.68 439.46 0.00 439.46 44.32 0.73 1.54 46.59 5.48 3031

Songwe Bipugu 34 153 84.07 2004 127.2 106.93 3 15.68 123.70 0.00 123.70 12.48 0.17 0.43 13.08 8.55 3638

Songwe Sofre 157 736 255.05 2004 127.2 324.40 3 15.68 375.28 0.00 375.28 37.85 0.79 1.31 39.95 5.43 2390

Songwe Manolo 149 780 259.32 2004 127.2 329.83 3 15.68 381.56 0.00 381.56 38.48 0.75 1.34 40.56 5.20 2561

Kakono (High) 53 404 90.07 2008 100.0 90.07 3 15.68 104.20 0.00 104.20 10.51 0.27 0.36 11.14 2.76 1966

Kishanda 207 1087 181.00 2004 127.2 230.21 4 18.05 271.78 0.00 271.78 27.41 1.04 0.95 29.40 2.70 1313



Name


Inst Cap. MW

Avrg Energy GWh

Orig cost MUSD

Price Year

Esc. Index 2009

Esc to Dec. 09 MUSD

Const Years

IDC %

Cost w/ IDC

MUSD


Total Cost MUSD


Total Energy cost

c/kWh

Invest Cost $/kW

UGANDA

Luiche 15 100 68.70 2004 127.2 87.38 3 15.68 101.08 0.00 101.08 10.20 0.08 0.35 10.63 10.63 6607

Rusumo Falls (Full) 63 444 227.44 2008 100.0 227.44 4 18.05 268.50 29.45 297.95 30.05 0.31 1.04 31.40 7.07 4845

Karuma High 700 5512 2660.00 2009 100.0 2660.00 5 2660.00 133.00 2793.00 281.70 3.50 9.78 294.98 5.35 3990

Ayago 550 4336 2048.20 2009 100.0 2048.20 4 2048.20 102.41 2150.61 216.91 2.75 7.53 227.19 5.24 3910

Murchison high 750 5904 1579.50 2009 100.0 1579.50 5 1579.50 78.98 1658.48 167.27 3.75 5.80 176.83 3.00 2211

Isimba 100 788 345.80 2009 100.0 345.80 4 345.80 17.29 363.09 36.62 0.50 1.27 38.39 4.87 3631

Notes:

The Capital Cost of large hydro plants includes the cost of transmission required to connect the HPP to the system.

Environmental Mitigation Costs already include IDCs.



5.6 Ranking by cost and earliest availability The project ordering shown in Table 5-13 takes projects that are ranked in terms of energy cost, by country, and assigns them into future periods based on earliest on-power dates, as follows:

• Unit costs for hydro average energy were taken from Table 5-12.

• Earliest on-power dates were based on the minimum lead time criteria provided in Section 5.3, and as shown in Table 4-2 to Table 4-11. Availability (earliest on-power) is based on present level of preparation.

The objective of Table 5-13 is primarily to identify those projects that could start generating in the short term 2013 to 2017 planning period, and to provide ordering in terms of generation cost. It should be noted that some projects in cascade are ordered from upstream to downstream, not by cost, e.g.

• Steigler´s Gorge - three stages to project

• Songwe – 3 projects

Also some projects are delayed beyond their nominal earliest on-power date due to lack of a recent study, as is noted in the screening shown in Table 5-10. Some other projects are delayed as their recent country master plan has designated them as long term options. In the table certain “shared” projects are attributed to one country, as follows:

• Ruzizi hydro plants – Eastern DRC

• Rusumo - Tanzania



Table 5-13 EAPP Hydro Options – Ranking by unit cost and earliest on-power

Name

Generation and capital cost Unit Costs

Earliest on Power

Earliest available generation 2013‐2017 MW Earliest available generation 2018‐2022

MW

Nom. Cap MW

Avrg Energy GWh

Total cost 2009 MUSD

Energy cost c/kWh

Invest Cost $/kW

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

BURUNDIKabu 16 20 113 58.85 5.52 2943 2015 90 Siguvyaye 90 510 420.43 9.06 4869 2016 90 Mule 34 17 54 48.56 9.94 3070 2016 17 Jiji 03 16 40 64.78 17.09 4179 2016 16 Mpanda 10 40 62.77 17.21 6548 2016 10

EAST DRCPiana Mwanga 29 182 53.72 3.16 1853 2017 29 Wannie Rukula 688 6000 1854.19 3.28 2695 2019 688 Bengamisa 48 363 157.04 4.58 3272 2017 48 Babeda I 50 341 155.68 4.84 3114 2017 50 Semliki 28 118 54.00 4.89 1928 2017 28 Bendera 43 143 79.91 5.98 1858 2017 43 Ruzizi IV (Sisi 5C) 287 1249 594.17 5.08 2070 2019 287 Mugomba 40 163 111.44 7.26 2786 2017 40 Ruzizi III 145 664 485.41 7.74 3348 2016 145

EGYPTAssiut 40 175 187.81 11.31 4695 2015 40

ETHIOPIA

Baro 1 and 2 + Genji 900 4522 1204.40 2.88 1338 2016, 2017

900

Halele Worabesa 422 2215 606.67 2.95 1438 2014 422 Mandaya 2000 11950 3324.62 2.99 1662 2019 2000 Genale 6D 246 1609 458.30 3.05 1863 2016 246 Karadobi 1600 8784 2569.03 3.14 1606 2018 1600 Genale 3D 258 1228 363.76 3.20 1410 2015 258 Tekaze II 450 1758 520.52 3.22 1157 2019 450 Border 1200 6331 2047.66 3.47 1706 2019 1200 Beko Abo 2100 10825 3688.73 3.65 1757 2019 2100 Chemoga‐Yeda 280 1384 482.23 3.74 1722 2016 280



Name Generation and capital cost Unit Costs

Earliest on Power


MW Nom. Cap

MW Avrg Energy

GWh Total cost 2009 MUSD

Energy cost c/kWh

Invest Cost $/kW

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Gibe III 1870 6087 2145.89 3.83 1148 2013 1870 Geba I & II 372 1802 640.18 3.81 1721 2018 372 Awash 4 38 166 59.25 3.84 1559 2016 38 Gibe IV 1468 5644 2788.15 5.29 1899 2015 1468 Gibe V 662 1882 1106.95 6.31 1672 2019 662 Aleltu East 186 885 540.50 6.48 2906 2018 186 Gojeb 150 526 337.70 6.84 2251 2016 150 Aleltu West 265 1028 692.28 7.16 2612 2019 265

KENYALow Grand Falls 140 707 544.11 8.13 3887 2017 140 Mutonga 60 336 272.20 8.54 4537 2016 60 Magwagwa 120 525 442.20 8.90 3685 2017 120 Ewaso Ngiro 180 568 493.04 9.22 2739 2016 180 Karura 56 184 226.74 13.01 4049 2017 56

RWANDANyabarongo 28 150 148.5 10.42 5342 2014 28

SUDANShukoli 210 1443 540.24 3.98 2573 2020 210 Lakki 210 1443 551.82 4.06 2628 2020 210 Fula 1 720 4134 1781.94 4.59 2475 2020 720 Bedden 400 2748 1188.86 4.59 2972 2020 400 Shereiq 315 1962 1137.67 6.13 3612 2016 315 Dal 1 (low) 340 1968 1402.18 7.52 4124 2018 340 Dagash 285 1503 1080.78 7.60 3792 2019 285 Kagbar 300 1413 1030.80 7.72 3436 2018 300 Sabaloka 90 670 766.62 12.01 8518 2017 90

TANZAN IAStiegler Gorge 3 300 1523 316.66 2.27 1056 2019 300 300 Kishanda 207 1087 271.78 2.70 1313 2016 207 207

Igamba Falls (Stage 2) 8 65 16.63 2.73 2078 2019 8 8 Kakono (High) 53 404 104.20 2.76 1966 2016 53 53 Stiegler Gorge 2 600 1506 386.28 2.88 644 2018 600 600 Mpanga 144 955 293.91 3.29 2041 2018 144 144 Ruhudji 358 1928 614.68 3.42 1717 2016 358 358



Name Generation and capital cost Unit Costs

Earliest on Power


MW Nom. Cap

MW Avrg Energy

GWh Total cost 2009 MUSD

Energy cost c/kWh

Invest Cost $/kW

2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

Masigira 118 664 246.34 3.96 2088 2018 118 118 Rumakali 222 1475 570.15 4.11 2568 2018 222 222 Ikondo 340 1842 741.39 4.29 2181 2019 340 340 Stiegler Gorge 1 300 2230 1084.24 5.14 3614 2015 300 300 Songwe Manolo 149 780 381.56 5.20 2561 2020 149 149 Songwe Sofre 157 736 375.28 5.43 2390 2019 157 157 Taveta 145 850 439.46 5.48 3031 2020 145 145 Songwe Bipugu 34 153 123.70 8.55 3638 2016 34 34 Igamba Falls 980 m 80 494 606.62 12.90 7583 2020 80 80 Kinansi II 120 69 222.01 34.45 1850 2018 120 120

UGANDAMurchison high 750 5904 1658.48 3.00 2211 2019 750 Isimba 100 788 363.09 4.87 3631 2016 100 Ayago 550 4336 2150.61 5.24 3910 2019 550 Karuma High 700 5512 2793.00 5.35 3990 2018 700



Total new hydro availability by December 2017, and for the next 5 year period, is summarized as follows:

Table 5-14 Total new hydro for the first two 5 year periods of the study (MW) Country New hydro on‐power 2013‐2017 New hydro on‐power 2018‐2022

Burundi 62 90

Eastern DRC 145 1,446

Egypt 40 0

Ethiopia 4,582 9,735

Kenya 256 300

Rwanda 28 0

Sudan 0 2,870

Tanzania 477 2,648

Uganda 100 2,000

TOTAL 5,691 19,089



6 FUTURE THERMAL OPTIONS 6.1 Capital costs for future thermal projects The costs of all future thermal options that have been listed in country master plans have been harmonized, by escalating capital costs to 2009 price levels using the indices provided in Section 3.2.4, and by adding an allowance for interest during construction. The allowance for interest during construction reflects normal construction periods, as a function of plant type and size,

For projects for which capital costs have not been provided, generic prices have been used, as are provided in Section 6.1.1 below. These generic prices reflect plant size and type and have been developed by comparing costs provided in country master plans with international data.

6.1.1 Generic capital costs Steam plants Various countries have included steam plants in their generation plans. These can be coal, oil or gas fired. Plant sizes range from 100-150 MW to multiples of units in the 600 MW range.

A review of recent costs for coal fired steam plant indicates overnight costs (ie without financing / IDC) in the range of:

• 150 MW units 2800 US$/kW

• 600 MW 2000 US$/kW

The comparisons and trend line for coal fired plant are shown inTable 6-1. Information sources include:

• 2009 prices developed for the TANESCO PSMP

• 2004 prices for the EAPMP, for Uganda, Kenya and Tanzania

• 2008 prices included in the Kenya Master Plan

• Prices given in the Uganda (2009) and Sudan (2000) generation plans

• Prices given in the 2008 ESMAP report on equipment prices in the energy sector. These compared prices for plants were sourced in the USA, India and Romania. Romania data represented a median range and so were used.25

• SNC statistical data for EPCM packages as a function of size

These costs were escalated to 2009 price levels, as required, using USBR Dept Labour cost indices for electrical generating plant.26

25 ESMAP – URS Study of equipment prices in the energy sector, June 2008 26 US Department of labout producer price index for electric power generation NAICS 221110



Table 6-1 Comparative costs for coal fired STPPs - 2009 $ excluding IDC

Config. Total Capacity

(MW) Capital Cost (MUSD)

Year EscalationFactor

Cost2009

Cost ($/KW)

Source

4x50 200 760 2009 100 760 3800 SNC for TANESCO2x100 200 600 2009 100 600 3000 SNC for TANESCO2x150 300 780 2009 100 780 2600 SNC for TANESCO2x100 200 190 2004 127 241 1207 EAPMP 2x150 300 260 2004 127 330 1101 EAPMP 2x150 300 742 2007 102 757 2523 Kenya 4x150 600 1234 2007 102 1259 2098 Kenya 1x56 56 167 2009 100 167 2982 Uganda PB 1x400 400 457 2006 105 480 1200 Sudan PB 1x100 100 133 2005 109 145 1450 Ethiopia PB 1x300 300 875 2007 102 893 2975 ESMAP/Romania1x500 500 1267 2007 102 1292 2585 ESMAP/Romania1x800 800 1801 2007 102 1837 2296 ESMAP/Romania1x200 200 446 2007 102 455 2275 SNC EPCM Packages1x300 300 624 2007 102 636 2122 SNC EPCM Packages1x350 350 714 2007 102 728 2081 SNC EPCM Packages1x400 400 800 2007 102 816 2040 SNC EPCM Packages

The above values also provided the basis for oil and gas fired steam plant. The ESMAP report provided comparative costs for 300 MW coal, oil and gas fired units, which indicated oil fired plant was approximately 50 % of the price of coal fired plant, and gas fired plant 40 % for the coal plant cost. For the current study the relative costs have been assumed as:

• Coal plant 100 %

• Oil plant 60 %

• Gas plant 50 %

Typical unit costs for steam generation plant used in this study were therefore as follows:

Table 6-2 Typical unit costs for STPP Fuel Unit size (MW) Cost – no IDC (US$/kW) ‐ 2009

Coal 650 2000

Coal 150 2500

Coal 100 2800

Oil 135 1700

Gas 650 1000

Gas 50 1700



Nuclear A series of 5000 MW nuclear units are included in the Egypt generation plan. Capital costs will depend on the plant type, size, supplier technology, supplier country and plant location.

Kenya is also considering nuclear generation, with possible on-power of the first plant about 2020. It is understood that 1000 MW modules are planned.27

A useful basis for typical nuclear plant costs is provided by a 2006 paper by NERA28. This provides a comparison of costs from a number of suppliers in different countries, with units typically in the 1000 MW size range. Indicated capital costs, understood to be overnight (excluding IDC) are in the range of 1000 US$/kW to 2500 US$/kW. A typical value would be about 2000 US$/kW (corresponding to a 2005 Areva price for multiple units). Escalated to 2009 the corresponding cost would be 2200 US$/kW.

A report issued in 2010 by the World Nuclear Association provides somewhat higher costs29. Typically 2008 overnight costs for a complete plant (including cooling towers, site works, land and risk) are in the order of 3000 to 4600 US$/kW. The same reference quotes a series of recent bare plant costs in the 2000 to 3500 US$/kW range. Adding balance of plant (about 27 %) would increase this range to 2500 to 4500 US$/kW. For the purpose of preliminary studies an all-in overnight cost of 3500 US$/kW has been assumed.

Geothermal Geothermal generation is planned for Kenya and Ethiopia. Kenya already has significant experience with this technology. Prices in the region from recent studies, and adjusted to 2009 suggest a cost range of 2500 to 4000 US$/kW. An average cost of 3800 US$/kW, which reflects the Kenya recent master plan costs, is used for future projects in Kenya. Comparative costs are shown in Table 6-3.

For Ethiopia capital costs for a series of geothermal plants are provided in a recent report issued by the Ministry of Mines and Energy30. These estimates provided a range of 2800 to 3100 US$/kW. A unit cost of 3000 US$/kW has been used for Ethiopia projects.

Gas turbines Open cycle gas turbines are proposed in the country generation plans for Tanzania and Uganda. Unit sizes are in the 50-60 MW range. Some comparative costs at 2009 price levels are shown in Table 6-3. The SNC value for the TANESCO PSMP reflected an average of 7 price quotations. Prices quoted in 2008 indicated a cost of about 850 US$/kW for 25 MW units and 650 to 730 US$/kW for 65 MW units, expressed as bare plant overnight costs. In the ENPTPS, It is also suggested to use 140 MW OCGT generics in Ethiopia. For the purpose of this study a complete plant overnight cost of 900 US$/kW has been selected for all plants.

Combined cycle gas turbine plants Combined cycle plants form an important part of the Egyptian generation plan, and are included in the Kenya and Uganda expansion plans. For Egypt a series of plants with multiple 250 MW units are scheduled, as well as some 650 MW units. Previous plans by EEHC had been based on 750 MW plants, as multiples of 250 MW units. It is understood

27 Nuclear generation in Kenya was not included in the subsequent expansion plans as this option was not defined during the Inception or data gathering stage. It is understood that currently environmental assessment and preliminary site selection is underway 28 SPRU, University of Sussex and NERA Economic Consulting - The role of nuclear power in a low carbon economy – paper 4 - the economics of nuclear power, March 2006 29 World Nuclear Association – The economics of nuclear power - January 2010 30 Ministry of Mines and Energy, Investment opportunities in geothermal energy development in six selected geothermal prospects in Ethiopia,- project profiles, December 2008



that these combined cycle plants have a configuration of approximately 2x250 MW gas turbines and a 250 MW steam plant31. For these large combined cycle plants an average cost of 900 US$/kW has been assumed.

For the midsized combined cycle plants in the 180 MW range, as included in the Kenya and Uganda expansion plans, the configuration is approximately 2x60 MW of gas turbine and 1 x 60 MW of steam plant or 1 x 120 MW of gas turbine and 1x60 of steam plant. Three quotations obtained for the TANESCO PSMP, were in the range of 1050 to 1250 US$/kW at 2008 prices. Based on this and other sources, an average cost of 1200 US$/ kW, overnight, complete plant, at 2009 prices, has been selected.

Table 6-3 Comparative costs for Geothermal, OCGT and CCGT - 2009 $, no IDC Plant Type

Config. Fuel Total Cap. (MW)

Capital Cost (MUSD)

Year Escalationfactor

Cost 2009

Cost ($/kW)

Source

Geo 2x70

140 520 2008 100 520 3714 Kenya PSMP33 33 132 2009 100 132 4000 Uganda PB2x50 100 234 2005 110 257 2574 Ethiopia PB2x70 140 518 2009 100 518 3700 SNC TANESCO

OCGT 1x90 LFO 90 68 2008 100 68 756 Kenya PSMP1x60 60 100 2007 102 102 1700 Uganda PB3x50 NG 150 128 2009 100 128 853 SNC TANESCO1x25 25 19 2007 102 19 775 ESMAP/Romania1x150 150 69 2007 102 70 469 ESMAP/Romania

CCGT 3x60 LFO 180 221 2008 100 221 1228 Kenya PSMP1x185 185 419 2009 100 419 2265 Uganda PB2x70+50 NG 150 174 2005 110 191 1276 Ethiopia PB3x60 180 210 2009 100 210 1167 SNC TANESCO

140 155 2007 102 158 1129 ESMAP/Romania 580 411 2007 102 419 723 ESMAP/Romania

Diesel plants Unit costs for conventional diesel plant have been set as:

• Medium speed (LFO or gas) 1300 US$/kW

• Low speed (HFO) 2000 US$/kW

It may be noted that any diesel plants for Rwanda and Uganda would have to use LFO, due to transport constraints.

Lake Kivu methane fuelled engines The capital cost for the first methane gas fired plant has been stated as 325 MUS$ for the 100 MW plant to be developed by Contour Global32. This includes the gas gathering system, supply pipeline, the diesel generation plant, road access and development of port facilities at Kibuye. This yields an average cost of 3250 US$/kW. It is assumed that the infrastructure requirements for the second plant, the 200 MW to be developed by (or for supply to) a partnership of Rwanda, DRC and Burundi, would be similar, so the same unit cost is assumed.

Cogeneration Cogeneration plant in the region is assumed to be steam thermal burning biomass (bagasse). Given the small size of these plants, a relatively high unit cost of 2500 US$/kW

31 Mitsubishi Heavy Industries have provided for 2 GT units each to West Delta and East Delta Electricity Production Companies. These M701F units have a rating of about 270 MW and are the GT components for the 750 MW combined cycle plants at Sidi Krir and El Atf power stations 32 East Africa Business Week – November 2009



has been assumed as 75 % of the cost of a coal fired plant, noting that a biomass plant will include major fuel handling facilities.

Table 6-4 below is a summary table of all generic capital costs used in the present study for thermal power plants:

Table 6-4 Unit costs for Generic Thermal plants - 2009 $, no IDC Plant Type Fuel Type Unit Size (MW) 2009 Cost – No IDC ($/kW)

STPP

Coal

650 2000

150 2500

100 2800

Oil 135 1700

NG 650 1000

50 1700

Nuclear 1000 (Egypt) 3500

Geothermal 70 (Kenya) 3800

<50 (Ethiopia) 3000

OCGT NG / Oil Any 900

CCGT NG / Oil 250‐650 900

60‐120 1200

MSD LFO/NG Any 1300

LSD HFO Any 2000

6.1.2 Interest during construction Capital costs for thermal plants, as shown above, are based on overnight costs, i.e. without interest during construction. To obtain capitalized costs for the calculation of unit generation costs, IDC has been added. These are based on standardized assumed capital disbursement schedules during construction, by plant type, as shown below:

Table 6-5 Typical disbursement schedules during construction

CCGT GT Diesel Diesel Geo Coal Coal Oil Oil

180 60x2 LSD MSD 2x100 2x150 2x00 2x150

Years (nominal) 3 2 3 2 4 4 4 4 4

Year 4 13 20 20 5 5

Year 3 15 15 12 35 35 40 40

Year 2 50 60 50 60 45 30 30 40 40

Year 1 35 40 35 40 30 15 15 15 15

The corresponding increments for interest during construction, based on an interest rate of 10 %, are as follows:



Table 6-6 Interest during construction - typical increments for thermal plants

Type of plant Years of construction costs % of total cost

Coal STPP 4 24.4

Oil STPP 4 19.6

OCGT 2 11.1

CCGT 3 13.4

LSD 3 13.4

MSD 2 11.1

Geothermal 4 16.7

Cogeneration 3 13.4

Nuclear 5 26.3

The generic thermal power plants can therefore be summarized in the following table:

Table 6-7 Generic TPP Unit costs - $/kW with IDC

Type Fuel Type

Installed Capacity MW

Cost No IDC$/kW

Plant LifeYears

Construction Years

IDC %

Unit Cost $/kW

STPP

Coal

650 2000 25 4 24.4 2488

150 2500 25 4 24.4 3110

100 2800 25 4 24.4 3483

Oil 135 1700 25 4 19.6 2033

NG 650 1000 25 4 19.6 1196

50 1700 25 4 19.6 2033

Nuclear 1000 (Egypt) 3500 40 5 26.3 4420

Geothermal 70 (Kenya) 3800 25 4 16.7 4434

<50 (Ethiopia) 3000 25 4 16.7 3501

OCGT NG / Oil Any 900 20 2 11.1 1000

CCGT NG / Oil 250‐650 900 20 3 13.4 1020

60‐120 1200 20 3 13.4 1361

MSD LFO/NG Any 1300 20 2 11.1 1444

LSD HFO Any 2000 20 3 13.4 2268

6.2 Minimum lead times to on-power Total lead times to on-power will depend on the preparatory work required to define a project for approval. In the absence of specific information in source references the following lead times are used:



Table 6-8 Minimum on-power lead times for thermal plants Plant Type Project preparation Procurement / Construction Total

Coal STPP 3 3 6

Oil STPP 3 3 6

LSD / MSD 1 1 2

OCGT 2 1 3

CCGT 2 1 3

Geothermal 3 3 6

Cogeneration 3 3 6

Nuclear 5 6 11

6.3 Plant heat rates Plant heat rates are a function of the specific technology and the manufacturers’ process. For this study the following typical heat rates have been adopted33:

Table 6-9 Heat Rates for different Thermal Plants Plant type Heat rate (kJ/kWh)

Coal STPP 10,000

Oil STPP 10,500

OCGT 11,500

CCGT 7,900

LSD 7,900

MSD 8,000

Geothermal 20,700

Cogeneration 12,000

6.4 Fuel prices Fuel price projections are one of the key components of this study. Fuel prices directly impact the profitability of the interconnection between the different countries because high fossil fuel prices will increase the attractiveness of hydro plant with respect to thermal plant, while low fuel price might turn the interconnection non profitable. The fuel prices considered in this study reflect international prices in order to avoid internal distortions in each country related with subsidies or royalties.

6.4.1 Oil The oil prices for this study were taken from the import price of “Annual Energy Outlook 2010” (AEO2010) issued on April 2010 with projections to 2035. World oil prices can be influenced by a multitude of factors. Some tend to be short term, such as movements in exchange rates, financial markets, and weather, and some are longer term, such as expectations concerning future demand and production decisions by the Organization of the 33 heat rates were selected following review of values used in the TANESCO 2009 PSMP, the 2008 Kenya least cost plan, the Sudan 2007 master plan and the EAPMP study



Petroleum Exporting Countries (OPEC). In 2009, the interaction of market factors led prompt month contracts (contracts for the nearest traded month) for crude oil to rise relatively steadily from a January average of 41.68 US$/bbl to a December average of 74.47 US$/bbl.

Changes in the world oil market over the course of 2009 served to highlight the myriad factors driving future liquids demand and supply and how a change in these factors can reverberate through the world liquids market. Over the long term, world oil prices in EIA’s outlook are determined by four broad factors: (1) non-OPEC conventional liquids supply, (2) OPEC investment and production decisions, (3) unconventional liquids supply, and (4) world liquids demand. Uncertainty in long-term projections of world oil prices can be explained largely by uncertainty about one or more of these four broad factors.

Table 6-10 below shows the projections of the oil prices to 2038, for the last three years, the EIA forecast was extended using the rate of increase in 2035 over 2034.

Table 6-10 Oil price projections - 2038

Year Crude Oil US$/bbl IDO US$/L HFO US$/L

2013 78.9 0.592 0.567

2018 95.3 0.713 0.666

2023 101.6 0.763 0.704

2028 108.0 0.809 0.747

2033 117.0 0.872 0.805

2038 127.3 0.951 0.875

Levelized 96.7 0.722 0.675

Source: EIA long term forecast base scenario AEO2010

6.4.2 Natural Gas Figure 6-1 shows the evolution of NG prices for different regions. In 2009 and 2010 the prices returned around the same level of 2006.

Figure 6-1 Evolution of NG prices for different regions



While the oil market is fairly integrated at a global level, this is not the case for gas and coal which still show a strong regional spread. The main reason for these regional differentiations is the high transportation cost of gas and coal, relative to their production cost. Although the development of LNG transport facilities will introduce some degree of trade-off between regional gas markets the price differentials are not expected to fully disappear over the next 30 years.

Higher world oil prices are expected to result in a shift away from petroleum consumption and toward natural gas consumption in all sectors of the international energy market. In addition, some NG contract prices are tied directly to crude oil prices, putting further upward pressure on NG prices. Finally, higher oil prices are expected to promote increases in gas based production, which in turn would lead to more price pressure on world natural gas supplies.

Accordingly, natural gas prices are assumed broadly to follow the trend in oil prices, because of the continuing widespread use of oil-price indexation in long-term gas contracts and because of inter-fuel competition. For this study, considering the information provided by the countries natural gas will be significantly available for power plants only in Egypt.

For this regional master plan study, the price of natural gas will reflect international market prices. Table 6-11 below shows the most recent projections by the EU for the EU/African market and the projection of DOE/EIA for a hub in the US. For this study the EU projection will be used.

Table 6-11 NG price projections - 2038

Year NG‐EU US$/MMBTU NG‐EIA US$/MMBTU

2013 6.1 5.52018 6.5 5.82023 7.3 6.32028 7.9 6.82033 8.5 7.72038 9.3 8.3Levelized 6.9 6.1

6.4.3 Coal The coal price projection is based on the reference coal price used in the Tanzania PSMP 2009 updated with the latest trend reflected in the AEO 2010 projections. The reference price in 2007 was 65 US$/Mt plus $10 for transportation and $5 for handling charge, to provide a total estimated cost of 80 US$/Mt. Table 6-12 shows the forecast for the period 2013-2038:

Table 6-12 Coal price projections - 2038

Year COAL US$/Mt

2013 80.0 2018 74.3 2023 73.7 2028 74.1 2033 75.8 2038 78.6 Levelized 75.0



6.4.4 Geothermal The geothermal price is based on actual geothermal plant operations in Central American countries. The price used is: 0.725 $/GJ. This comes from the following:

1 kg of geothermal steam has a calorific content of 660 kcal/kg. That is equivalent to 2.7615 GJ/Mt (Metric Ton). With the price of geothermal steam at 2 $/Mt, we get the geothermal fuel price: 0.725 $/GJ

We assume that this price is maintained throughout the study horizon.

6.4.5 Net calorific value The net calorific value is the quantity of heat liberated by the complete combustion of a unit of fuel when the vapour produced is assumed to remain as a vapour and the heat is not recovered. The net calorific value is a key parameter to determine the specific cost of fuel. The following table presents default values used in this study:

Table 6-13 Typical net calorific values

Fuel Net Calorific Value Unit

HFO 6.15 GJ/bbl Diesel 6.63 GJ/bbl NG 38.30 GJ/103m3

Coal 22.20 GJ/Mt Geo 2.76 GJ/Mt

6.4.6 Fuel forecast Table 6-14 and Figure 6-2 show the annual projections for the fuels price in physical units and energy units:



Table 6-14 Fuel Forecast

Year Crude Oil 1 IDO 1 HFO 1 Coal 2 NG* $/GJ

$/bbl Incr (%) $/lt Incr (%) US$/lt Incr (%) US$/Mt Incr (%) US$/m3 Incr (%) IDO HFO Coal NG‐EU* NG‐EIA**2013 78.9 0.6 0.6 80.0 0.2 15.3 13.6 3.6 6.5 5.8 2014 83.6 6.0 0.6 4.2 0.6 5.1 74.2 ‐7.2 0.2 0.0 16.0 14.3 3.3 6.5 5.8 2015 86.6 3.6 0.6 2.8 0.6 2.8 74.9 0.9 0.2 0.0 16.4 14.7 3.4 6.5 5.9 2016 89.8 3.7 0.7 5.0 0.6 2.6 74.4 ‐0.7 0.3 1.8 17.2 15.1 3.3 6.6 6.0 2017 92.5 2.9 0.7 3.6 0.6 3.3 74.6 0.2 0.3 1.8 17.8 15.6 3.4 6.7 6.1 2018 95.3 3.1 0.7 3.4 0.7 2.6 74.3 ‐0.3 0.3 1.8 18.4 16.0 3.3 6.8 6.1 2019 96.6 1.4 0.7 2.1 0.7 1.5 74.1 ‐0.3 0.3 1.8 18.8 16.2 3.3 6.9 6.2 2020 97.9 1.3 0.7 1.6 0.7 0.5 74.1 ‐0.1 0.3 1.8 19.1 16.3 3.3 7.1 6.3 2021 99.0 1.2 0.7 0.7 0.7 1.5 73.8 ‐0.4 0.3 3.0 19.3 16.5 3.3 7.3 6.4 2022 100.2 1.2 0.8 0.9 0.7 0.9 73.9 0.1 0.3 3.0 19.4 16.7 3.3 7.5 6.6 2023 101.6 1.4 0.8 1.5 0.7 1.3 73.7 ‐0.2 0.3 3.0 19.7 16.9 3.3 7.7 6.6 2024 102.8 1.2 0.8 0.9 0.7 1.3 73.7 0.0 0.3 3.0 19.9 17.1 3.3 7.9 6.6 2025 104.2 1.3 0.8 1.3 0.7 1.2 73.4 ‐0.4 0.3 3.0 20.2 17.3 3.3 8.2 6.6 2026 105.0 0.8 0.8 1.2 0.7 0.4 73.9 0.6 0.3 0.7 20.4 17.4 3.3 8.2 6.8 2027 106.5 1.4 0.8 1.1 0.7 1.6 73.7 ‐0.2 0.3 0.7 20.6 17.7 3.3 8.3 6.9 2028 108.0 1.4 0.8 1.4 0.7 1.4 74.1 0.5 0.3 0.7 20.9 17.9 3.3 8.4 7.1 2029 109.9 1.8 0.8 1.8 0.8 1.6 74.5 0.5 0.3 0.7 21.3 18.2 3.3 8.4 7.4 2030 111.2 1.1 0.8 0.8 0.8 1.6 74.7 0.3 0.3 0.7 21.5 18.5 3.4 8.5 7.6 2031 113.4 2.0 0.8 1.9 0.8 1.8 75.2 0.7 0.3 1.8 21.9 18.8 3.4 8.6 8.0 2032 115.2 1.6 0.9 1.7 0.8 1.5 75.5 0.4 0.3 1.8 22.2 19.1 3.4 8.8 8.1 2033 117.0 1.6 0.9 1.4 0.8 1.2 75.8 0.4 0.3 1.8 22.6 19.3 3.4 8.9 8.1 2034 119.0 1.7 0.9 1.7 0.8 1.7 76.3 0.7 0.3 1.8 22.9 19.6 3.4 9.1 8.3 2035 121.0 1.7 0.9 1.8 0.8 1.7 76.9 0.7 0.4 1.8 23.3 20.0 3.5 9.3 8.4 2036 123.1 1.7 0.9 1.8 0.8 1.7 77.4 0.7 0.4 1.8 23.8 20.3 3.5 9.4 8.5 2037 125.2 1.7 0.9 1.8 0.9 1.7 78.0 0.7 0.4 1.8 24.2 20.6 3.5 9.6 8.7 2038 127.3 1.7 1.0 1.8 0.9 1.7 78.6 0.7 0.4 1.8 24.6 21.0 3.5 9.8 8.8

Levelized 96.7 1.9 0.7 1.9 0.7 1.8 75.0 ‐0.1 0.3 1.7 18.7 16.2 3.4 7.3 6.5 1 From EIA long term forecast – AEO 2010 2 First year from Tanzania Master Plan August 2009. Annual adjustment from EIA forecast electric power

* From ENPTPS: June 2007 adjusted to 2009 prices. Main source European Commission ** From EIA long term forecast – AEO 2010. Henry Hub Prices



Figure 6-2 Fuel forecast

6.5 Future thermal generation costs The supply-demand analyses generally reflect the ordering of new plant provided in country master plans. However these in most cases cover short term and midterm planning periods, as compared with the planning horizon up to 2038 used in this current study. Additionally some of the timing of future projects may be affected by the minimum lead times being used in this study. Consequently the preparation of preliminary alternative generation plans for the demand supply analyses also uses comparative costs for alternative thermal technologies. These are presented in Table 6-15 below and show generation costs as a function of plant capacity factor. Project generation costs are shown on a country by country basis.

The unit cost of generation is based on:

Fixed component • Amortization of capitalized amount

• Interim replacement

• Insurance

• Fixed operation and maintenance

Annual costs • Fuel cost

• Variable operation and maintenance

The parameters used to calculate the unit costs are provided in Section 3, apart from the fuel costs given in Section 6.4 above, and the plant heat rates from Section 6.3.

The relative contribution of fixed costs (primarily capital) and variable cost (primarily fuel) varies considerably throughout the EAPP region, with plant size and type being the main factors. Illustrative costs are compared below in Table 6-15:



Table 6-15 Illustrative future unit generation costs in c/kWh, based on 75% CF

Country Type Capacity (MW)

Capital cost with

IDC ($/kW)

Fixed cost

c/kWh

Variable cost

c/kWh

Total cost

c/kWh

Fixed cost %

Variable cost %

Egypt STPP ‐ NG 1300 1196 2.57 1.82 3.47 59% 41%

CCGT ‐ NG 1000 1021 2.04 1.43 3.47 59% 41%

Nuclear 1000 4430 8.44 0.96 9.40 90% 10%

Ethiopia Geothermal 75/100 3503 6.73 1.75 8.48 79% 21%

Kenya Geothermal 140 4437 8.38 1.75 10.13 83% 17%

STPP ‐ coal

(Richards Bay) 300 2919 5.92 5.05 10.97 54% 46%

Rwanda Diesel/Methane 100 3613 6.69 2.05 8.74

Sudan STPP ‐ Crude 250 2034 4.05 9.38 13.43 77% 23%

Tanzania STPP ‐ Coal 400 3482 6.77 2.65 9.42 30% 70%

OCGT ‐ NG 240 1001 2.03 5.10 7.13 72% 28%

Uganda CCGT ‐ Gasoil 185 1361 2.68 21.73 24.41 28% 72%

STPP ‐ HFO 60 2034 4.13 14.27 18.90 11% 89%



Table 6-16 Thermal generation costs by country

NAME Type

Generation Capital Cost Fixed Costs / Year Variable cost c/kWh Total Unit Cost c/kWh

Inst Cap MW

Fuel Life Yr Yr GWh Const Yr

2009 Cost $/kW

IDC % Total Cost $/kW

Fixed Annual Cost $/kW

Insur Inter Repl (%)

Fixed O&M $/kW

Total Fixed Cost $/kW

O&M Fuel Cost

Total

Plant Factor %

25 50 75

hrs / Year

2190 4380 6570

BURUNDI

EAST DRC

EGYPT

Qassasen CCGT 1,250 NG 20 8760 3 900 19.6 1021 120 0.60 8 134 0.40 1.03 1.43 7.5 4.5 3.5

Qassasen CCGT 250 NG 20 1752 3 900 19.6 1021 120 0.60 8 134 0.40 1.03 1.43 7.5 4.5 3.5

Giza North CCGT 1,000 NG 20 7008 3 900 19.6 1021 120 0.60 8 134 0.40 1.03 1.43 7.5 4.5 3.5

Giza North CCGT 500 NG 20 3504 3 900 19.6 1021 120 0.60 8 134 0.40 1.03 1.43 7.5 4.5 3.5

Damietta West 1 CCGT 1,500 NG 20 10512 3 900 19.6 1021 120 0.60 8 134 0.40 1.03 1.43 7.5 4.5 3.5

Damietta West 2 CCGT 1,500 NG 20 10512 3 900 26.6 1021 120 0.60 8 134 0.40 1.03 1.43 7.5 4.5 3.5

Combined cycle CCGT 8,250 NG 20 57816 3 900 19.6 1021 120 0.60 8 134 0.40 1.03 1.43 7.5 4.5 3.5

Ain Sokhna STPP 1,300 NG 25 9110 4 1000 19.6 1196 132 0.60 30 169 0.45 1.37 1.82 9.5 5.7 4.4

Suez STPP 650 NG 25 4555 4 1000 19.6 1196 132 0.60 30 169 0.45 1.37 1.82 9.5 5.7 4.4

Helwan south STPP 1,300 NG 25 9110 4 1000 19.6 1196 132 0.60 30 169 0.45 1.37 1.82 9.5 5.7 4.4

Helwan south STPP 1,300 NG 25 9110 4 1000 19.6 1196 132 0.60 30 169 0.45 1.37 1.82 9.5 5.7 4.4

Qena STPP 650 NG 25 4555 4 1000 26.6 1196 132 0.60 30 169 0.45 1.37 1.82 9.5 5.7 4.4

Qena STPP 650 NG 25 4555 4 1000 19.6 1196 132 0.60 30 169 0.45 1.37 1.82 9.5 5.7 4.4

Safaga STPP 1,300 NG 25 9110 4 1000 19.6 1196 132 0.60 30 169 0.45 1.37 1.82 9.5 5.7 4.4

Steam 650 MW STPP 16,250 NG 25 113880 4 1000 19.6 1196 132 0.60 30 169 0.45 1.37 1.82 9.5 5.7 4.4

Dabaa nuclear Nuclear 5,000 U 40 39420 5 3500 19.6 4430 453 0.60 75 555 0 0.96 0.96 26.3 13.6 9.4

ETHIOPIA

Aluto.Langano Geo 75 Heat 25 526 4 3000 16.8 3503 386 0.60 35 442 0.25 1.50 1.75 21.9 11.8 8.5

Tendaho Geo 100 Heat 25 701 4 3000 16.8 3503 386 0.60 35 442 0.25 1.50 1.75 21.9 11.8 8.5

Corbetti Geo 75 Heat 25 526 4 3000 16.8 3503 386 0.60 35 442 0.25 1.50 1.75 21.9 11.8 8.5

Abaya Geo 100 Heat 25 701 4 3000 16.8 3503 386 0.60 35 442 0.25 1.50 1.75 21.9 11.8 8.5

Tulu Moye Geo 40 Heat 25 280 4 3000 16.8 3503 386 0.60 35 442 0.25 1.50 1.75 21.9 11.8 8.5

Dofan Fantale Geo 60 Heat 25 420 4 3000 16.8 3503 386 0.60 35 442 0.25 1.50 1.75 21.9 11.8 8.5



NAME Type


Inst Cap MW


2009 Cost $/kW




Fixed O&M $/kW


O&M Fuel Cost

Total

Plant Factor %

25 50 75

hrs / Year

2190 4380 6570

KENYA

Olkaria ext Geo 35 Heat 25 245 3 3800 13.4 4310 475 0.60 35 536 0.25 1.50 1.75 26.2 14.0 9.9

Longonot Geo 140 Heat 25 981 4 3800 16.8 4437 489 0.60 35 550 0.25 1.50 1.75 26.9 14.3 10.1

Suswa Geo 140 Heat 25 981 4 3800 16.8 4437 489 0.60 35 550 0.25 1.50 1.75 26.9 14.3 10.1

Menengai Geo 140 Heat 25 981 4 3800 16.8 4437 489 0.60 35 550 0.25 1.50 1.75 26.9 14.3 10.1

North Rift Geo 70 Heat 25 491 4 3800 16.8 4437 489 0.60 35 550 0.25 1.50 1.75 26.9 14.3 10.1 Other geothermal (multiple)

Geo 140 Heat 25 981 4 3800 16.8 4437 489 0.60 35 550 0.25 1.50 1.75 26.9 14.3 10.1

Mombasa (multiple)

STPP 300 Coal 25 2102 4 2500 24.4 3110 343 0.60 50 411 0.65 4.40 5.05 23.8 14.4 11.3

RWANDA

Biomas peat cogen

STPP 50 Biom 25 329 3 2500 13.4 2836 312 0.60 40 369 0.60 2.40 3.00 19.9 11.4 8.6

Kivu gas plant 1 Diesel 100 Meth 25 657 2 3250 11.2 3613 398 0.60 20 440 1.20 0.85 2.05 22.1 12.1 8.7

Kivu gas plant 2 Diesel 200 Meth 25 1314 2 3250 11.2 3613 398 0.60 20 440 1.20 0.85 2.05 22.1 12.1 8.7

Generic diesel Diesel 50 LFO 20 329 2 1300 11.2 1445 170 0.60 40 218 1.00 20.64 21.64 31.6 26.6 25.0

SUDAN

Crude fired 238 MW units

STPP 476 Crude 25 3336 4 1700 19.6 2034 224 0.60 30 266 0.45 8.93 9.38 21.5 15.5 13.4

Crude fired 475 MW units

STPP 1425 Crude 25 9986 4 1700 19.6 2034 224 0.60 30 266 0.45 8.93 9.38 21.5 15.5 13.4

CCGT 208 MW ‐ gas oil

CCGT 624 gas oil 25 4373 3 900 13.4 1021 112 0.60 8 127 0.40 9.09 9.49 15.3 12.4 11.4


CCGT 1368 gas oil 25 9587 3 900 13.4 1021 112 0.60 8 127 0.40 9.09 9.49 15.3 12.4 11.4


CCGT 1832 gas oil 25 12839 3 900 13.4 1021 112 0.60 8 127 0.40 9.09 9.49 15.3 12.4 11.4

TANZANIA

Kiwira STPP 200 Coal 25 1402 4 2800 24.4 3483 384 0.60 40 445 0.65 2.00 2.65 23.0 12.8 9.4



NAME Type


Inst Cap MW


2009 Cost $/kW




Fixed O&M $/kW


O&M Fuel Cost

Total

Plant Factor %

25 50 75

hrs / Year

2190 4380 6570

Mchuchuma STPP 400 Coal 25 2803 4 2800 24.4 3483 384 0.60 40 445 0.65 2.00 2.65 23.0 12.8 9.4

Ngaka STPP 400 Coal 25 2803 4 2800 24.4 3483 384 0.60 40 445 0.65 2.00 2.65 23.0 12.8 9.4

Nyasa STPP 200 Coal 25 1402 4 2800 24.4 3483 384 0.60 40 445 0.65 2.00 2.65 23.0 12.8 9.4

Kinyerezi OCGT 240 NG 20 1682 2 900 11.2 1001 118 0.60 10 134 0.50 4.60 5.10 11.2 8.1 7.1

Mnazi OCGT 300 NG 20 2102 2 900 11.2 1001 118 0.60 10 134 0.50 4.60 5.10 11.2 8.1 7.1

Generic diesel Diesel 50 LFO 20 350 2 1300 11.2 1445 170 0.60 40 218 1.00 18.29 19.29 29.3 24.3 22.6

UGANDA

Kampala steam STPP 56 Coal 25 392 4 2800 24.4 3483 384 0.60 70 475 0.66 4.40 5.06 26.7 15.9 12.3

Tullow steam STPP 53 HFO 25 371 4 1700 19.6 2034 224 0.60 35 271 0.45 14.32 14.77 27.2 21.0 18.9

Tullow GT OCGT 57 gas oil 20 399 2 900 11.2 1001 118 0.60 10 134 0.50 31.05 31.55 37.6 34.6 33.6

Tullow CCGT CCGT 185 gas oil 20 1296 3 1200 13.4 1361 160 0.60 8 176 0.40 21.33 21.73 29.8 25.7 24.4

Tullow diesel Diesel 10 HFO 25 66 2 2000 11.2 2223 245 0.60 40 298 1.00 21.60 22.60 36.2 29.4 27.1

Geothermal Geo 33 Heat 25 217 4 1500 16.8 1751 193 0.60 35 238 0.45 1.50 1.95 12.8 7.4 5.6



6.6 Thermal plant retirements For future thermal additions (after 2013) retirement dates will be based directly on the service lives shown in the planning criteria.

For existing plant the same procedure will be followed, however with the exception that for any project where the on power year was not available, year 2000 was used (i.e. resulting in about 50 % of the plant life by 2013). On power dates were generally taken from previous country master plans.

The list of retirement dates for existing and committed thermal is shown in Table 6-17 below.

Table 6-17 Existing and committed thermal retirements

Name

Generation Retirements

Inst. Cap MW

Plant Type Fuel Type Plant Life Years

Max Plant Factor %

Max Energy GWh

On Power Year

Retirement Year

BURUNDIBujumbura diesel 6 diesel LFO 20 75 36 1998 2018

EAST DRCSNEL 18 diesel LFO 20 75 116 2000 2020Other 22 diesel LFO 20 75 141 2000 2020

EGYPTShoubra El Kheima 1260 Steam NG/HFO 25 80 8830 1988 2013Cairo West 350 Steam NG/HFO 25 80 2453 1979 2004Caire West Ext 660 Steam NG/HFO 25 80 4625 1995 2020Cairo South I 570 CCGT NG/HFO 20 80 3995 1989 2009Cairo South II 165 CCGT NG/HFO 20 80 1156 1995 2015Cairo North 1500 CCGT NG/LFO 20 80 10512 2008 2028Wadi Hof 100 GT NG/LFO 20 80 701 1985 2005Damietta 1200 CCGT NG/LFO 20 80 8410 1993 2013Ataka 900 Steam NG/HFO 25 80 6307 1987 2012Abu Sultan 600 Steam NG/HFO 25 80 4205 1986 2011Shahab 100 GT NG/LFO 20 80 701 1982 2002Port Said 73 GT NG/LFO 20 80 512 1984 2004Arish 66 Steam NG/HFO 25 80 463 2000 2025Oyoun Mousa 640 Steam NG/HFO 25 80 4485 2000 2025Sharm el Sheik 178 GT LFO 20 80 1247 2000 2020Hurghada 143 GT LFO 20 80 1002 2000 2020Suez Gulf 683 Steam NG/HFO 25 80 4786 2002 2027Port Said East 683 GT NG/HFO 20 80 4786 2003 2023Talkha 290 CCGT NG/LFO 20 80 2032 1989 2009Talkha 210 420 Steam NG/HFO 25 80 2943 1995 2020Talkha 750 750 CCGT NG/LFO 20 80 5256 2008 2028Nubaria 1500 CCGT NG/LFO 20 80 10512 2006 2026Mahmoudia 316 CCGT NG/LFO 20 80 2215 1995 2015Mahmoudia 75 GT NG/LFO 20 80 526 1982 2002Kafr El‐Dawar 440 Steam NG/HFO 25 80 3084 1986 2011Damanhour Ext 300 Steam NG/HFO 25 80 2102 1991 2016Damanhour Old 195 Steam NG/HFO 25 80 1367 1969 1994Damanhour 157 CCGT NG/LFO 20 80 1100 1995 2015El‐Seiuf 200 Steam NG/LFO 25 80 1402 1984 2009



Name


Inst. Cap MW


Max Plant Factor %

Max Energy GWh

On Power Year

Retirement Year

El‐Seiuf 113 GT HFO 20 80 792 1969 1989Karrmouz 23 GT LFO 20 80 161 1980 2000Abu Kir 911 Steam NG/HFO 25 80 6384 1991 2016Abu Kir 24 GT NG/LFO 20 80 168 1983 2003Sidi Krir 1.2 640 Steam NG/HFO 25 80 4485 2000 2025Matrouh 60 Steam NG/HFO 25 80 420 1990 2015Sidi Krir 3.4 683 Steam NG/HFO 25 80 4786 2002 2027Walidia 624 Steam HFO 25 80 4373 1997 2022Kunemat 1 1254 Steam NG/HFO 25 80 8788 1999 2024Kunemat 2 500 CCGT NG/LFO 20 80 3504 2007 2027Assiut 90 Steam HFO 25 80 631 1967 1992Atfe 750 CCGT NG/HFO 20 80 5256 2009 2029Nubaria 3 750 CCGT NG/HFO 20 80 5256 2009 2029Wind Zarafana 305 Wind 20 50 1336 2008 2028Solar Kurimat 140 Wind 20 50 613 2009 2029

ETHIOPIADire Dawa 44 diesel HFO 20 75 289 2004 2024Awash 7 25 diesel HFO 20 75 164 2003 2023Kaliti 14 diesel HFO 20 75 92 2003 2023Aluto 7 geo 25 80 49 2007 2032Small diesel 57 diesel HFO 20 75 374 1975 1995

KENYAKipevu 75 diesel HFO 20 75 493 1999 2019Kipevu new GT 60 GT 20 80 420 1999 2019Nairobi Fiat 13 diesel LRO 20 75 85 2008Olkaria 1 45 geo 25 80 315 1981 2010Olkaria 2 70 geo 25 80 491 2003 2028Olkaria 3 13 geo 25 80 91 2000 2025Olbkaria 3 b 35 geo 25 80 245 2008 2033Iberafrica IPP 56 diesel HFO 20 75 368 2000 2019Tsavo IPP 74 diesel HFO 20 75 486 2001 2021Cogen IPP 26 cogen Bagasse 25 75 171 2008 2025Agrekko EPP 150 diesel LRO 20 75 986 2000 2013

RWANDAGatsata 2 diesel LFO 20 75 13 1975 1995Jabana diesel 8 diesel LFO 20 75 51 2000 2020Mukungwa diesel 5 diesel LFO 20 75 30 2006 2026New diesel 20 diesel HFO 20 75 131 2009 2029RIG Kivu gas plant 5 diesel methane 20 75 30 2007 2027

SUDANDr Sharif 1 60 Steam NG 25 80 420 1985 2010Dr. Sharif 2 120 Steam NG 25 80 841 1994 2019Khartoum North 50 GT NG 20 80 350 1992 2012Khartoum North 160 Steam NG 25 80 1121 2000 2025Khartoum North 200 Steam NG 25 80 1402 2008 2033Kuku 25 GT NG 20 80 175 1985 2005Garri 450 CCGT NG 20 80 3154 2003 2023



Name


Inst. Cap MW


Max Plant Factor %

Max Energy GWh

On Power Year

Retirement Year

Garri 80 Steam NG 25 80 561 2008 2033Kilo 40 GT NG 20 80 280 2007 2027El Fau 13 Diesel NG 20 75 85 2003 2023Atbara 13 Diesel NG 20 75 88 2003 2023Kassala 12 Diesel NG 20 75 76 1982 2002Kassal 1‐5 50 Diesel NG 20 75 329 2007 2027Port Sudan 1‐3 405 Steam NG 25 80 2838 2009 2034Kosti 1&2 250 Steam NG 25 80 1752 2009 2034El Bagair 1&2 270 Steam NG 25 80 1892 2009 2034Al Fula 1&2 270 Steam NG 25 80 1892 2009 2034Girba 7 Diesel NG 20 75 46 1983 2003

TANZANIASongas 1 42.0 GT NG 20 80 294 2004 2024Songas 2 120.0 GT NG 20 80 841 2005 2025Songas 3 40.0 GT NG 20 80 280 2006 2026Ubungo GT 102.0 GT NG 20 80 715 2007 2027Tegeta IPTL 100.0 diesel HFO 20 75 657 2002 2022

UGANDAKakira 17.0 Cogen Bagasse 25 75 112 2008 2039Namanve 50.0 Diesel HFO 20 75 329 2008 2027Invespro HFO IPP 50.0 Diesel HFO 20 75 329 2010 2015



7 IDENTIFICATION OF POTENTIAL REGIONAL PROJECTS The concept of the regional project is that the project could be part of a regional supply, at least for a few years. In this context it is noted that all countries except for Ethiopia and Egypt will exhaust all their identified indigenous resources before the end of the planning period in 2038. However larger projects could be important contributors to regional supply for a number of years.

The criterion used at this preliminary stage for the identification of potential regional projects has been to compare project size with country load growth. Specifically, plant capacity has been compared with (preliminary) load growth estimates for 2030, and where project size is more than 2 years of load growth, the project is classified as a potential regional project. As load forecast growth varies around 6-9% / year, a uniform criterion of 15% of the 2030 preliminary load forecast has been used. This process primarily covers new hydro options, however the same criteria has been applied in reviewing larger thermal proposed additions.

Country 2030 Load (MW) 15 % of 2030 load (MW) Plant Type MW Burundi 385 58 Siguvyaye hydro 90

Eastern DRC 179 27

Ruzizi III hydro 145 Ruzizi IV hydro 287 Wannie Rukula hydro 688 Piana Mwanga hydro 29 Bengamisa hydro 48 Babeda I hydro 50 Semliki hydro 28 Bendera hydro 43 Mugomba Hydro 40

Egypt 69,909 10,486

Ethiopia 8,464 1,270

Beko Abo hydro 2100 Mandaya hydro 2000 Gibe III hydro 1870 Karadobi Hydro 1600 Border hydro 1200 Gibe IV hydro 1468

Kenya 7,795 1170

Rwanda 484 73 Kivu gas Plant 1 diesel 100 Kivu gas Plant 2 diesel 200

Sudan 11,054 1,658 Tanzania 3,770 565 Stieglers Gorge hydro 1200

Uganda 1,898 285 Karuma hydro 700 Ayago hydro 550 Murchison Falls hydro 750

The generation projects identified in the previous table will be further analyzed in the regional plan (WBS 1300) These projects, whenever their earliest on-power date allows, will be assessed on earlier dates than in the national plans. This will allow identifying the potential additional net benefits (savings minus additional costs of advancing the project) to the whole EAPP region.

Certain “shared” projects are attributed to one country, as follows:

• Kivu methane plants – Rwanda

• Ruzizi hydro plants – Eastern DRC



The Border project is included as it would be developed as part of the Blue Nile cascade, and because Ethiopia has a large number of midsized hydro sites that would also provide export potential.

Egypt is including nuclear 1000 MW plants in its program, and certainly would have an export potential from gas fired plants or by pre-building nuclear for export.

Draft Master Plan Report WBS 1300 Supply Demand Analysis February 2011 & Project Identification


WBS 1300 Supply-Demand Analysis and Project Identification

Final Master Plan Report i WBS 1300 Supply Demand Analysis May 2011 & Project Identification


TABLE OF CONTENTS 1 OBJECTIVE AND SCOPE ....................................................................................... 1-1 1.1 Inputs ........................................................................................................................ 1-1 1.2 Tools ......................................................................................................................... 1-1 1.2.1 OPTGEN ............................................................................................................... 1-2 1.2.2 SDDP ..................................................................................................................... 1-3 1.3 Methodology .............................................................................................................. 1-3 1.4 Main Results ............................................................................................................. 1-6

2 DEMAND FORECAST .............................................................................................. 2-1 2.1 Demand Scenarios .................................................................................................... 2-1 2.1.1 Selecting the adequate scenario ........................................................................... 2-1 2.1.2 Summary of forecast results .................................................................................. 2-2 2.2 Demand Forecast in SDDP Format .......................................................................... 2-6

3 STUDY DATABASE ................................................................................................. 3-1 3.1 Data required by SDDP ............................................................................................. 3-1 3.1.1 Thermal, Wind and Solar Plants ............................................................................ 3-1 3.1.2 Hydro Plants .......................................................................................................... 3-2 3.1.3 Fuels ...................................................................................................................... 3-2 3.1.4 Demand Forecast .................................................................................................. 3-2 3.2 Data Required for OptGen ........................................................................................ 3-3 3.3 References ................................................................................................................ 3-3

4 NATIONAL EXPANSION PLANS ............................................................................ 4-1 4.1 Tanzania ................................................................................................................... 4-1 4.1.1 Existing national expansion plan ........................................................................... 4-1 4.1.2 Modified national expansion plan .......................................................................... 4-2 4.1.3 Existing Vs. Modified national expansion plan ...................................................... 4-3 4.1.4 Investment net present value ................................................................................ 4-5 4.1.5 Interconnections and energy generation ............................................................... 4-5 4.2 Kenya ........................................................................................................................ 4-7 4.2.1 Existing national expansion plan ........................................................................... 4-7 4.2.2 Modified national expansion plan .......................................................................... 4-8 4.2.3 Existing Vs. Modified national expansion plan ...................................................... 4-9 4.2.4 Investment net present value .............................................................................. 4-11 4.2.5 Interconnections and energy generation ............................................................. 4-11 4.3 Uganda .................................................................................................................... 4-12 4.3.1 Existing national expansion plan ......................................................................... 4-12 4.3.2 Modified national expansion plan ........................................................................ 4-13 4.3.3 Existing Vs. Modified national expansion plan .................................................... 4-15 4.3.4 Investment net present value .............................................................................. 4-16 4.3.5 Interconnections and energy generation ............................................................. 4-16 4.4 Ethiopia ................................................................................................................... 4-18 4.4.1 Existing national expansion plan ......................................................................... 4-18 4.4.2 Modified national expansion plan ........................................................................ 4-19 4.4.3 Existing Vs. Modified national expansion plan .................................................... 4-20 4.4.4 Investment net present value .............................................................................. 4-22 4.4.5 Interconnections and energy generation ............................................................. 4-22 4.5 Sudan ...................................................................................................................... 4-23 4.5.1 Existing national expansion plan ......................................................................... 4-23

Final Master Plan Report ii WBS 1300 Supply Demand Analysis May 2011 & Project Identification


4.5.2 Modified national expansion plan ........................................................................ 4-25 4.5.3 Existing Vs. Modified national expansion plan .................................................... 4-26 4.5.4 Investment net present value .............................................................................. 4-28 4.5.5 Interconnections and energy generation ............................................................. 4-28 4.6 Egypt ....................................................................................................................... 4-29 4.6.1 Existing national expansion plan ......................................................................... 4-29 4.6.2 Modified national expansion plan ........................................................................ 4-31 4.6.3 Existing Vs. Modified national expansion plan .................................................... 4-32 4.6.4 Investment net present value .............................................................................. 4-34 4.6.5 Interconnections and energy generation ............................................................. 4-34 4.7 Burundi, Eastern DRC and Rwanda ....................................................................... 4-36 4.7.1 Regional coordination .......................................................................................... 4-36 4.7.2 Shared Projects ................................................................................................... 4-36 4.7.3 New national expansion plans ............................................................................. 4-37 4.7.4 Investment Net Present Value ............................................................................. 4-41 4.7.5 Interconnections and energy generation ............................................................. 4-41 4.8 Djibouti .................................................................................................................... 4-46 4.8.1 Existing national expansion plan ......................................................................... 4-46 4.8.2 Additional 3-year Period ...................................................................................... 4-47 4.8.3 Investment net present value .............................................................................. 4-48 4.8.4 Interconnections and energy generation ............................................................. 4-48

5 REGIONAL SUPPLY-DEMAND ANALYSIS ............................................................ 5-1 5.1 Introduction ............................................................................................................... 5-1 5.2 Proposed Interconnections projects .......................................................................... 5-2 5.3 National Generation Plans and Regional Interconnection Plans (NGP_RIP) ........... 5-4 5.4 Regional Generation and Interconnection Plans (RGP_RIP) ................................... 5-9 5.5 Sensitivity analysis .................................................................................................. 5-12 5.5.1 National Generation Plans ................................................................................... 5-12 5.5.2 Regional Generation Plans .................................................................................. 5-13 5.6 Benefit-Cost analysis .............................................................................................. 5-14

6 IDENTIFIED PROJECTS FOR FURTHER ANALYSIS IN PHASE II ....................... 6-1 6.1 Generation projects ................................................................................................... 6-1 6.2 Interconnection Projects ............................................................................................ 6-2

Final Master Plan Report iii WBS 1300 Supply Demand Analysis May 2011 & Project Identification


LIST OF TABLES Table 1-1 OPTGEN typical inputs/outputs ...................................................................... 1-3 Table 1-2 SDDP typical inputs/outputs ........................................................................... 1-3 Table 1-3 Annual Average Potential Surplus by Country ............................................... 1-6 Table 2-1 Demand Forecast Scenarios Selected ........................................................... 2-1 Table 2-2 Demand Forecast Chosen Scenarios - Peak Demand and Generated Energy .. ....................................................................................................................... 2-2 Table 4-1 Tanzania Existing Vs. Modified National Expansion Plan .............................. 4-4 Table 4-2 Kenya Existing Vs. Modified National Expansion Plan ................................... 4-9 Table 4-3 Uganda Existing Vs. Modified National Expansion Plan .............................. 4-15 Table 4-4 Ethiopia Existing Vs. Modified National Expansion Plan .............................. 4-21 Table 4-5 Sudan Existing Vs. Modified National Expansion Plan ................................ 4-27 Table 4-6 Egypt Existing Vs. Modified National Expansion Plan .................................. 4-32 Table 4-7 Burundi New National Expansion Plan ......................................................... 4-40 Table 4-8 Eastern DRC New National Expansion Plan ................................................ 4-40 Table 4-9 Rwanda New National Expansion Plan ........................................................ 4-41 Table 4-10 2013 Investment NPV for Burundi, Eastern DRC and Rwanda ................... 4-41 Table 4-11 Djibouti Existing National Expansion Plan .................................................... 4-47 Table 5-1 Definition and description of the scenarios analyzed ..................................... 5-2 Table 5-2 Interconnection Projects ................................................................................. 5-3 Table 5-3 Generation capacity displaced or advanced Case RGP_RIP ........................ 5-9 Table 5-4 Schedule of the interconnection projects selected Cases RGP_RIP and

NGP_RIP ...................................................................................................... 5-12 Table 5-5 Schedule of the interconnection projects selected Cases NGP_RIP (Base, S1,

S2) ................................................................................................................ 5-13 Table 5-6 Schedule of the interconnection projects selected Cases RGP_RIP (Base, S1,

S2) ................................................................................................................ 5-14 Table 5-7 Benefit-Cost Analysis Present Values in MUS$ ........................................... 5-15 Table 6-1 Identified Generation Projects for Phase II ..................................................... 6-1 Table 6-2 Identified Interconnection Projects for Phase II .............................................. 6-2

Final Master Plan Report iv WBS 1300 Supply Demand Analysis May 2011 & Project Identification


LIST OF FIGURES

Figure 1-1 OPTGEN investment and operation coordination 1-2 Figure 1-2 Methodology for developing regional plans 1-5 Figure 2-1 Peak Demand Forecasts - Burundi, Djibouti, Eastern DRC and Rwanda 2-5 Figure 2-2 Peak Demand Forecasts - Ethiopia, Kenya, Sudan, Tanzania and Uganda 2-5 Figure 2-3 Peak Demand Forecasts - Egypt 2-6 Figure 4-1 Tanzania Existing National Expansion Plan by Plant Category 4-2 Figure 4-2 Tanzania Modified National Expansion Plan by Plant Category 4-3 Figure 4-3 Tanzania Generation by Fuel Category - Modified National Expansion Plan 4-6 Figure 4-4 Kenya Existing National Expansion Plan by Plant Category 4-7 Figure 4-5 Kenya Modified National Expansion Plan by Plant Category 4-8 Figure 4-6 Kenya Generation by Fuel Category - Modified National Expansion Plan 4-12 Figure 4-7 Uganda Existing National Expansion Plan by Plant Category 4-13 Figure 4-8 Uganda Modified National Expansion Plan by Plant Category 4-14 Figure 4-9 Uganda Generation by Fuel Category - Modified National Expansion Plan 4-17 Figure 4-10 Ethiopia Existing National Expansion Plan by Plant Category 4-18 Figure 4-11 Ethiopia Modified National Expansion Plan by Plant Category 4-20 Figure 4-12 Ethiopia Generation by Fuel Category - Modified National Expansion Plan 4-23 Figure 4-13 Sudan Existing National Expansion Plan by Plant Category 4-24 Figure 4-14 Sudan Modified National Expansion Plan by Plant Category 4-26 Figure 4-15 Sudan Generation by Fuel Category - Modified National Expansion Plan 4-29 Figure 4-16 Egypt Existing National Expansion Plan by Plant Category 4-30 Figure 4-17 Egypt Modified National Expansion Plan by Plant Category 4-31 Figure 4-18 Egypt Generation by Fuel Category - Modified National Expansion Plan 4-35 Figure 4-19 Burundi New National Expansion Plan by Plant Category 4-37 Figure 4-20 Eastern DRC New National Expansion Plan by Plant Category 4-38 Figure 4-21 Rwanda New National Expansion Plan by Plant Category 4-39 Figure 4-22 Interconnections in the Burundi. Eastern DRC, Rwanda Region 4-42 Figure 4-23 Burundi Generation by Fuel Category - New National Expansion Plan 4-43 Figure 4-24 Eastern DRC Generation by Fuel Category - New National Expansion Plan 4-44 Figure 4-25 Rwanda Generation by Fuel Category - New National Expansion Plan 4-45 Figure 4-26 Djibouti Existing National Expansion Plan 4-46 Figure 4-27 Djibouti Existing National Expansion Plan with Extended Study Horizon 4-48 Figure 4-28 Djibouti Generation by Fuel Category – Existing National Expansion Plan 4-49 Figure 5-1 EAPP Interconnections Case NGP_RIP 5-5 Figure 5-2 Variation of some energy sources Case NGP_EIC vs Case NGP_RIP 5-6 Figure 5-3 Balance and net flow between countries Case NGP_RIP 5-8 Figure 5-4 EAPP Interconnections Case RGP_RIP 5-10 Figure 5-5 Balance and net flow between countries Case RGP_RIP 5-11 Figure 5-6 Benefit-Cost Analysis 5-15

Final Master Plan Report 1-1 WBS 1300 Supply Demand Analysis May 2011 & Project Identification


1 OBJECTIVE AND SCOPE This part of the study deals with the identification of interconnection and generation projects with regional scope, which potentially could bring regional benefits. Generation developments in each country, especially where large hydro projects are being planned, represent opportunities for exports in the initial years until the surplus is taken up by the local demand. When examined in a regional basis, exchange opportunities arise that can be leveraged by new interconnections. Also the re-scheduling of large regional hydro projects in one region can bring additional benefits by displacing expensive thermal-based generation in another region.

The specific objectives of this part of the study are:

• Set-up a regional database of existing, committed and candidate generation and interconnection projects for the development of the regional plans for the EAPP/EAC.

• Set-up the models for advanced generation planning simulation and planning tools: SDDP & OPTGEN (see below)

• To develop a supply-demand balance for each country based on the national expansion plans.

• To identify significant potential surpluses of indigenous generation as an indicator of potential interconnection opportunities.

• Develop regional master plans with different degrees of planning and operational coordination among the pool members.

1.1 Inputs Several Inputs are required for this part of the study, originating in other modules:

• Selected demand projections from Module 1A-1100

• Existing and committed plant technical characteristics from Module 1C-1200: capacity, efficiency (heat rate for TPP and production coefficients and reservoir characteristics for HPP), fuel costs, O&M costs, outage rates.

• Future plant technical characteristics from Module 1C-1200: Capacity, efficiency (heat rate for TPP and production coefficients and reservoir characteristics for HPP), fuel costs, O&M costs, outage rates and capital costs and construction schedule.

• Existing interconnections characteristics (transfer capacity in MW) from Module 1D-1500.

• Future interconnections characteristics (transfer capacity in MW) and capital costs capital costs and construction schedule from Module 1D-1500.

• Hydrological database for a common period for each existing and future HPP from Module 1C-1200

1.2 Tools In order to optimize the expansion of the interconnections and generation in the region and the short-term operation, it is absolutely necessary to take into account the interaction of each system with the rest. For this, computerized tools that are capable of modeling multiple systems are needed. The problem to be solved is to decide on the investments needed in generation and interconnections and the corresponding dispatch of these resources, so that the least cost at a regional level is attained. Moreover, due to the large proportion of hydro



energy, a dispatching algorithm representing individually the main reservoirs and run-of-river plants in the region is required that considers the stochastic nature of the inflows and their geographical and time (season, monthly) interdependencies.

For the optimization of the expansion of interconnections and generation and corresponding dispatching of resources the OPTGEN and SDDP tools have been chosen. SNC-Lavalin has a vast experience with the use of these tools in developing regional master plans as well as national master plans.

A brief description of the OPTGEN and SDDP follows. (More details about the models can be viewed on the publishing company’s website: PSR http://www.psr-inc.com.br).

1.2.1 OPTGEN OPTGEN is a computational tool for determining the least-cost expansion (generation and interconnections) of a multi-regional hydrothermal system, with a detailed representation of system operation. It takes into account constraints such as:

1. Investment decisions: earliest and latest dates, mandatory projects, mutually exclusive projects, minimum total installed capacity per year

2. Inflow uncertainties

3. Emission constraints

Generation and interconnection capacity expansion planning is a complex problem of decision-making under uncertainty. OPTGEN integrates the investment decision and operational analysis as shown in the Figure 1-1 below

Figure 1-1 OPTGEN investment and operation coordination

Typical inputs and outputs for OPTGEN are shown in the Table 1-1 below

investment decision

operational analysis

candidate plan

operation cost

investment cost

optimality check

feedback

SDDP

OPTGEN



Table 1-1 OPTGEN typical inputs/outputs

Inputs Outputs

• Existing system data

• Candidate plants / interconnectors costs and technical characteristics

• Retirement (existing plants)

• Demand projection

• Fuel cost projection

• Obligatory and optional projects

• Minimum installed capacity constraints

• Environmental constraints

• Generation and interconnections least cost expansion plan

• Benefits of coordinated vs. isolated expansion/operation

• All other outputs form SDDP (see below)

1.2.2 SDDP SDDP (Stochastic Dual Dynamic Programming) is a probabilistic multi-area hydro-thermal production costing model. It permits to optimize multiple reservoirs simultaneously. SDDP allows the optimal coordination of hydro and thermal resources. Key modeling capabilities include:

• Reservoir operation and optimization (turbining, spillage, irrigation, filtration, etc.) along complex cascades

• Inflow uncertainty through stochastic inflow models which represent both spatial and time dependence

• Thermal plant operation (efficiency curves, fuel limits, multiple fuels, etc.)

Typical inputs and outputs for SDDP are shown in the Table 1-2 below

Table 1-2 SDDP typical inputs/outputs

Inputs Outputs

• Plant technical characteristics.

• Interconnector capacities

• Demand shape’s projections

• Fuel cost projection

• Reservoir constraints

• Minimum generation constraints

• Fuel consumption constraints

• Generation by plant and by load block

• Marginal costs (demand, interconnection capacity, plant capacity, reservoir storage, etc)

• Opportunity cost of water in each hydro plant

• Locational Marginal Prices

• Inter-system flows

1.3 Methodology The first step consists of adjusting the available national master plans with OPTGEN. In the case were a recent plan was not available (Burundi, Rwanda, Eastern DRC), a new plan was developed. Then the national surpluses are evaluated with SDDP. All these national plans are developed using a common criteria:



• Revised demand forecast (see section 2).

• Common generation reliability criteria (see Module 1C-1200)

• Supply covers only national demand.

• Update of the status of projects that were assumed to be under construction, or that were supposed to be in operation by 2013.

The next step is to consider a coordinated regional operation (through a regional power exchange or regional pool dispatch) in order to maximize profitable power exchanges among the members of the pool and reduce as much as possible unserved energy. To this end, the existing interconnections plus future interconnection projects are considered. The new projects are identified based on the least cost regional development. Those projects that have been recently under study (i.e. Egypt-Sudan 500kV HVDC; Sudan-Ethiopia 500kV; Ethiopia-Kenya 500kV HVDC; Kenya-Tanzania 400kV; Tanzania-Uganda 220-kV and the Rusumo system) are analyzed to confirm their inclusion in the least cost regional plan. In addition, other new interconnection options are analyzed. The least cost master plan thus obtained balances the additional investments in interconnections with the saving due to fuel-displacement and operation cost savings via the regional exchanges.

An increased level of regional coordination would involve the consideration of generation plans. This next level represents a maximum level of cooperation in the development of both interconnection projects and large generation projects with regional scope. In this scenario the national generation master plans are re-optimized to exploit potential savings due to the advance of a cheap generation option in one country (e.g., Ethiopia hydro) to delay installation of more expensive options (e.g. steam plants) in other countries (e.g., Sudan )

Finally an analysis of the main factors of perceived risk is undertaken. One source of risk is the potential impact that a decision of a large importer can have in the regional exchanges. We consider in this case the impact on the regional plan of Egypt deciding to limit the imports only to the capacity of the (already planned) 500kv HVDC interconnection (2000MW). Another risk is the potential increase on the capital cost of interconnections, which is a distinct possibility if recent trends are considered (the cost of building material for transmission lines, associated equipments and substation showed a peak recently in 2008, and is now in 2010 almost at half the level then).

The Figure 1-2 below summarizes the methodology used for this part of the study



Figure 1-2 Methodology for developing regional plans

Adjustment of National Plans

•Revise (if necessary) with OPTGEN existing national generation master plans•Based on:•Revised demand forecast•Common generation reliability criteria•Update of status of commited projects•Self‐sufficiency (building only for local demand)•Evaluation of national surpluses (SDDP)

Regional Planning of interconnections

•First level of regional coordination•New interconnections are built to maximize profitable exchanges of surpluses of national plans•National Generation master plans are not modified•Analysis of net economic benefits

Regional Planning Interconnections and

large Generation projects

•Second level of regional coordination•New interconnections are built to maximize profitable exchanges of surpluses of national plans•National Generation master plans are coordinated so that advancing or delaying a large generation project may provide additional regional benefits•Analysis of net economic benefits

Risk analysis

•Variables/Policies that could have significant impact on the regional plan•Limited participation of large importers (eg. Egypt) in regional exchanges•Increase of investment cost of interconnections projects (double the base cost)•Analysis of impacts on net economic benefits



1.4 Main Results

• A national generation master plan has been updated for each of the ten countries in the region and this is presented in section 4. These revised plans are all based on consistent demand forecasts developed as part of this study (see Module 1A-1100). The plans also are subject to a set of common reliability criteria (see Module 1C-1200) and were adjusted so that the supply is developed to meet only the local needs. The status of projects under construction has been also updated according to the findings of the Inception Mission (see Inception Report). These revisions of the national generation master plans allow making a meaningful comparison of the benefits of the regional plans.

• National generation plans present some exploitable surplus due to the fact that the projects are of large size as compared to the local demand. This analysis is detailed in section 5.1. The following Table 1-3 shows the annual average potential surplus by country taken over the entire study period. The countries with greatest exportable surplus in relation to their local demand are Ethiopia, Uganda and Tanzania; followed by the region formed by (Burundi, Eastern DRC, Rwanda), then Sudan and then Kenya.

Table 1-3 Annual Average Potential Surplus by Country

Country Load (GWh) Surplus (GWh) Surplus/Load Ethiopia 28,386 12,557 44%

Uganda 7,768 2,636 34%

Tanzania 18,455 5,059 27%

Rwanda, Burundi, East DRC 3,369 840 25%

Sudan 46,707 7,824 17%

Kenya 39,975 6,003 15%

• As discussed in sections 5.3 and 5.6, the first level of regional coordination, through the coordinated operation of the pool using the existing and a selected group of new regionally planned interconnections, bring a significant benefit to the region (25,188 MUSD) when compared to the national plans for the study horizon (2013-38). This represents an annual benefit of 969 MUSD with an annual equivalent investment of only 172 MUSD.

In this scenario, all the interconnection projects that are currently being studied were selected in their corresponding earliest date: in 2015 the Tanzania-Uganda and the Tanzania-Kenya are needed, and in 2016, the Egypt-Sudan, the Ethiopia-Sudan and the Ethiopia-Kenya were selected. These interconnections are also selected as part of the least cost plan under the two sensitivities performed for this scenario and are therefore recommended for fast-track implementation.

• The second level of regional coordination (see sections 5.4 and 5.6) corresponds to an integrated interconnection and generation regional plan. This is the theoretical optimum that can be achieved. When compared to the national plans the regional net benefit amounts to 32,451 MUSD equivalents to 1,248 MUSD per year. 7,143MW of new generation capacity are saved in this scenario.

• The risk to a limitation of the import capacity of the Egyptian system (to a maximum of 2000MW) represents an impact of a reduction of 7,687 MUSD in regional net benefit



(296 MUSD/year) when compared to the second level of regional coordination and 6,852 MUSD (263 MUS/year) when compared to the first level of coordination.

• The risk to an increase in capital cost of interconnection and associated equipment/substations represent an impact of a reduction of 4,427 MUSD in regional net benefit (170 MUSD/year) when compared to the second level of regional coordination and 4,332 MUSD (167 MUSD/year) when compared to the first level of regional coordination.



2 DEMAND FORECAST The demand forecasts for all countries, for the entire study horizon, are presented in-depth in Module 1A-1100. For each country, several scenarios were created based on different criteria. In this chapter, the scenarios selected for the SDDP simulations are highlighted. This chapter also presents the manipulation done to these forecasts to render their format acceptable by the model.

2.1 Demand Scenarios

2.1.1 Selecting the adequate scenario

In Module 1A-1100, two sets of forecasts were proposed for each country, the national plan forecast and the PB forecast, each having a base, low and high case. Hence 6 scenarios were available to choose from for the supply-demand analysis in this module. The most adequate scenario was chosen. Table 2-1 summarizes the forecast scenarios chosen, referring to the names used in Module 1A-1100:

Table 2-1 Demand Forecast Scenarios Selected

Country Forecast Scenario Selected

Burundi Extended NELSAP Demand Forecast – Base Case

Djibouti LCEMP Demand Forecast – Base Case

Eastern DRC Extended NELSAP Demand Forecast – Base Case

Egypt Extended EEHC Demand Forecast – Base Case

Ethiopia Extended EEPCo Demand Forecast – Moderate I – Base Case

Kenya Extended 2008 LCPDP Demand Forecast – Base Case

Rwanda Extended NELSAP Demand Forecast – Base Case

Sudan PB Demand Forecast – Base Case

Tanzania Extended PSMP Demand Forecast – Base Case

Uganda PSIP Demand Forecast – Base Case

The forecasts listed above in Table 2-1 are in majority taken from the most recent available national master plan. This study starts on a national level, preparing new national plans that meet this study’s reliability criteria for each country and then compare them to the regional plan to assess the benefits of a regional expansion plan. However, these plans needed to be compared to the existing national expansion plans to highlight differences hence using the same forecast was more reasonable. This was the case for Djibouti, Egypt, Ethiopia, Kenya, Tanzania and Uganda. For Burundi, Rwanda and Eastern DRC, with no national plan available, the NELSAP report was considered. Finally in the case of Sudan, the national plan’s forecast starts in 2006 and demand for the years 2006-2009 did not match the forecast. Hence the PB forecast, which takes as a starting point the 2009 demand, was considered.

The full analysis and data behind these forecasts can be found in the report of Module 1A-1100 and its appendices.



2.1.2 Summary of forecast results

In this report, a brief summary of the forecasts for each country are presented in the form of:

• Tables with the values for the peak demand, sent out generation and growth rates;

• Graphs showing the evolution of the peak demand.

Table 2-2 Demand Forecast Chosen Scenarios - Peak Demand and Generated Energy

Year Burundi Djibouti

Energy (Gwh)

Annual Growth

Demand (MW)

Annual Growth

Energy (Gwh)

Annual Growth

Demand (MW)

Annual Growth

2009 379 68 2010 134 43 421 10.9% 74 9.5%2011 135 0.7% 44 1.6% 476 13.1% 84 12.5%2012 143 5.9% 47 6.3% 573 20.4% 100 18.9%2013 170 18.9% 56 19.8% 663 15.7% 116 16.7%2014 200 17.6% 66 17.8% 727 9.7% 128 10.3%2015 231 15.5% 77 16.5% 775 6.7% 138 7.3%2016 265 14.7% 89 15.4% 833 7.4% 149 8.0%2017 301 13.6% 102 14.4% 859 3.2% 153 3.2%2018 339 12.6% 116 13.6% 886 3.1% 158 3.1%2019 381 12.4% 131 13.1% 907 2.3% 162 2.3%2020 425 11.5% 147 12.4% 928 2.3% 165 2.2%2021 472 11.1% 165 12.0% 944 1.7% 168 1.6%2022 522 10.6% 184 11.6% 961 1.8% 171 1.6%2023 576 10.3% 204 11.3% 978 1.8% 173 1.7%2024 633 9.9% 227 10.9% 996 1.8% 176 1.7%2025 695 9.8% 251 10.7% 1016 2.1% 180 2.0%2026 760 9.3% 274 9.3% 1036 2.0% 183 2.0%2027 827 8.9% 300 9.4% 1057 2.0% 187 2.0%2028 898 8.5% 327 9.0% 1078 2.0% 191 2.0%2029 972 8.2% 355 8.7% 1100 2.0% 195 2.0%2030 1049 7.9% 385 8.3% 1122 2.0% 198 2.0%2031 1129 7.7% 415 8.0% 1144 1.9% 202 1.9%2032 1213 7.4% 448 7.7% 1166 1.9% 206 1.9%2033 1299 7.2% 481 7.5% 1189 2.0% 210 1.9%2034 1389 6.9% 516 7.2% 1212 2.0% 214 2.0%2035 1482 6.7% 552 7.0% 1236 2.0% 218 2.0%2036 1579 6.5% 589 6.8% 1260 1.9% 224 2.3%2037 1679 6.3% 628 6.6% 1284 1.9% 228 1.9%2038 1781 6.1% 667 6.4% 1308 1.9% 232 1.9%



Year Eastern DRC Egypt

Energy (Gwh)

Annual Growth

Demand (MW)

Annual Growth

Energy (Gwh)

Annual Growth

Demand (MW)

Annual Growth

2009 251 59 137056 22330 2010 262 4.5% 62 4.4% 145756 6.3% 23729 6.3%2011 275 5.0% 65 5.0% 154910 6.3% 25200 6.2%2012 289 5.0% 68 5.0% 164532 6.2% 26753 6.2%2013 303 5.0% 72 5.0% 174638 6.1% 28383 6.1%2014 318 5.0% 75 5.0% 185231 6.1% 30089 6.0%2015 334 5.0% 79 5.0% 196334 6.0% 31880 6.0%2016 352 5.5% 83 5.4% 207993 5.9% 33760 5.9%2017 372 5.5% 88 5.4% 220214 5.9% 35651 5.6%2018 392 5.5% 93 5.4% 233024 5.8% 37630 5.6%2019 413 5.5% 98 5.4% 246470 5.8% 39703 5.5%2020 436 5.5% 103 5.4% 260589 5.7% 41874 5.5%2021 461 5.7% 109 5.6% 275416 5.7% 44149 5.4%2022 487 5.7% 115 5.6% 290992 5.7% 46534 5.4%2023 515 5.7% 121 5.7% 307358 5.6% 49034 5.4%2024 545 5.8% 128 5.7% 324553 5.6% 51654 5.3%2025 576 5.8% 136 5.7% 342626 5.6% 54402 5.3%2026 610 5.8% 143 5.7% 361623 5.5% 57284 5.3%2027 645 5.8% 152 5.7% 381288 5.4% 60213 5.1%2028 682 5.8% 160 5.7% 401991 5.4% 63311 5.1%2029 722 5.8% 169 5.7% 423651 5.4% 66541 5.1%2030 764 5.8% 179 5.7% 446301 5.3% 69909 5.1%2031 808 5.8% 189 5.7% 469972 5.3% 73417 5.0%2032 855 5.8% 200 5.6% 494693 5.3% 77071 5.0%2033 904 5.7% 211 5.6% 520498 5.2% 80874 4.9%2034 955 5.7% 223 5.6% 547416 5.2% 84832 4.9%2035 1009 5.7% 235 5.5% 575478 5.1% 88947 4.9%2036 1066 5.6% 248 5.5% 604717 5.1% 93224 4.8%2037 1125 5.6% 262 5.5% 635162 5.0% 97668 4.8%2038 1187 5.5% 276 5.4% 666846 5.0% 102282 4.7%Year Ethiopia Kenya 2009 4828 1201 8140 1313 2010 5620 16.4% 1398 16.4% 8954 10.0% 1445 10.0%2011 6325 12.5% 1573 12.5% 9847 10.0% 1589 10.0%2012 7083 12.0% 1762 12.0% 10830 10.0% 1747 10.0%2013 7897 11.5% 1964 11.5% 12134 12.0% 1958 12.0%2014 8816 11.6% 2193 11.6% 13739 13.2% 2193 12.0%2015 9823 11.4% 2443 11.4% 15390 12.0% 2456 12.0%2016 10917 11.1% 2715 11.1% 16743 8.8% 2672 8.8%2017 12038 10.3% 2994 10.3% 17988 7.4% 2871 7.4%2018 13182 9.5% 3279 9.5% 19327 7.4% 3085 7.4%2019 14374 9.0% 3575 9.0% 20765 7.4% 3314 7.4%2020 15610 8.6% 3883 8.6% 22310 7.4% 3561 7.4%2021 16888 8.2% 4201 8.2% 24187 8.4% 3860 8.4%2022 18265 8.2% 4543 8.2% 26222 8.4% 4185 8.4%2023 19750 8.1% 4912 8.1% 28428 8.4% 4537 8.4%2024 21351 8.1% 5311 8.1% 30723 8.1% 4919 8.4%2025 23079 8.1% 5741 8.1% 33307 8.4% 5333 8.4%2026 24944 8.1% 6204 8.1% 35936 7.9% 5753 7.9%2027 26958 8.1% 6705 8.1% 38786 7.9% 6210 7.9%2028 29134 8.1% 7247 8.1% 41831 7.9% 6697 7.9%2029 31486 8.1% 7832 8.1% 45217 8.1% 7227 7.9%2030 34030 8.1% 8464 8.1% 48775 7.9% 7795 7.9%2031 36787 8.1% 9150 8.1% 52412 7.5% 8393 7.7%2032 39766 8.1% 9891 8.1% 56402 7.6% 9037 7.7%2033 42987 8.1% 10692 8.1% 60651 7.5% 9723 7.6%2034 46469 8.1% 11558 8.1% 65170 7.4% 10453 7.5%2035 50233 8.1% 12495 8.1% 69968 7.4% 11229 7.4%2036 54302 8.1% 13507 8.1% 75058 7.3% 12053 7.3%2037 58701 8.1% 14601 8.1% 80450 7.2% 12927 7.2%2038 63455 8.1% 15783 8.1% 86154 7.1% 13852 7.2%



Year Rwanda Sudan

Energy (Gwh)

Annual Growth

Demand (MW)

Annual Growth

Energy (Gwh)

Annual Growth

Demand (MW)

Annual Growth

2009 305 59 6118 1151 2010 330 8.1% 63 7.5% 7211 17.9% 1357 17.9%2011 386 17.0% 73 16.5% 8264 14.6% 1555 14.6%2012 442 14.6% 84 14.2% 9436 14.2% 1775 14.2%2013 499 12.7% 94 12.4% 10733 13.7% 2019 13.7%2014 555 11.3% 105 11.0% 12161 13.3% 2288 13.3%2015 611 10.1% 115 9.9% 13723 12.8% 2582 12.8%2016 697 14.1% 132 14.6% 15426 12.4% 2902 12.4%2017 784 12.4% 149 12.7% 17273 12.0% 3250 12.0%2018 870 11.0% 165 11.3% 19270 11.6% 3626 11.6%2019 957 9.9% 182 10.2% 21421 11.2% 4030 11.2%2020 1043 9.0% 199 9.2% 23731 10.8% 4465 10.8%2021 1162 11.4% 225 13.0% 26204 10.4% 4930 10.4%2022 1281 10.2% 251 11.5% 28845 10.1% 5427 10.1%2023 1399 9.3% 276 10.3% 31657 9.7% 5956 9.7%2024 1518 8.5% 302 9.3% 34844 10.1% 6556 10.1%2025 1637 7.8% 328 8.5% 38248 9.8% 7196 9.8%2026 1780 8.8% 356 8.5% 41874 9.5% 7878 9.5%2027 1922 8.0% 386 8.4% 45731 9.2% 8604 9.2%2028 2071 7.7% 417 8.1% 49825 9.0% 9374 9.0%2029 2225 7.5% 450 7.8% 54164 8.7% 10190 8.7%2030 2385 7.2% 484 7.6% 58754 8.5% 11054 8.5%2031 2552 7.0% 519 7.3% 63603 8.3% 11966 8.3%2032 2725 6.8% 556 7.1% 68718 8.0% 12929 8.0%2033 2904 6.6% 594 6.9% 74105 7.8% 13942 7.8%2034 3089 6.4% 634 6.7% 79773 7.6% 15009 7.6%2035 3280 6.2% 675 6.5% 85727 7.5% 16129 7.5%2036 3477 6.0% 717 6.3% 91976 7.3% 17304 7.3%2037 3680 5.9% 761 6.1% 98525 7.1% 18537 7.1%2038 3890 5.7% 806 5.9% 105383 7.0% 19827 7.0%Year Tanzania Uganda 2009 2877 561 2010 5293 895 3026 5.2% 596 6.2%2011 5773 9.1% 981 9.6% 3188 5.4% 633 6.2%2012 6439 11.5% 1103 12.4% 3371 5.7% 673 6.5%2013 7081 10.0% 1213 10.0% 3560 5.6% 715 6.2%2014 7489 5.8% 1285 6.0% 3788 6.4% 764 6.9%2015 8135 8.6% 1398 8.7% 4030 6.4% 816 6.8%2016 8987 10.5% 1542 10.3% 4288 6.4% 871 6.7%2017 9895 10.1% 1698 10.1% 4561 6.4% 929 6.6%2018 10704 8.2% 1839 8.3% 4851 6.4% 990 6.6%2019 11326 5.8% 1945 5.8% 5123 5.6% 1045 5.5%2020 11994 5.9% 2061 5.9% 5362 4.7% 1091 4.4%2021 12701 5.9% 2182 5.9% 5685 6.0% 1158 6.1%2022 13440 5.8% 2311 5.9% 6056 6.5% 1233 6.5%2023 14398 7.1% 2479 7.3% 6434 6.3% 1310 6.3%2024 15245 5.9% 2628 6.0% 6821 6.0% 1389 6.0%2025 16145 5.9% 2783 5.9% 7216 5.8% 1470 5.8%2026 17112 6.0% 2953 6.1% 7620 5.6% 1552 5.6%2027 18116 5.9% 3131 6.0% 8031 5.4% 1636 5.4%2028 19379 7.0% 3353 7.1% 8450 5.2% 1722 5.2%2029 20536 6.0% 3558 6.1% 8878 5.1% 1809 5.1%2030 21745 5.9% 3770 6.0% 9313 4.9% 1898 4.9%2031 23042 6.0% 4002 6.1% 9754 4.7% 1978 4.2%2032 24449 6.1% 4254 6.3% 10203 4.6% 2069 4.6%2033 26164 7.0% 4532 6.6% 10659 4.5% 2162 4.5%2034 27917 6.7% 4838 6.7% 11123 4.4% 2257 4.4%2035 29854 6.9% 5168 6.8% 11594 4.2% 2353 4.3%2036 31978 7.1% 5527 6.9% 12073 4.1% 2450 4.1%2037 34311 7.3% 5918 7.1% 12559 4.0% 2549 4.0%2038 36873 7.5% 6344 7.2% 13025 3.7% 2650 3.9%



The peak demand data in Table 2-2 is plotted next in graphs to visualize the trend. Countries with close levels of demand were grouped together in one graph.

Figure 2-1 Peak Demand Forecasts - Burundi, Djibouti, Eastern DRC and Rwanda

Figure 2-2 Peak Demand Forecasts - Ethiopia, Kenya, Sudan, Tanzania and Uganda

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Figure 2-3 Peak Demand Forecasts - Egypt

2.2 Demand Forecast in SDDP Format

The forecasts presented above are given in a yearly format. In the model’s database however, the forecast for each country has to be entered in a different format. The simulation runs in predefined stages and the model has to be provided with the peak load for every stage. For this study, the stage is one month hence the demand has to be on a monthly basis. More so, for every stage (month) the demand has to be split into three load blocks: The peak period, the middle period and the base period.

Therefore, for every system, one year’s energy and peak demand forecasts are manipulated to generate 36 load values (3 blocks x 12 months). Using the hourly load historical data, a continuous load duration curve (LDC) for every month is drawn. Then it is rendered into a discrete curve of three blocks, with the following conventions:

• The peak block accounts for 10% of the month’s time (e.g. January: 10% x 24 hrs x 31 days = 74.4 hrs) and the load level is the peak demand in the month’s continuous LDC. (The energy in this block can therefore be calculated by a straight calculation)

• The middle block accounts for 50% of the time and has 60% of the total energy of the continuous LDC. The load level is then calculated through dividing the energy by the time.

• The base block accounts for 40% of the time and has the remaining energy in the LDC, from which the load level can be calculated in a similar way.

Finally, these LDCs are scaled for every year of the forecast through multiplying the load values by a factor equal to the rate of increase of the forecast from the year the LDC was drawn to the forecast year. The 36 values for each of the 26 years (936 values) are then entered into the model’s database.

An in depth explanation and example on this manipulation is provided in Appendix A.

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3 STUDY DATABASE For the present study, the power systems of the ten countries were simulated on the models SDDP and OPTGEN. In order to get as close as possible to the real systems and have the simulations mirror their daily operations, it was essential to gather all the data available on the technical specs of every power plant, be it thermal, hydro, wind or solar. The numbers would then be entered into the database, along with the demand forecast for the entire study horizon, and used by the models to generate the desired results. Having the right characteristics for the plants adds a degree of credibility to the expansion plans generated by the model.

Even though both models work cooperatively, each has its own list of required data. Scanning through the references listed in Table 2-2 of Module 1C-1200, the database for both models was completed and each country’s power system was adequately simulated.

In this chapter, the various data required by both models are presented briefly. The full set of data is provided in Appendix B in the form of two tables per country: one for the hydro plants and one for the remaining plants.

3.1 Data required by SDDP 3.1.1 Thermal, Wind and Solar Plants For the simulation of thermal plants, SDDP mainly requires the following data:

• Plant name, fuel type, and status (Existing/Future);

• Installed potential (MW), minimum and maximum generation (MW), number of units;

• Composite outage rate (COR) (%), variable operation & maintenance (O&M) cost ($/MWh), heat rate (GJ/MWh).

Fuels are separately defined in the model for each system, with the forecasted prices compliant with Section 6.4 in Module 1C-1200. Then when defining a new plant, the corresponding fuel type is selected from the fuels database. Heat rates and variable costs also comply with the values in Module 1C-1200.

Due to the difficulty of obtaining all the required characteristics for all the plants of every system, some assumptions were made for the simplification of the database building, when the required numbers were not found:

• Number of units was set at 1;

• Minimum generation was set at 0;

• Maximum generation was set equal to installed potential;

• FORs and CORs were set equal to the ones from a similar plant in the system, or the next closest system;

• For nuclear plants, COR = 10%, with variable O&M cost = 0;

• Generic plants took similar characteristics to other plants of the same type in the system or plants from the closest system.

In the model, wind farms were modeled as thermal plants, with no fuel cost and 70% COR. Solar plants were also modeled as thermal plants, with no fuel costs and 55% COR. Both wind and solar plants had 0 variable O&M costs.



3.1.2 Hydro Plants For the simulation of hydro plants, SDDP mainly requires the following data:

• Plant name, type (Storage/Run-of-River) and status (Existing/Future);

• Hydro site, plant to turbine to, plant to spill to;

• Installed potential (MW) and number of units;

• Minimum and maximum turbining (m3/s) , production coefficient (MW/m3/s);

• Minimum and maximum storage (Hm3)

Hydro sites refer to the ones presented in Appendix C of Module 1C-1200. The complete hydrology data is entered into the model. And each storage plant is linked to one of these hydro sites to simulate their water intake. For run-of-river (ROR) plants, no hydro site is required, thus a dummy zero-inflow hydro site was created and ROR plants were linked to that site.

Downstream plants (“Turbine to”) and “Spill to” plants were obtained from the study of the geographical layouts of the hydro plants on the rivers. Plants at the end of the stream turbine and spill to the river, with no other plant benefiting from that flow.

Due to the difficulty of obtaining all the required characteristics for all the plants of every system, some assumptions were made for the simplification of the database building, when the required numbers were not found or information was not available:

• The “hydro site” was set as the zero-inflow one.

• The “turbine to” and “spill to” entries were left blank.

• Number of units set at 1

• Minimum Turbining set at 0

• Minimum Storage set at 0

When the storage was mentioned as being only used for daily regulation, minimum storage was set equal to maximum storage. Finally when a plant was described as a storage plant in a reference but the storage level was not found, the plant was set as ROR instead i.e. with 0 storage.

3.1.3 Fuels As mentioned earlier, fuels are separately defined. For every system, the fuels are entered into the fuel database with their name, preferred consumption unit and fuel price in $/unit. The unit was set as GJ for all fuels for consistency. For the fuel prices, Section 6-4 of Module 1C-1200 defined forecasts for most of them (Oils, NG, Coal, Geothermal), while the rest (Methane Gas, Cogen, Bagasse, Nuclear) had one price for the entire study horizon, taken from the references in Table 2-2 of Module 1C-1200.

3.1.4 Demand Forecast As mentioned in the introduction to this chapter, the demand forecast for the entire study horizon is required. However SDDP requires it in the form of load blocks for every stage of the study. It was explained in the previous section that the load in the study is split into three blocks (peak, mid and low) and the simulations are run for every month. Appendix A explains how the forecast was obtained for every block of every month of the study horizon. The forecast in SDDP format (3 blocks x 12 months x 26 years = 936 values) is thus entered in the model’s database for every system.



3.2 Data Required for OptGen OptGen deals with future plants primarily, and both hydro and thermal future plants need the same types of data:

• Investment cost in MUSD or $/KW

• Fixed O&M Cost in $/KW

• Plant Lifetime in years

• Plant entrance schedule

• Investment Payment schedule

• Minimum and Maximum entrance in operation date

• Decision type: Optional or Obligatory

Investment costs, Fixed O&M costs and plant lifetimes are compliant with the data in Module 1C-1200 Tables 5-12 and 6-16. For entrance schedule, the default setting for most plants was to install all units at once, except when advised otherwise by the already existing national plans. The payment schedule was set as one single payment in the first year since the investments considered come from Tables 5-12 and 6-16 where the interest during construction was already calculated and included in the total cost.

The Minimum and Maximum entrance dates were initialized at 2013 and 2038 respectively and the decision type was selected as Optional for all candidates. These settings would then be modified depending on the first iterations of the model to generate the final expansion plan.

3.3 References The references used to gather the required data are all listed in Table 2-2 of module 1C-1200. In most cases, the main source was the most recent available master plan for the country in question. However, in some cases, more in-depth research had to be done, looking at feasibility studies for select hydro projects or annual reports from the utilities of the countries. Regional studies like the SSEA [1,2] or the ENPTPS [10] were of great help. Finally, internet research and email communications with the utilities clarified any discrepancy. The references used for each system are listed in the tables in Appendix B.



4 NATIONAL EXPANSION PLANS Although the latest national master plans are taken as a starting point for the elaboration of the regional master plan, it is important to realize that these available national plans were not consistent among each other. Different study horizons and reliability criteria were used in their elaboration. For the purpose of the regional master plan and the assessment of benefits of an increased level of regional coordination in operation and planning, it is necessary to have national master plans with consistent criteria for:

• study horizon: 2013-2038;

• reliability criteria;

• an update of the status of planned and committed projects; and,

• covering the local demand with national resources only. Exports and imports are considered later in the regional master plan.

For that purpose, the latest existing master plan was considered and, when needed, was modified to fit the new demand forecast as well as to meet the reliability criteria. Also in some cases, projects that were supposed to come online prior to 2013 but experienced major delays and have yet to get commissioned, were considered as candidates in the modified plan, instead of counting them as existing in 2013.

Note: In the presentation of the master plan results in the form of bar charts, three categories are used in order to group plants running on similar types of fuel:

• Renewable Energy: Hydro, Wind, Solar and Biomass plants.

• Clean Energy: Geothermal, Natural Gas, Methane Gas, Nuclear and Cogeneration plants.

• Conventional Energy: Diesel, Fuel Oil, Crude Oil, Gasoil and Coal plants.

Each category’s aggregate installed capacity (MW) will form one single bar with the total capacity of the system in any given year consisting of the stacked bars from the three categories.

The same repartition will be used when presenting energy generation results (GWh) from the SDDP simulations of each individual system with the addition of a category for net exchange.

4.1 Tanzania 4.1.1 Existing national expansion plan The national plan considered for Tanzania is the 2009 PSMP done by SNC-Lavalin for TANESCO [3]. The study period in that plan is from 2009 to 2033. Figure 4-1 presents the expansion plan in a bar chart showing the evolution of the Tanzania generation capacity by plant category:



Figure 4-1 Tanzania Existing National Expansion Plan by Plant Category

The system has a huge proportion of hydro generation (up to 64% in 2023) and the reliability criteria used in the 2009 PSMP was to meet the energy demand with the firm energy of hydro plants plus the available thermal production. This produced an expansion plan that was driven primarily by energy needs. This resulted in a reserve margin that is quite high from the first year of this study horizon: 46% in 2013. The reserve increases to 59% by 2033.

4.1.2 Modified national expansion plan The load considered in the present study is the same as the one from the PSMP, with an expansion on the forecast to cover the remaining 5 years. The two main goals of the modified plan are:

• Adjust the generation additions to take into account the new reliability criteria.

• Taking care of the generation expansion for the years 2034-2038.

The chart for the modified plan is presented hereafter in Figure 4-2:

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Figure 4-2 Tanzania Modified National Expansion Plan by Plant Category

The reserve at the end of the horizon settles a little above 15%, which is enough for the system to meet the load within the adopted reliability criteria.

The main changes as will be seen in the next section, affected the new CCGT and Coal STPP plants: the orange bar representing the clean thermal plant additions (i.e. CCGTs running on NG) grows in small steps between 2033 and 2038 in the new plan instead of coming in as a one shot addition in 2033. It’s also possible to see that red bars representing conventional thermal plants (Coal STPPs) follow a similar trend. The capacity additions in the new plan are more evenly distributed and it takes 4 more years to cross the 7,000 MW mark (2037 vs. 2033).

The complete set of tabulated values for the data behind these charts can be found in Appendix C.

4.1.3 Existing Vs. Modified national expansion plan Both the existing and modified plans are displayed next in Table 4-1 to compare and inspect the changes. Those changes, whether in the date of entry of a plant, or when a totally new plant is introduced to the plan, are highlighted in bold, whereas any retirement is in italic:

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Table 4-1 Tanzania Existing Vs. Modified National Expansion Plan

Year Existing Plan (EP) Modified Plan (MP)

Plant Name Type MW S/T (MW) Plant Name Type MW S/T (MW)

2013 Kiwira TPP 200 490 Kinyerezi TPP 240 240 Kinyerezi TPP 240 Wind WPP 50

2014 0 Kiwira TPP 200 200

2015 Rusumo HPP 63 63 Rusumo HPP 63 113

Wind WPP 50

2016 Ruhudji HPP 358 358 Ruhudji HPP 358 358

2017 Mnazi Bay TPP 300 300 Mnazi Bay TPP 300 300

2018 Rumakali HPP 222 222 Rumakali HPP 222 222

2020 Stieglers 1 HPP 300 300 Stieglers 1 HPP 300 300

2022 Tegeta IPTL TPP -100 -100 Mchuchuma TPP 200 100 Tegeta ITPL TPP -100


Songas 1 TPP -40 Songas 1 TPP -40

2024 Ngaka TPP 400 253 Ngaka TPP 200 53 Songas 2 TPP -110 Songas 2 TPP -110 Songas 3 TPP -37 Songas 3 TPP -37

2025 Mchuchuma TPP 400 400 0


2027 Nyasa Coal TPP 200 253 Kakono HPP 53 53

Kakono HPP 53

2028 Local Gas TPP 200 462 Local Gas TPP 200 462 Masigira HPP 118 Masigira HPP 118 Mpanga HPP 144 Mpanga HPP 144

2029 Ikondo HPP 340 240 Ikondo HPP 340 240

Ubongo_T TPP -100 Ubongo_T TPP -100

2030 Coastal Coal I TPP 300 404 Taveta HPP 145 104 Taveta HPP 145 Tegeta GT TPP -41 Tegeta GT TPP -41

2031 Coastal Coal II & III TPP 600 440 Ngaka TPP 200 40

New Cogen TPP 40 New Cogen TPP 40 Mwanza TPP -100 Mwanza TPP -100 Cogen TPP -40 Cogen TPP -40 Ubongo_E TPP -60 Ubongo_E TPP -60

2032 Coastal Coal IV & V TPP 600 600 Coastal Coal I TPP 300 300

New Wind WPP 50 New Wind WPP 50 Wind WPP -50 Wind WPP -50

2033 CC LNG (I-IV) TPP 696 456 CC LNG I TPP 174 234

Kinyerezi TPP -240 Coastal Coal II TPP 300 Kinyerezi TPP -240

2034 0 Tegeta IPTG TPP 100 724

CC LNG II TPP 174 Coastal Coal III TPP 300




Plant Name Type MW S/T (MW) Plant Name Type MW S/T (MW) Songwe Sofre HPP 150

2035 0 Songwe Manolo HPP 156 456

Coastal Coal IV TPP 300

2036 0 Songwe Bigupu HPP 34 208 CC LNG III TPP 174

2037 0 Coastal Coal V TPP 300 300

2038 0 DSM CCGT TPP 174 348

CC LNG IV TPP 174

Total Existing Plan 6001 Modified Plan 6215

The total additions are almost the same with only around 200 MW of difference. In 2033 the modified plan has only 4,174 MW of additions which is almost 2,000 MW less than the original expansion plan. The main changes to the existing national plan were:

• 400 MW of coal STPP (200 from Mchuchuma and 200 from Nyasa) were removed.

• 200 MW each from Ngaka and Mchuchuma Coal STPP were displaced.

• Coastal Coal and CC LNG generic plants had their units displaced into the future.

• Hydro plants from the Songwe river were selected.

4.1.4 Investment net present value The investment costs of all future plants in the modified national expansion plan are listed in Tables 5-12 and 6-16 of Module 1C-1200. Using a 10% interest rate, Tanzania’s investment net present value in 2013 is split into:

• Hydro: 1,976.33 MUSD; and,

• Thermal: 2,916.19 MUSD.

For a total of 4,892.51 MUSD, which means thermal investments make up 60% of the total against 40% for the hydro investments. Investments will be compared in the next section to the ones in the regional plan, in order to highlight the benefits of interconnections.

4.1.5 Interconnections and energy generation The new expansion plan was simulated with SDDP in order to obtain the generation by fuel type. The following existing and committed interconnections were considered in the simulation:

• 132 KV double-circuit AC transmission line between Tanzania and Uganda with a capacity of 59 MW.

• 220 KV single-circuit AC transmission line between Tanzania, Rwanda and Burundi, through the Rusumo Falls project with a capacity of 350 MW from the project towards Tanzania, with a 280 MW portion from the project to Rwanda and a 320 MW portion to Burundi.

The energy generation by fuel category for Tanzania, including net exchanges with neighbouring countries, is shown below in Figure 4-3:



Figure 4-3 Tanzania Generation by Fuel Category - Modified National Expansion Plan

It is observed that the generation is mostly comprised of renewable energy (blue bar) under the form of hydro power, with coal accounting for the majority of the thermal generation as well, under the conventional fuels label (red bar). Renewable energy (hydro, wind) makes up about 40% of the generation in the initial year but increases to about 80% in 2030. That proportion drops to around 55% by 2038 as very few new renewable plants are introduced.

There is a corresponding increase in conventional thermal generation (Coal, Diesel, HFO) from as little as 2% in 2013 to 40% in 2038. The clean thermal energy (NG, Cogen) observes an opposite trend starting at 60% in 2013 and dropping to 5% in 2038. The main reason for that is that coal is a cheaper source of energy than NG and the reserve of NG in Tanzania will be reduced at the end of the study period. With the expansion plan involving a large amount of new Coal STPPs, the generation will shift from NG to coal for a least cost operation.

Finally, the exchange with Uganda, Rwanda and Burundi represented by the green bar is a very small portion of the load (3% on average), which means the expansion plan put in place for Tanzania is self-sufficient.

The complete set of tabulated values for the data behind this chart can be found in Appendix C.

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4.2 Kenya 4.2.1 Existing national expansion plan The national plan considered for Kenya is the 2008 Least Cost Power Development Plan (LCPDP) done for the Kenya Ministry of Energy in collaboration with the power utility corporations KenGen and KPLC [27]. The study period in that plan is from 2009 to 2030. Figure 4-4 presents the expansion plan in a bar chart showing the evolution of the Kenya generation capacity by plant category:

Figure 4-4 Kenya Existing National Expansion Plan by Plant Category

The reserve margin in 2030 is close to 15%. With the load considered in the present study being the same as the one used in the LCPDP, the main reasons behind the need for a new national expansion plan are:

• The system looks to be over-installed in 2013, with more than 50% reserve margin. The existing system needs to be inspected for any delayed or un-commissioned projects.

• The plan includes around 1,700 MW of import capacity. It was explained that the study requires a national plan that is self-sufficient i.e. can meet its load from within its own generation. These 1,700 MW need to be replaced by local generation.

• The plan includes 1,200 MW of nuclear development. As discussed in the Inception Report, nuclear plants are only considered in Egypt. Hence these 1,200 MW also need to be replaced by another type of local generation.

• Additional generation might be needed to cover the load for the years beyond the study horizon of the LCPDP (2031-2038), with the forecasted growth around 8% in 2030 and the reserve in 2030 only 15%.

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4.2.2 Modified national expansion plan With the objectives of this modified plan highlighted in the previous sub-section, the following measures have been taken:

• Some wind developments with a total capacity close to 350 MW, present in the original plan with a date of entry between 2011 and 2013, were used as candidates for after 2013 instead as no additional information was available. This will decrease the capacity of the existing system in 2013.

• Imports have been taken out of the expansion plan.

• Nuclear development has been taken out as well. It was directly replaced by the most available thermal resource in Kenya: Coal. 1,200 MW of Coal STPP were fixed in the plan with the same entry schedule as the NPPs from the LCPDP (600 MW in 2025 and 600 MW in 2028).

• The LCPDP mentions a large resource of geothermal and the desire to develop that resource at the rate of around two (140 MW) plants per year. That guideline was considered by the new plan.

• Additional generic Coal STPPs (300 MW plants) were added. Other generics were also considered: OCGTs (200 MW) and CCGTs (348 MW) running on imported NG.

• Hydro projects highlighted in Module 1C-1200 but unselected by the LCPDP were also considered (Karura, Ewaso Ngiro and Magwagwa).

The new national expansion plan is shown in Figure 4-5 in the form of a bar chart representing the yearly system configuration by plant category:

Figure 4-5 Kenya Modified National Expansion Plan by Plant Category

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At first glance, the issues highlighted previously look to be resolved. The reserve is close to 40% in 2013 (with a smaller existing system) but drops slowly to stabilize a little under the 15% mark without any NPP or imports. With this expansion plan, Kenya should now have a self-sufficient future system. The mix of different types of generic thermal plants creates an extra degree of reliability as the system is not dependant on one type of generation and will not deplete Kenya of its coal reserve.



Table 4-2 Kenya Existing Vs. Modified National Expansion Plan



2013 Geothermal TPP 140 440 Geothermal TPP 140 440 Import IMP 300 Turkana Wind WPP 300

2014 0 Cogen Future TPP 126 406

Geothermal TPP 280

2015 Geothermal TPP 140 185 Generic Coal TPP 300 245 Import IMP 100 Nairobi Fiat TPP ‐10 Nairobi Fiat TPP ‐10 Olkaria 1 TPP ‐45 Olkaria 1 TPP ‐45

2016 Geothermal TPP 280 280 Geothermal TPP 140 140


2018 Geothermal TPP 280 280 Mutonga HPP 60 200 Geothermal TPP 140

2019 Import IMP 100 40 Generic CCGT NG TPP 348 288

Kipevu Diesel TPP ‐60 Kipevu Diesel TPP ‐60

2020 Low Grand Falls HPP 140 220 Low Grand Falls HPP 140 340 Geothermal TPP 140 Aeolus Wind WPP 60 IberAfrica 1 TPP ‐60 Generic OCGT NG TPP 200 IberAfrica 1 TPP ‐60

2021 Mutonga HPP 60 360 Generic CCGT NG TPP 348 348

Import IMP 300

2022 Geothermal TPP 280 203 Magwagwa HPP 120 391 Tsavo IPP TPP ‐77 Generic CCGT NG TPP 348 Tsavo IPP TPP ‐77

2023 Import IMP 900 900 Geothermal TPP 140 340

Generic OCGT NG TPP 200

2024 Geothermal TPP 140 290 Ewaso Ngiro HPP 180 430 LSD 150 TPP 150 Osiwo Wind WPP 50 Generic OCGT NG TPP 200

2025 Nuclear NPP 600 600 Mombasa Coal TPP 600 600





2026 LSD 150 TPP 150 290 Geothermal TPP 280 280 Geothermal TPP 140


Generic CCGT NG TPP 348

2028 Nuclear NPP 600 530 Momnasa Coal TPP 300 530 Olkaria 2 TPP ‐70 Generic Coal TPP 300 Olkaria 2 TPP ‐70

2029 LSD 150 TPP 150 404 Generic CCGT NG TPP 696 670

Geothermal TPP 280 Cogeneration TPP ‐26 Cogeneration TPP ‐26

2030 Geothermal TPP 280 730 Karura HPP 56 476

LSD 150 TPP 150 Geothermal TPP 420 Coal 300 TPP 300

2031 0 Geothermal TPP 140 836

Generic CCGT NG TPP 696


2033 0 Geothermal TPP 280 628 Generic CCGT NG TPP 348



2035 0 Geothermal TPP 280 880 Generic OCGT NG TPP 600



2037 0 Geothermal TPP 280 880 Generic Coal TPP 600


Generic Coal TPP 900


The modified plan adds around 7,000 MW more than the existing plan by 2038. 6,400 of those additions are installed after the LCPDP’s final year (2030). This means that with the new modified plan, the 2030 total additions would be around 6,900 MW, 600 MW more than the original plan. The nuclear plants were adequately replaced by Coal STPPs, while the required import capacity was mainly substituted by Generic CCGTs running on NG, albeit in a different schedule. What can also be observed in Table 4-2 is the extra amount of renewable energy in the form of Hydro (356 MW) and wind (410 MW; 350 of which have been displaced into the future from the 2013 existing system).

The Geothermal expansion follows a 280 MW/year trend for the extended period (2031-2038). It is accompanied by a combination of Generic CCGTs, OCGTs and Coal STPPs for the required additional 6,400 MW of capacity.



In conclusion, from a capacity point of view, in the LCPDP horizon, there is not much difference as the new plan proposes a system with only 200 MW more of capacity in 2030 for reliability purposes. The difference is in the type and schedule of additions, with the new plan projecting a system that is more diverse, feasible and self-sufficient.

4.2.4 Investment net present value The investment costs of all future plants in the modified national expansion plan are listed in Tables 5-12 and 6-16 of Module 1C-1200. Using a 10% interest rate, Kenya’s investment net present value in 2013 is split into:

• Hydro: 713.74 MUSD; and,

• Thermal: 9,815.83 MUSD,



• 132 KV double-circuit AC transmission line between Kenya and Uganda with a capacity of 118 MW.

• 220 KV double-circuit AC transmission line between Kenya and Uganda with a capacity of 300 MW.

The energy generation by fuel category for Kenya, including net exchanges with neighbouring countries, is shown below in Figure 4-6:



Figure 4-6 Kenya Generation by Fuel Category - Modified National Expansion Plan

In Kenya, renewable generation represents a small proportion of the total generation. It decreases from 45% in 2013 to under 10% by the end of the study period, as more thermal plants are introduced.

The rest of the generation is split between clean and conventional thermal generation with clean energy, consisting of NG, geothermal and cogeneration, accounting for more than 50% starting in 2017 and reaching as high as 70% in the final years. Conventional generation from Coal mostly, varies around an average of 23%. This is a cheap source of energy and is used for economic purposes and for peak load periods when clean generation alone is insufficient.

Finally imports from Uganda are worth around 5% of the total load. Therefore with around 80% of the total generation consisting of clean energy while satisfying the load with little need for imports, the expansion plan proposed is then considered to be a good option both from reliability and environmental viewpoints.


4.3 Uganda 4.3.1 Existing national expansion plan The national plan considered for Uganda is the Generation Plan included in the 2009 Power Sector Investment Plan (PSIP) done for the Uganda Ministry of Energy and Mineral Development by Parsons Brinckerhoff [37]. The study period in that plan is from 2009 to 2030. Figure 4-7 presents the expansion plan in a bar chart showing the evolution of the Uganda generation capacity by plant category:

05,000

10,00015,00020,00025,00030,00035,00040,00045,00050,00055,00060,00065,00070,00075,00080,00085,00090,000

2013

2015

2017

2019

2021

2023

2025

2027

2029

2031

2033

2035

2037

GWh Net Exchange

Conventional

Clean

Renewable



Figure 4-7 Uganda Existing National Expansion Plan by Plant Category

In the final 5 years (2026-2030) the existing expansion plan has a reserve problem as it drops below 10 % and even goes negative in 2027 and 2030. The main reason is that the present study considers a new load forecast, defined in Module 1A-1100, about 10% higher than the one used in the plan. With the original load forecast, the reserve oscillated between 10 and 20% in these 5 years. However it was necessary to simulate the original plan with the new load to highlight any deficiencies since the plan required for Uganda has to be self-sufficient with the new load.

The problems that need to be dealt with by the new plan are:

• Re-optimize the future system for the years 2013-2030 since this study is dealing with a different load.

• Extend the plan to cover for the remaining 8 years of this present study’s horizon (2031-2038).

• The original plan involves generic plants called Base Load (assumed to be similar to an STPP) and Peak Load (similar to an OCGT), in addition to some small hydro generics. The choice of generics in the plan has to be changed to be consistent (type, fuel, size, costs) with the planning criteria presented in Module 1C-1200 and used throughout this study.

4.3.2 Modified national expansion plan With the objectives of this modified plan highlighted in the previous sub-section, the following measures have been taken:

0%

10%

20%

30%

40%

50%

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

2,400

2,600

2,800

3,000

3,200

3,400

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

2029

2030

Reserve

MW

Conventional

Clean

Renewable

Load (MW)

Reserve Margin



• The hydro plant Murchisson Falls, with the large capacity development (750 MW) has been included as a candidate for the extended period (2031-2038).

• Generic STPPs (53 MW and 56 MW) OCGTs (57 MW) CCGTs (185 MW) and MSDs (10 MW) that were listed in Module 1C-1200 were added as candidates in the plan.

• Additional CCGT generics were also included to meet the demand adhering to the reliability criteria.


Figure 4-8 Uganda Modified National Expansion Plan by Plant Category

The chart is a visual indication that the system is hydro-dominated with blue bars representing renewable capacity (hydro and 17 MW of Biomass) forming the better part of the capacity bars in every year of the study horizon.

The modified future system has enough reserve to be self-sufficient. The reserve margin oscillates mainly around the 20% mark. When it does drop to 10% the large hydro project Murchisson Falls (750 MW) comes into operation (2032) shooting the reserve up to 40%. The system then does not require any more new plants as the reserve is dropping down towards 20%. In the final two years thermal generics are added to increase the reserve again towards the 20% mark.


0%

10%

20%

30%

40%

50%

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

2,000

2,200

2,400

2,600

2,800

3,000

3,200

3,400

2013

2015

2017

2019

2021

2023

2025

2027

2029

2031

2033

2035

2037

Reserve

MW

Conventional

Clean

Renewable

Load (MW)

Reserve Margin




Table 4-3 Uganda Existing Vs. Modified National Expansion Plan



2013 Base Load TPP 100 105 Tallow CCGT TPP 185 125 Small Hydros HPP 65 Electromaxx TPP -10 Electromaxx TPP -10 Invespro TPP -50 Invespro TPP -50

2014 Peak Load TPP 25 25 Tallow GT TPP 57 57

2016 Small Hydros HPP 32 32 0

2016 Karuma HPP 250 250 Karuma HPP 250 250

2018 Isimba HPP 100 100 Isimba HPP 100 100




2023 Ayago HPP 250 250 Ayago HPP 250 250

2025 Small Hydros HPP 7 7 CCGT Generic TPP 250 250

2028 Ayago HPP 300 250 Ayago HPP 300 250

Namanve TPP -50 Namanve TPP -50

2030 Small Hydros HPP 20 20 0

2031 0 CCGT Generic TPP 50 50

2032 0 Murchisson Falls HPP 750 750


2038 0 Kampala Steam TPP 56 169 Tallow Steam TPP 53 Tallow Diesel TPP 10 CCGT Generic TPP 50


From the comparison of the two totals in the last row in Table 4-3, it is shown that the new plan adds 1,250 MW more generation to the future system than the original plan. However 1,000 of this amount is in the final 8 years. There is a 250 MW increase to the additions in the existing study’s horizon.

Looking at the plan, for the period 2013-2030, the base load, peak load and small hydro plants (249 MW) were replaced by CCGT and OCGT generics (492 MW). With the load forecast in 2030 being 200 MW higher in the new plan, the conclusion that can be made is that the modifications made to the plan were only brought to replace the generics from the existing plan and to cover for the increase in the load forecast.



4.3.4 Investment net present value The investment costs of all future plants in the modified national expansion plan are listed in Tables 5-12 and 6-16 of Module 1C-1200. Using a 10% interest rate, Uganda’s investment net present value in 2013 is split into:


• Thermal: 520.98 MUSD,



• 132 KV double-circuit AC transmission line between Uganda and Kenya with a capacity of 118 MW.

• 132 KV double-circuit AC transmission line between Uganda and Tanzania with a capacity of 59 MW.

• 220 KV double-circuit AC transmission line between Uganda and Kenya with a capacity of 300 MW.

• 220 KV double-circuit AC transmission line between Uganda and Rwanda with a capacity of 250 MW.

The energy generation by fuel category for Uganda, including net exchanges with neighbouring countries, is shown below in Figure 4-9:



Figure 4-9 Uganda Generation by Fuel Category - Modified National Expansion Plan

The system in Uganda is dominated by hydro generation with renewable energy making up more than 90% of the total in the system. This had to be expected since the expansion plan shown in Figure 4-8 was also dominated by hydro capacity additions. With the water in Uganda being abundantly available for electricity generation year-long in the Victoria Lake, all hydro plants operate at more than 90% capacity factor (Module 1C-1200), given that the lake is the natural reservoir used by all the plants located downstream on the river.

Uganda has a great potential to export and utilizes the four interconnections it has with Kenya, Rwanda and Tanzania to good effect. The net exchange is represented in Figure 4-9 by a negative generation in green, peaking at 4,500 GWh in (2032-2034). It does import slightly in the early years (170 GWh in 2015) but on average it exports an amount close to 30 % of its own load. This means that the proposed future Uganda power system is not only self-sufficient but profitable to Uganda and beneficial to the region by providing cheap energy to its neighbours. In addition it is a clean system with close to 98% of its energy made up from renewable generation (Hydro, Biomass) and clean thermal generation (Geothermal). The small remaining portion (2-3%) consists of the conventional thermal resources (Gasoil, Diesel and HFO).


‐4,500

‐3,000

‐1,500

0

1,500

3,000

4,500

6,000

7,500

9,000

10,500

12,000

13,500

15,000

16,500

18,000

19,500

2013

2015

2017

2019

2021

2023

2025

2027

2029

2031

2033

2035

2037

GWh Net Exchange

Conventional

Clean

Renewable



4.4 Ethiopia 4.4.1 Existing national expansion plan The national plan considered for Ethiopia is part of the highlights on the power sector development program done by EEPCo in 2008 [47]. The study period in that plan is from 2009 to 2030. Figure 4-10 presents the expansion plan in a bar chart showing the evolution of the Ethiopia generation capacity by plant category:

Figure 4-10 Ethiopia Existing National Expansion Plan by Plant Category

Ethiopia’s future system is almost entirely renewable. The expansion plan is based only on hydro power plants as no clean or conventional type of capacity is introduced to add to the very small proportion of thermal energy from the existing system (1% in 2030).

The reserve is quite high in the system starting at 130%. It does drop to about 40% and a high reserve is always expected in a hydro system for reliability purposes. A power system with a mix of hydro and thermal is more robust and would require a smaller amount of reserve when less hydro-dependant.

Finally, that plan was developed with the desire for Ethiopia to export. Some plants may have been selected for the sole purpose of selling cheap power to the neighbours which is the main reason why the local reserve is high. That is not in accordance with the required national plan criteria set in this study as national plans have to be developed irrespective of the exchange possibilities, be it exports or imports. Hence the main targets of the modified plan are:

0%

20%

40%

60%

80%

100%

120%

140%

160%

0

1,500

3,000

4,500

6,000

7,500

9,000

10,500

12,000

13,500

15,000

16,500

18,000

19,500

2013

2015

2017

2019

2021

2023

2025

2027

2029

Reserve

MW

Conventional

Clean

Renewable

Load (MW)

Reserve Margin



• Re-optimize the entrance decision and schedule of large hydro projects neglecting the possibility to export. Some plants are likely to get postponed while others may be taken out completely.

• Reduce the level of reserve of the system. This may automatically follow from meeting the previous target.

• Add thermal generics to create a more robust system, less hydro dependant.

• Plan the generation expansion for the remaining years of the study horizon (2031-2038)

4.4.2 Modified national expansion plan In the present study the same load forecast is used. In order to treat the issues highlighted in the existing national expansion plan, the following measures have been taken:

• The large hydro plants (Mandaya, Karadobi and Border) had their entrance schedule carefully studied. There should be at least 5 years separating each plant. Also the need for all three of them has been put in question. Border was deemed unnecessary, being the most expensive of the three in terms of levelized cost. (see Table 5-12 in Module 1C-1200)

• Geothermal developments presented in Module 1C-1200 were introduced to the plan to add thermal capacity to the hydro system

• Additional Geothermal generics (400 MW) and OCGT generics running on diesel (140 MW) were also included to cover for the period 2031-2038 and to solve small deficit issues without adding large hydro plants.

• Hydro plants that were not considered in the original plan were included as candidates.




Figure 4-11 Ethiopia Modified National Expansion Plan by Plant Category

As observed, the system is still hydro dominated (Renewable energy in blue) but now clean and conventional additions have a bigger share, especially in the last period (2031-2038). Clean energy comprising of geothermal developments, in orange, accounts for 17% of the total capacity in 2038, while conventional energy (Diesel OCGTs) in red, provides 11% of the total system installation. The 28% combined share replaces the 1% share from the original plan, helping to drive the reserve level below 20% with the system now less hydro dependant.

The system looks to be self-sufficient and still has a great potential to export in the first half of the study horizon (2013-2026) where its reserve is above 40%, even though exchanges were not considered.



0%

20%

40%

60%

80%

100%

120%

140%

160%

0

1,500

3,000

4,500

6,000

7,500

9,000

10,500

12,000

13,500

15,000

16,500

18,000

19,500

2013

2015

2017

2019

2021

2023

2025

2027

2029

2031

2033

2035

2037

Reserve

MW

Conventional

Clean

Renewable

Load (MW)

Reserve Margin



Table 4-4 Ethiopia Existing Vs. Modified National Expansion Plan



2013 Gibe III HPP 1870 2572 Gibe III HPP 1870 2712

Chemoga Yeda HPP 280 Chemoga Yeda HPP 280 Halele Worabesa HPP 422 Halele Worabesa HPP 422 OCGT Generic TPP 140

2015 Genale 3D HPP 258 258 Genale 3D HPP 258 258

2016 Gibe IV HPP 1468 1468 Gibe IV HPP 1468 1468

2017 Geba I & II HPP 372 372 Geba I & II HPP 372 372

2018 0 Tekeze 2 HPP 275 350 Langano Geo TPP 75

2019 0 OCGT Generic TPP 140 140

2020 Mandaya HPP 2000 2000 0

2021 Baro I HPP 200 862 Baro I HPP 200 300 Gibe V HPP 662 Tendaho Geo TPP 100

2022 Baro II HPP 510 720 Baro II HPP 510 720

Genji HPP 210 Genji HPP 210

2023 0 Gibe V HPP 662 662

2025 Karadobi HPP 1600 1600 0

2028 0 Awash 4 HPP 38 38

2029 Border HPP 1200 1200 Geo Generic TPP 800 800

2030 0 Geo Generic TPP 400 400

2031 0 Mandaya HPP 2000 2000 Abaya Geo TPP 100

2033 0 Corbetti Geo TPP 75 355

OCGT Generic TPP 280

2034 0 Genale 6D HPP 246 846 Geo Generic TPP 600

2035 0 Aleltu East HPP 186 881

Aleltu West HPP 265 Gojeb HPP 150 OCGT Generic TPP 280

2036 0 Karadobi HPP 1600 1700

Tulu Moye Geo TPP 40 Dofan Geo TPP 60

2037 0 OCGT Generic TPP 560 960

Geo Generic TPP 400

2038 0 OCGT Generic TPP 560 960 Geo Generic TPP 400




The new plan adds 5,000 MW more power to the future system. However, the additions in the previously uncovered period (2031-2038) total 7,800 MW with the remaining 8,200 MW coming in the earlier years. Therefore the modified plan reduced the additions before 2031 by 2,800 MW which is 25% of the original additions to the future system. This represents huge savings for the Ethiopians since the new plan adheres to the reliability criteria as well.

Changes include:

• Mandaya and Karadobi, with a total of 3,600 MW, pushed 11 years into the future, out of the original horizon.

• Gibe V (600 MW) postponed 2 years.

• Border (1,200 MW) taken out of the plan.

• Geothermal and OCGT generics (a total of 1,500 MW) distributed throughout the study horizon to fill deficit gaps and meet reserve requirements.

For the uncovered period, previously unused hydro projects were selected in parallel with more thermal generics. The 7,800 MW are just enough to meet the demand within the criteria and maintain a level of reserve between 15% and 20%.

4.4.4 Investment net present value The investment costs of all future plants in the modified national expansion plan are listed in Tables 5-12 and 6-16 of Module 1C-1200. Using a 10% interest rate, Ethiopia’s investment net present value in 2013 is split into:




4.4.5 Interconnections and energy generation The new expansion plan was simulated with SDDP in order to obtain the generation by fuel type. The following committed interconnections were considered in the simulation:

• 220 KV double-circuit AC transmission line between Ethiopia and Sudan with a capacity of 200 MW.

• 220 KV single-circuit AC transmission line between Ethiopia and Djibouti with a capacity of 180 MW but a transfer limit of 700 GWh/year.

The energy generation by fuel category for Ethiopia, including net exchanges with neighbouring countries, is shown below in Figure 4-12:



Figure 4-12 Ethiopia Generation by Fuel Category - Modified National Expansion Plan

Just like the expansion plan was hydro dominated, the energy generation is almost entirely renewable (hydro, wind). The blue bars representing the renewable sources provide 99% of the energy in the early years. This proportion drops as more geothermal generics are added but it still remains above 90%. Clean energy (geothermal) makes up most of the remaining 10% while Conventional thermal plants (Diesel OCGTs) produce only 1%.

The system is self-sufficient, clean and even beneficial to the region as Ethiopia exports more than 2,300 GWh (3% of its load) in 2038 to Djibouti and Sudan. This is almost 95% of the maximum energy it can export with the existing interconnections.


4.5 Sudan 4.5.1 Existing national expansion plan The national plan considered for Sudan is the Long-Term Power System Planning Study (LTPSPS) conducted by Parsons Brinckerhoff for the Sudan National Electricity Corporation (NEC) in 2007 [30]. The study period in that plan is from 2007 to 2030. Figure 4-13 presents the expansion plan in a bar chart showing the evolution of the Sudan generation capacity by plant category:

‐5,000

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

50,000

55,000

60,000

65,000

70,000

2013

2015

2017

2019

2021

2023

2025

2027

2029

2031

2033

2035

2037

GWh Net Exchange

Conventional

Clean

Renewable



Figure 4-13 Sudan Existing National Expansion Plan by Plant Category

The expansion plan focuses mostly on conventional types of thermal plants. The red bar grouping Crude STPPs, Coal STPPs and Gasoil CCGTs and OCGTs, is around 70% of the total capacity throughout the horizon. The remaining 30% are all hydro, i.e. renewable energy in blue.

Due to the new updated demand forecast, the system is over-installed from the start with close to 230% of reserve in 2013. It does drop almost continuously but it is still at 50% in 2030 which is an elevated margin for a system that is thermally dominated.

Finally, the load forecast used in the available plan is a much higher figure than the one used in the present study and drawn in Figure 4-13. This further emphasizes the need for a new plan.

The new plan needs to treat the following issues:

• Review the construction progress and status of committed projects to get the correct picture for the existing system in 2013. This will help reduce the starting reserve margin.

• Re-optimize the entrance schedule of the hydro plants and the thermal generic additions to further reduce the reserve, accounting for the new demand forecast.

• Plan the generation for the period 2031-2038, using unselected projects and, if needed, more generics.

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

200%

220%

240%

01,0002,0003,0004,0005,0006,0007,0008,0009,00010,00011,00012,00013,00014,00015,00016,00017,00018,00019,00020,00021,00022,000

2013

2015

2017

2019

2021

2023

2025

2027

2029

Reserve

MW

Conventional

Renewable

Load (MW)

Reserve Margin



4.5.2 Modified national expansion plan After consulting the power system profile on the NEC website [68], it was discovered that the following projects, proposed for the period leading up to January 2013 by the LTPSPS were not even commissioned yet:

• Port Sudan STPP 405 MW

• El Bagair STPP 540 MW

• Garri 3 STPP 540 MW

• New GT 60 MW

• New LSD 272 MW

• New Coal STPP 143 286 MW

• New Coal STPP 380 380 MW

• Rumela HPP 30 MW

These plants combine for a total of 2,513 MW. The existing national plan considers them as existing in the year 2013, which creates an over-installed system when considering the new reduced load forecast. In the modified plan, these plants have been considered as candidates starting from 2013.

The hydro plants entrance schedule was also reshuffled adequately.

Additional CCGT and STPP generics were introduced to the plan in the same proportion as proposed in the LTPSPS, to cover for the load in 2031-2038.




Figure 4-14 Sudan Modified National Expansion Plan by Plant Category

With the 2013 existing system now corrected, there is a noticeable drop in the starting reserve from 230% to 90%. The reserve then decreases even further to settle around 5% in 2038, resolving the issue of over-instalment.

The system is still thermally dominated, though now the proportion of conventional sources in 2013 is smaller, with the postponement of some project. In that year the system is 55% made up of conventional thermal capacity (Gasoil OCGTs and CCGTs, Crude and Coal STPPs, LSDs) but that share increases to 78% in 2038 since the expansion plan has much more thermal options than hydro options. Renewable energy constitutes the other half of the capacity and drops from 45% 2013 to 22% in 2038. With a low proportion in hydro, the system can meet the reliability criteria with only 5% reserve. That reserve being 1,180 MW in 2038, it is more than twice the size of the biggest thermal plant used (570 MW Coal STPP).



0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

200%

220%

240%

01,0002,0003,0004,0005,0006,0007,0008,0009,000

10,00011,00012,00013,00014,00015,00016,00017,00018,00019,00020,00021,00022,000

2013

2015

2017

2019

2021

2023

2025

2027

2029

2031

2033

2035

2037

Reserve

MW

Conventional

Renewable

Load (MW)

Reserve Margin



Table 4-5 Sudan Existing Vs. Modified National Expansion Plan



2013 Shereiq HPP 315 315 0

2014 New CCGT 208 TPP 208 208 0

2015 New Coal STPP 380 TPP 380 631 Khartoum STPP U1-2 TPP -55 -89 Low Dal HPP 340 Khartoum GT U1-2 TPP -34 Khartoum STPP U1-2 TPP -55 Khartoum GT U1-2 TPP -34

2016 Kajbar HPP 300 300 Rumela HPP 30 173

New Coal STPP 143 TPP 143

2017 New CCGT 208 TPP 208 446 Sabaloka HPP 90 233 New Crude STPP 238 TPP 238 New Coal STPP 143 TPP 143

2018 New Coal STPP 380 TPP 380 380 Port Sudan TPP 405 405

2019 New CCGT 208 TPP 208 731 New Coal STPP 380 TPP 380 380

New Crude STPP 238 TPP 238 Dagash HPP 285

2020 New Crude STPP 475 TPP 950 1670 Shukoli HPP 210 690

Fula I HPP 720 Lakki HPP 210 El Bagair U1-2 TPP 270

2021 New Coal STPP 570 TPP 570 570 El Bagair U3-4 TPP 270 270

2022 Shukoli HPP 210 210 Fula I HPP 720 1125

Garri 3 STPP U1-3 TPP 405

2023 New CCGT 342 TPP 342 240 Bedden HPP 400 433 Khartoum STPP U3-4 TPP -102 Garri 3 STTP U4 TPP 135 Khartoum STPP U3-4 TPP -102

2024 New GT 60 TPP 60 270 Shereiq HPP 315 1035

Lakki HPP 210 Low Dal HPP 340 New Coal STPP 380 TPP 380

2025 New Crude STPP 475 TPP 475 475 Dagash HPP 285 617

New GT 60 TPP 60 New LSD 272 TPP 272

2026 New CCGT 342 TPP 342 742 Kajbar HPP 300 850

Bedden HPP 400 New CCGT 208 TPP 208 New CCGT 342 TPP 342

2027 New CCGT 342 TPP 684 1254 New Coal STPP 570 TPP 570 778

New Coal STPP 570 TPP 570 New CCGT 208 TPP 208

2028 Garri 1 CCGT TPP -164 -164 New CCGT 208 TPP 208 1070 New CCGt 456 TPP 456 New Coal STPP 570 TPP 570 Garri 1 CCGT TPP -164

2029 New CCGT 456 TPP 912 912 New CCGT 456 TPP 456 798

New CCGT 342 TPP 342

2030 New CCGT 456 TPP 912 912 New CCGT 456 TPP 456 456

2031 0 New GT 60 TPP 60 991 New CCGT 456 TPP 456 New Crude STPP 475 TPP 475





2032 0 New Crude STPP 238 TPP 238 713 New Crude STPP 475 TPP 475

2033 0 New Coal STPP TPP 570 1501

New CCGT 456 TPP 456 New Crude STPP 475 TPP 475

2034 0 New Coal STPP 380 TPP 380 1386

New CCGT 208 TPP 208 New CCGT 342 TPP 342 New CCGT 456 TPP 456

2035 0 New Coal STPP 570 TPP 570 778

New CCGT 208 TPP 208

2036 0 New CCGT 208 TPP 208 550 New CCGT 342 TPP 342

2037 New Crude STPP 238 TPP 238 1625

New CCGT 456 TPP 456 New CCGT 456 TPP 456 New Crude STPP 475 TPP 475

2038 0 New Crude STPP 475 TPP 475 475

Total Existing Plan 10,102 Modified Plan 17,243

The new plan adds 7,000 MW more than the original plan. However, it introduces 8,000 MW in the period 2031-2038. Hence the existing plan adds 1,000 MW more in the period 2013-2038. Taking into consideration that the existing system in the modified plan is 2,500 MW smaller, there is a reduction of 3,500 MW in capacity by 2030. This is a good indicator of the over-instalment present in the original plan and of the savings this new plan would bring to the Sudanese system.

The entire plan has been reshuffled, for both hydro and thermal projects. In addition, extra generic plants were added, using the same types and sizes and keeping the proportion of STPPs to CCGTs almost intact. The old plan would have probably been less changed had the demand forecast been kept the same. However the new forecast was the main driver behind this re-optimization.

4.5.4 Investment net present value The investment costs of all future plants in the modified national expansion plan are listed in Tables 5-12 and 6-16 of Module 1C-1200. Using a 10% interest rate, Sudan’s investment net present value in 2013 is split into:




4.5.5 Interconnections and energy generation The new expansion plan was simulated with SDDP in order to obtain the generation by fuel type. The following committed interconnection was considered in the simulation:



• 220 KV double-circuit AC transmission line between Sudan and Ethiopia with a capacity of 200 MW.

The energy generation by fuel category for Sudan, including net exchanges with Ethiopia, is shown below in Figure 4-15:

Figure 4-15 Sudan Generation by Fuel Category - Modified National Expansion Plan

Renewable energy (hydro) in Sudan is more accentuated in the early years (83% in 2013). However with the development of more STPPs and CCGTs, Conventional thermal energy (Oil, Coal) starts taking over as renewable generation’s proportion drop to 25% while the conventional generation increases from 17% to 75%. There are no clean thermal sources in Sudan.

Exports from Ethiopia do not play a big part as they constitute only 1.5% of the load of Sudan in 2038. This proves the self-sufficiency of the system. However, with only 25% of renewable generation and no clean thermal generation that plan would have environmental issues in the future. The possibility of importing NG needs to be studied, especially with their neighbours Egypt having a big reserve of that commodity.


4.6 Egypt 4.6.1 Existing national expansion plan The national plan considered for Egypt is the national generation expansion plan done by the Egypt Electricity Holding Company (EEHC) in 2009 [59]. The study period in that plan is

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from 2009/2010 to 2026/2027. Figure 4-16 presents the expansion plan in a bar chart showing the evolution of the Egypt generation capacity by plant category:

Figure 4-16 Egypt Existing National Expansion Plan by Plant Category

Renewable energy has a minor role in Egypt’s expansion plan. In the proposed future system, it makes up about 15% of the total capacity. New wind farms are included in the expansion plan (Zafarana) and some solar development as well. However, only one small hydro plant is added (Assiut).

The plan focuses on a mix of HFO STPPs and NG CCGTs. The clean energy is a little less than 40% of the future system while the conventional thermal plants are a little over 45% of the total capacity in 2038.

Nuclear energy plays a part with 5,000 MW being included in the plan to form 15% of the clean thermal energy. The nuclear development follows a [1,000 MW / 2 years] trend. The EEHC desires to continue this trend after the expiration of this plan.

The reserve margin is low in the first few years of the expansion (less than 10%). It does however grow to exceed 25% by 2027. With the load forecast in the present study being almost the same as the one used in the existing national plan, the only issues that need to be dealt with by the new plan are:

• Add capacity in the form of generic thermal plants in the early years to increase the reserve in 2013.

• Cover the remaining 11 years of the expansion using more thermal generics, similar to the ones used in the existing plan.

• Continue the development of nuclear plants following the same trend.

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4.6.2 Modified national expansion plan The expansion plan was subject to the following modifications and additions to solve the issues highlighted in the existing one:

• A CCGT plant running on NG (1,500 MW) was added in 2013 to solve the reserve problem.

• NG CCGTs (250 MW units) and HFO STPPs (650 MW units) were employed to meet the load for the period (2028 – 2038).

• Nuclear generics (1,000 MW units) were added every other year to follow the desired nuclear development trend, with Egypt having the capability to introduce Nuclear plants to its system.


Figure 4-17 Egypt Modified National Expansion Plan by Plant Category

The issue of low reserve in 2013 has been resolved with the reserve now above 10% in that year and exceeds 20% by 2014. The added CCGT has done the required effect.

The renewable proportion is still small with no new renewable projects introduced to the plan. And now with only thermals added after 2027, the proportion drops from 14% to 9%. The big change in proportions has been the increase in clean energy which is now at 50% in 2038 while conventional energy is at 41%.

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The expansion plan uses to great effect Egypt’s resources in NG and its capability to install NPPs, in order to reduce the system’s dependence on expensive polluting fuel oils. And with a reserve of more than 25% of the system load, the future system is deemed self-sufficient. However with 40% of its generation coming from expensive fuels, it may decide to import cheaper power if connected to Ethiopia through Sudan, especially during peak-load periods.


4.6.3 Existing Vs. Modified national expansion plan Both the existing and modified plans are displayed next in Table 4-6 to compare and inspect the changes. Those changes, whether in the date of entry of a plant, or when a totally new plant is introduced to the plan, are highlighted in bold, whereas any retirement is in italic.

Table 4-6 Egypt Existing Vs. Modified National Expansion Plan



2013 Giza North TPP 1000 1676 Giza North TPP 1000 3176 Abu Kir TPP 650 Abu Kir TPP 650 Banha TPP 750 Banha TPP 750 Wind Farms WPP 320 Wind Farms WPP 320 Solar Units SPP 50 Solar Units SPP 50 Shabab TPP -100 CCGT Generic TPP 1500 Sharm El Sheikh TPP -178 Shabab TPP -100 El Huraghda TPP -143 Sharm El Sheikh TPP -178 Mahmoudia TPP -50 El Huraghda TPP -143 Karmouz TPP -23 Mahmoudia TPP -50 Kuriemat 3 TPP -300 Karmouz TPP -23 Nubaria 3 TPP -300 Kuriemat 3 TPP -300 Nubaria 3 TPP -300

2014 Ain Sokhna TPP 1300 4150 Ain Sokhna TPP 1300 4150

Qassasen TPP 1250 Qassasen TPP 1250 Giza North TPP 500 Giza North TPP 500 Suez TPP 650 Suez TPP 650 Wind Farms WPP 450 Wind Farms WPP 450

2015 Qassasen TPP 250 2702 Qassasen TPP 250 2702

Helwan South TPP 1300 Helwan South TPP 1300 Qena TPP 650 Qena TPP 650 Assiut HPP 25 Assiut HPP 25 Wind Farms WPP 700 Wind Farms WPP 700 Solar Units SPP 50 Solar Units SPP 50 Port Said TPP -73 Port Said TPP -73 El Seiuf TPP -200 El Seiuf TPP -200

2016 Qena TPP 650 2500 Qena TPP 650 2500

Damietta West 1,2 TPP 1250 Damietta West 1,2 TPP 1250 Wind Farms WPP 700 Wind Farms WPP 700 Wadi Hof TPP -100 Wadi Hof TPP -100

2017 Helwan South TPP 1300 3400 Helwan South TPP 1300 3400

Damietta West 1,2 TPP 250 Damietta West 1,2 TPP 250 Safaga TPP 650 Safaga TPP 650 Wind Farms WPP 1200 Wind Farms WPP 1200

2018 Damietta West 1,2 TPP 1000 3160 Damietta West 1,2 TPP 1000 3160

Safaga TPP 650 Safaga TPP 650 Dabaa Nuclear NPP 1000 Dabaa Nuclear NPP 1000 Wind Farms WPP 600 Wind Farms WPP 600 Assiut TPP -90 Assiut TPP -90




Plant Name Type MW S/T (MW) Plant Name Type MW S/T (MW) 2019 Damietta West 1,2 TPP 500 2250 Damietta West 1,2 TPP 500 1750

Steam Units TPP 650 Steam Units TPP 650 Combined Cycle TPP 500 Wind Farms WPP 600 Wind Farms WPP 600

2020 Steam Units TPP 1950 3105 Steam Units TPP 1950 3105

Combined Cycle TPP 750 Combined Cycle TPP 750 Wind Farms WPP 600 Wind Farms WPP 600 Damanhour TPP -195 Damanhour TPP -195


Combined Cycle TPP 1250 Combined Cycle TPP 1250 Dabaa Nuclear TPP 1000 Dabaa Nuclear TPP 1000 Wind Farms WPP 600 Wind Farms WPP 600


Combined Cycle TPP 1000 Combined Cycle TPP 1000 Wind Farms WPP 100 Wind Farms WPP 100


Combined Cycle TPP 1250 Combined Cycle TPP 1250 Dabaa Nuclear TPP 1000 Dabaa Nuclear TPP 1000 Wind Farms WPP 100 Wind Farms WPP 100




Combined Cycle TPP 1250 Combined Cycle TPP 1250 Dabaa Nuclear TPP 1000 Dabaa Nuclear TPP 1000 Wind Farms WPP 100 Wind Farms WPP 100 Cairo West TPP -350 Cairo West TPP -350




Combined Cycle TPP 250 Combined Cycle TPP 250 Dabaa Nuclear TPP 1000 Dabaa Nuclear TPP 1000 Wind Farms WPP 100 Wind Farms WPP 100 Abu Sultan TPP -600 Abu Sultan TPP -600 Kafr El Dawar TPP -440 Kafr El Dawar TPP -440

2028 Ataka TPP -900 -900 Ataka TPP -900 3800

CCGT Generic TPP 2750 Steam Generic TPP 1950

2029 Shoubra El Kheima TPP -1260 -1260 Shoubra El Kheima TPP -1260 4440

CCGT Generic TPP 2750 Steam Generic TPP 1950 Nuclear Generic NPP 1000

2030 Talkha TPP -290 -290 Talkha TPP -290 4410



Steam Generic TPP 1950 Nuclear Generic NPP 1000

2032 Damanhour Ext. TPP -300 -1211 Damanhour Ext. TPP -300 3489

Abu Kir TPP -911 Abu Kir TPP -911 CCGT Generic TPP 2750




Plant Name Type MW S/T (MW) Plant Name Type MW S/T (MW) Steam Generic TPP 1950



2034 Damietta TPP -1200 -1200 Damietta TPP -1200 3500


2035 0 Combined Cycle TPP 500 6200

CCGT Generic TPP 2750 Steam Generic TPP 1950 Nuclear Generic NPP 1000

2036 Cairo West Ext. TPP -660 -2228 Cairo West Ext. TPP -660 2722

Cairo South 1 TPP -510 Cairo South 1 TPP -510 Cairo South 2 TPP -165 Cairo South 2 TPP -165 Talkha 210 TPP -420 Talkha 210 TPP -420 Mahmoudia TPP -316 Mahmoudia TPP -316 Damanhour TPP -157 Damanhour TPP -157 CCGT Generic TPP 3000 Steam Generic TPP 1950




Steam Generic TPP 1950


As already mentioned, the plan was not modified in 2013-2027. Only a small addition was brought to the system in the form of a generic CCGT of 1,500 MW. The remaining 57,000 MW additions were introduced in the uncovered period. The trend used is 2,750 MW of CCGT and 1,950 MW of STPP every year with 1,000 MW of nuclear every other year. All the retirements were respected.

4.6.4 Investment net present value The investment costs of all future plants in the modified national expansion plan are listed in Tables 5-12 and 6-16 of Module 1C-1200. Using a 10% interest rate, Egypt’s investment net present value in 2013 is split into:

• Hydro: 142.59 MUSD; and,


for a total of 73,298.69 MUSD, which means thermal investments make up 99.9% of the total against 0.1% for the hydro investments. Investments will be compared in the next section to the ones in the regional plan, in order to highlight the benefits of interconnections.

4.6.5 Interconnections and energy generation The new expansion plan was simulated with SDDP in order to obtain the generation by fuel type. The following existing interconnections were considered in the simulation:

• A 400 KV bipolar HVDC transmission line between Egypt and Jordan, going all the way to Syria, with a capacity of 600 MW.



• A 220 KV double-circuit AC transmission line between Egypt and Libya with a capacity of 240 MW.

However, based on historical data from the latest annual report produced by the EEHC, a total of 700 GWh of net yearly exports were simulated since the Jordanian, Syrian and Libyan systems were not simulated individually.

The energy generation by fuel category for Egypt, including net exports to Jordan, Syria and Libya, is shown below in Figure 4-18:

Figure 4-18 Egypt Generation by Fuel Category - Modified National Expansion Plan

It is clear from Figure 4-18 that the system’s generation is dominated by clean thermal energy. From 58% in 2013, the proportion increases to 73% in 2038. Conventional fuels produce 30% in 2013 but their output is only 21% of the total generation in 2038. Renewable energy makes up the rest. These proportions are caused by the low price of nuclear and NG generation compared to HFO and the unavailability of enough renewable energy. The system is nevertheless clean with up to 80% coming from clean thermals and renewable energy combined.

Net exchanges don’t appear on the graph as the 700 GWh exports to neighbouring countries are too small to be visible with a much higher scale. With the available energy not completely used (conventional sources are working at a 30% CF only) the system has proven to be self-sufficient, a conclusion that was expected given the level of reserve attained with the expansion plan.


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4.7 Burundi, Eastern DRC and Rwanda 4.7.1 Regional coordination In this present study, the modified national expansion plans were developed for isolated systems for reasons defined previously such as having a self-sustained system. However in the case of Burundi, Eastern DRC and Rwanda, the national plans were developed in coordination with each other for the following reasons:

‐ There was no recently available master for individual countries. Studies in the past few years proposed regional plans.

‐ The three countries share the generation from four hydro plants (the Ruzizi plants), with two of them being future projects (Ruzizi 3 and 4).

‐ The three countries share the generation from a future thermal plant, the second installment of the Lake Kivu methane gas project (200 MW).

‐ The countries have a history of cooperation and power transfer that is preferred to be respected.

Hence the new national expansion plan for Burundi, Eastern DRC and Rwanda presented in this section takes into account exchanges between the three countries throughout the study period.

4.7.2 Shared Projects The three countries have an agreement to share the generation from several projects located near the borders:

• Ruzizi hydro plants

There are currently 2 existing hydro plants on the Ruzizi river:

‐ Ruzizi 1: 30 MW; It is equally shared between Eastern DRC and Rwanda (15 MW each) ‐ Ruzizi 2: 36 MW; It is equally shared between the three countries (12 MW each)

In addition there are two projects which are expected to get selected in the national expansion plan:

‐ Ruzizi 3: 147 MW; It will be equally shared between the three countries (49 MW each) ‐ Ruzizi 4: 288 MW; It will be equally shared between the three countries (96 MW each)

Geographically, the Ruzizi projects are located in Eastern DRC. However, Ruzizi 2, (and in the future Ruzizi 3 and 4), are not directly connected to the Eastern DRC network. These plants are connected to a bus (Mururu 2) in Rwanda, and from there, the shares of Eastern DRC and Burundi are exported. Hence the transfer capacities from Rwanda to Burundi and Eastern DRC are effectively deducted by the reserved shares for the Ruzizi projects.

• Lake Kivu Methane gas project

In Rwanda, there are plans to develop Methane gas plants on Lake Kivu. The first part of the project (100 MW) is entirely reserved for Rwanda. However, the second part is of 200 MW and is equally shared between the three countries (66.67 MW each). Again, the transfer capacities from Rwanda to Burundi and Eastern DRC are effectively deducted by the reserved shares for the Lake Kivu projects.



4.7.3 New national expansion plans As explained previously, the national plans for the three countries were developed in a coordinated manner. When needed, thermal generic plants (100 MW Diesel plants) were added to the systems. It should be noted that each Ruzizi plant had only one commissioning date and its three portions were added to each country’s expansion plan at the same date. The same was done for the Lake Kivu project.

The new national expansion plans are shown next in Figures 4-19 to 4-21 in the form of bar charts representing the available capacity by plant category:

Figure 4-19 Burundi New National Expansion Plan by Plant Category

As shown in Figure 4-19 the future system in Burundi observes two main trends: The Renewable share is high in 2013 (hydro system) making up 89% of the generation. This share drops along the study horizon to 25% by 2038 as very few hydro additions are introduced. In contrast, the share of conventional fuel plants (diesel) increases from 11% to 67% by 2038 with the addition of about 600 MW of generics. The Lake Kivu share of Burundi added in 2033 and representing Burundi’s only source of clean thermal capacity, constitutes only 8% of the 2038 system.

The system’s reserve is negative from the start of the study horizon but experiences a drastic increase in 2016 with the first 100 MW of generic diesel being added. It then oscillates around 60% to finally settle at 35%. With the plans of the three countries being developed cooperatively, the negative reserve in the beginning is not a major problem as it was deemed preferable to use imports from Eastern DRC’s new projects instead of having Burundi start adding generics in the first couple of years.

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Figure 4-20 Eastern DRC New National Expansion Plan by Plant Category

As shown in Figure 4-20, the future system in Eastern DRC is dominated by renewable plants (Hydro). Hydro capacity makes up around 85% of the 2013 system with the remaining 15% being conventional thermal plants (diesel). The expansion plan is made up entirely of hydro plants up to 2033 which increases the portion of renewable to 96% by the end of 2032. When Eastern DRC’s share of the Kivu project is added in 2033, the system configuration changes slightly, with renewable capacity making up 83% of the system, 12% being clean energy and the remaining 4% represent the existing diesel generation (conventional thermal).

The system’s reserve is high in the period 2017-2027, reaching a peak in 2027 of 197%. It then drops to about 90% (with a small surge in 2033 when the Lake Kivu plant is added). The reason behind this high reserve is the coordinated national plans with Rwanda and Burundi. Eastern DRC is seen as the main exporter and has the most resources and potential hydro projects. These projects are developed early to help the systems of Burundi and Rwanda. These two countries then start to develop generic diesels when the load in Eastern DRC increases enough to reduce substantially the capacity available for exports from the Eastern DRC (i.e. starting in 2028).

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Figure 4-21 Rwanda New National Expansion Plan by Plant Category

As shown in Figure 4-21, the renewable energy in Rwanda makes up close to 30% of the 2013 system. That figure drops to 20% as no new hydro plants are introduced but readjusts when Ruzizi 3 comes online in 2024 and then again Ruzizi 4 in 2027. With few other renewable additions, the system’s renewable capacity settles at around 25% by 2038. The main source of generation in Rwanda’s expansion plan is however the conventional type of thermal plants. Diesel generic are added throughout the study horizon to increase the system’s conventional fuels capacity from 20% in 2013 to 60 % in 2038, with about 600 MW of new plants. The 100 MW of methane gas from Lake Kivu representing the clean fuels in 2013 had a bigger impact (50%) but with only a further 67 MW added before 2038, the clean fuels share drops to 15% of the Rwanda capacity.

The system’s reserve experiences a huge drop in the period (2013-2021) from 120% to -10% but then readjusts and settles around 35%. Since the plans of the three countries were developed cooperatively, the negative reserve is not a major issue; no new plants were added in that period because other plants were added in Eastern DRC at the same time and imports from Eastern DRC were preferred to generation additions.

The complete set of Tabulated values behind these charts can be found in Appendix C.

The following tables show the capacity additions for Burundi, Eastern DRC and Rwanda:

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Table 4-7 Burundi New National Expansion Plan

Year New Plan (NP)

Plant Name Type MW S/T (MW)

2016 Kabu 16 HPP 20 120 Generic Diesel TPP 100

2021 Generic Diesel TPP 100 100

2024 Ruzizi III (1/3 Share) HPP 49 149

Generic Diesel TPP 100

2027 Ruziz IV (1/3 Share) HPP 96 96

2029 Jiji 03 HPP 16 16



2033 Mpanda HPP 10 77 Kivu Gas 2 (1/3 Share) TPP 67


Total New Plan 858

Table 4-8 Eastern DRC New National Expansion Plan

Year New Plan (NP)


2014 Piani Mwanga HPP 34 34

2017 Babeda I HPP 50 78 Semliki HPP 28

2018 Bengamisa HPP 48 48

2023 Mugomba HPP 40 40



2033 Kivu Gas 2 (1/3 Share) TPP 67 67

Total New Plan 409



Table 4-9 Rwanda New National Expansion Plan

Year New plan (NP)


2013 Kivu Gas 1 TPP 100 100







2033 Nyabarong HPP 28 95 Kivu Gas 2 (1/3 Share) TPP 67


2037 Biomass (peat) TPP 50 150

Generic Diesel TPP 100

Total New Plan 989.8

4.7.4 Investment Net Present Value The investment costs of all future plants in the new national expansion plans are listed in Tables 5-12 and 6-16 of Module 1C-1200. Using a 10% interest rate, the investments net present value (NPV) of the three countries in 2013 are:

Table 4-10 2013 Investment NPV for Burundi, Eastern DRC and Rwanda

Country Total NPV Hydro NPV Thermal NPV

MUSD MUSD % of Total MUSD % of Total

Burundi 474.87 134.28 28.3% 340.59 71.7%

Eastern DRC 395.18 377.14 95.4% 18.04 4.6%

Rwanda 680.18 90.64 13.3% 589.55 86.7%

Region 1,550.23 602.06 38.8% 948.17 61.2%

From Table 4-10, It can be seen that the bulk of the investment in Eastern DRC is in hydro projects (95%) while for Rwanda and Burundi the money goes in thermal projects (86% and 71% respectively).

4.7.5 Interconnections and energy generation The new expansion plans were simulated with SDDP in order to obtain the generation by fuel category. For that purpose, all the existing interconnections of those countries with each other as well as interconnections with other countries in the present study were considered. In addition, committed interconnections were included. These existing and committed interconnections are:

• 70 KV Existing double-circuit AC transmission line between Rwanda and Eastern DRC with a capacity of 52 MW.



• 110 KV Existing double-circuit AC transmission line between Rwanda and Eastern DRC with a capacity of 100 MW.

• 70 KV Existing double-circuit AC transmission line between Burundi and Eastern DRC with a capacity of 45 MW. Will be upgraded to to 110 KV double circuit AC, with a capacity of 100 MW.

• 110 KV Existing double-circuit AC transmission line between Rwanda and Burundi with a capacity of 100 MW.

• 220 KV Committed double-circuit AC transmission line between Rwanda and Uganda with a capacity of 250 MW, to come online in 2014.

• 220 KV Committed single-circuit AC transmission line between East DRC and Rwanda with a capacity of 370 MW, to come online in 2014.

• 220 KV Committed single-circuit AC transmission line between East DRC and Burundi with a capacity of 330 MW, to come online in 2014.

In addition to those existing and committed interconnections, and for the purpose of providing enough transfer capacity to channel the power from the shared future projects to the 3 countries, interconnections projects proposed in other studies were considered and interconnection planning was conducted to get these lines online when needed:

• 220 KV single-circuit AC transmission line connecting Burundi and Rwanda to Tanzania, through the Rusumo Falls project with a capacity of 350 MW from the project towards Tanzania, a 280 MW portion from the project to Rwanda and a 320 MW portion to Burundi. Will be needed in 2016.

• 220 KV Committed single-circuit AC transmission line between Rwanda and Burundi with a capacity of 330 MW, Will be needed in 2016.

The following figure shows all the interconnections considered:

Figure 4-22 Interconnections in the Burundi. Eastern DRC, Rwanda Region



The energy generation by fuel category for the three countries, including net exchange in between them, as well as with Uganda and Tanzania, is shown next. It should be noted that the exchanges in the three figures below do not include the shared projects as these are considered as part of the generation for the three countries.

Figure 4-23 Burundi Generation by Fuel Category - New National Expansion Plan

As shown in Figure 4-22, Burundi’s generation is mostly renewable in the first 8 years, where more than 80% of the energy fed to the system is from hydro plants. However as diesel generics are developed and hydro development is minimal (except for the Ruzizi projects), the share of hydro slowly drops to 33% by 2038 while generation from conventional fuel plants reaches its peak in 2032 at 51% and provides 36% in 2038. That drop in conventional fuels in the last 5 years from 51% to 36% coincides with the introduction of the clean fuel plant in Lake Kivu in 2033. The Generation from that plant is around 30% in 2038. The Burundi system is therefore highly dependent on thermal energy however half of that energy is from clean fuels, which when added to the renewable gives Burundi two thirds of its energy from clean sources.

The system of Burundi imports a substantial amount of energy, making up 40% of the load in 2015 and is constantly around the 25% mark until 2032. In 2033 Burundi’s share of the Lake Kivu project is added to its system and its dependence on imports drops. Its 2038 imports are only 10% of its load.

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Figure 4-24 Eastern DRC Generation by Fuel Category - New National Expansion Plan

As shown in Figure 4-23, Eastern DRC is highly dependent on hydro generation. The renewable energy’s share of the generation is above 95% and even close to 100% up until the end of 2032. It drops to 80% in the latter years when the lake kivu project comes online and takes about 20% of the generation in Eastern DRC. The system is totally clean with almost 0% generation from conventional fuels throughout the study horizon.

Eastern DRC is a major exporter in the region as can be observed by the net exchange values in the negative part of the chart. The exports peak at more than double the load in 2018 and stay above 150% of the load until 2028. Then with no new additions in the system until the Lake Kivu project is added in 2033, the exports drop to 75% of the load in 2038. In absolute terms however, they stay close to their peak of 1000 GWh.

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Figure 4-25 Rwanda Generation by Fuel Category - New National Expansion Plan

As shown in Figure 4-24, in Rwanda the generation is almost equally shared between renewable (hydro and biomass), clean fuels (methane) and conventional fuels (Diesel). In the first few years there is almost no diesel generation, but as the development of generics is progressing, the share of conventional generation increases from 7% in 2022 to 36% in 2038, peaking at 46% in 2031. For the clean fuels, with Rwanda the sole benefactor of the first Kivu project (100 MW), 68% of the generation is from methane in 2013. This figure drops to 39% in 2038, with a late surge to 55% in 2033 when the second Kivu project is added. Renewable energy takes up the rest of the country’s generation with 31% in 2013 and hovering around 25%, until 2038. Just like in Burundi, the system has two thirds of its generation from clean sources.

Rwanda exports some energy in the first 4 years but then starts to import from Eastern DRC, Uganda and Tanzania at around 30% of its load in 2017. The imports are still substantial at the end of the study period, even after all the generics are added. In 2038, Rwanda imports 20% of its load.

The complete set of tabulated values for the data behind the charts can be found in Appendix C.

‐250

0

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4.8 Djibouti 4.8.1 Existing national expansion plan The national plan considered for Djibouti is the Least Cost Electricity Master Plan (LCEMP) conducted by Parsons & Brinckerhoff for the World Bank in 2009 [30]. The study period in that plan is from 2009 to 2035. Figure 4-26 presents the expansion plan in a bar chart showing the evolution of the Djibouti generation capacity by plant category:

Figure 4-26 Djibouti Existing National Expansion Plan

The Plan is made up of thermal plants only with conventional thermal capacity being dominant. It makes up 100% of the future system in 2013 but drops to 76% by 2038. That drop is met by an increase in clean thermal capacity (from 0 to 24%) due to the introduction of geothermal plants.

The reserve is oscillating and settles around 20% which is acceptable for a thermal system. With the load practically unchanged in this present study, there doesn’t seem to be any issue to deal with, except for the expansion till 2038. The system might not need any extra generation.

The existing national plan can be examined year by year, plant by plant in the following table:

0%

10%

20%

30%

40%

0153045607590

105120135150165180195210225240255270285

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2015

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2029

2031

2033

2035

Reserve

MW

Clean

Conventional

Load (MW)

Reserve Margin



Table 4-11 Djibouti Existing National Expansion Plan

Year Existing Plan (EP)


2013 Diesel HFO 12 MW TPP 24 24


2015 Diesel HFO 7 MW TPP 7 22 Gas Turbine 15 MW TPP 15

2016 Geothermal 20 MW TPP 20 20




2031 Diesel HFO 7 MW TPP 7 -3

Diesel HFO 12 MW TPP 12 Boulaos TPP -22

2032 Boulaos TPP -9 -9



Boulaos TPP -7

2035 Diesel HFO 7 MW TPP 7 -6 Boulaos TPP -13

Total Existing Plan 137

A total of 137 MW of additions are introduced to the plan between 2013 and 2035. The most notable of those additions are the three 20 MW Geothermal plants (2016, 2019 and 2022) that provide some amount of clean energy to the system. The rest are all HFO Diesel plants bar one 15 MW OCGT running on Gasoil in 2015. The Boulaos plant’s retirement schedule has been observed.

4.8.2 Additional 3-year Period The system’s expansion plan was left unchanged and the criteria were still met in the additional 3-year period (2036-2038).

The existing national expansion plan with the study horizon extended by 3 years is shown in Figure 4-27 in the form of a bar chart representing the yearly system configuration by plant category:



Figure 4-27 Djibouti Existing National Expansion Plan with Extended Study Horizon

The configuration is still the same. The reserve drops to 10% but that is still acceptable for a thermal system.


4.8.3 Investment net present value The investment costs of all future plants in the existing national expansion plan are listed in Tables 5-12 and 6-16 of Module 1C-1200. Using a 10% interest rate, Djibouti’s investment net present value in 2013 is a total of 418.54 MUSD all of it as thermal. Investments will be compared in the next section to the ones in the regional plan, in order to highlight the benefits of interconnections.

4.8.4 Interconnections and energy generation The existing expansion plan was simulated with SDDP in order to obtain the generation by fuel type. The following committed interconnection was considered in the simulation:

• 220 KV single-circuit AC transmission line between Djibouti and Ethiopia with a capacity of 180 MW but a transfer limit of 700 GWh/year.

The energy generation by fuel category for Djibouti, including net exchanges with Ethiopia, is shown below in Figure 4-28:

0%

10%

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30%

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0153045607590

105120135150165180195210225240255270285

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2037

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Conventional

Load (MW)

Reserve Margin



Figure 4-28 Djibouti Generation by Fuel Category – Existing National Expansion Plan

The dominant source of energy for Djibouti is the net import from Ethiopia, shown in green. It is around 83% of the load in 2013. With the development of the geothermal plants and the additional new diesel generics, that proportion drops to 50% by 2038.

For the local generation, clean energy is preferred, in the form of geothermal plants. Clean thermal plants represented in orange constitute around 58% of the local generation by 2038. Clean generation even reaches a peak of 81% in 2022 when the last geothermal plant is added. But as the remaining years of the plan only include diesel additions, that share drops while the proportion of conventional thermals increases to 42 %.

It was shown through the system’s reserve that it is self-sufficient. However with no renewable energy and with the only source of cheap and clean power being the 60 MW geothermal developments, Djibouti tends to overuse the possibility to import from Ethiopia where the generation is mostly hydro, thus much cheaper than its own diesel.


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5 REGIONAL SUPPLY-DEMAND ANALYSIS

5.1 Introduction

The coordination in the planning of the expansion and operation of electric power systems brings important benefits for the systems involved because they could share reserve, replace high investment costs and save O&M costs. According to the terms of reference, the main objective of the study is to identify power generation and interconnection projects, at Master Plan level, to interconnect the power systems of EAPP countries in short-to-long term in order to reduce the future investment and operating cost for the whole region.

The previous section showed the analysis of the least cost generation expansion plan for each country (Case NGP_EIC), to supply the national load considering only the existing interconnections. The main criteria for the optimization, in each case, was to produce a least cost generation expansion plan while meeting the reliability criteria defined in the Module IC-1200. In general the national generation plan has surplus during certain periods of the year where the load is smaller or during certain years when a new big project enters in operation. That surplus could be exported to other country if there’s interconnection between both systems.

The methodology used for this study consisted, as a first step, in the identification of potential surplus of the generation national plans assuming that there was infinite capacity of interconnection between countries (case NGP_UIC). With these results it was possible to identify potential interconnection projects, in addition to the ongoing/committed interconnection projects.

As a second step, an interconnection expansion plan was optimized using as a base the national generation plans, in order to identify interconnection projects and to evaluate the benefits of a first level of regional coordination (case NGP_RIP) using OPTGEN/SDDP generation and interconnections planning software (the details about the models can be viewed on the publishing company’s website: PSR http://www.psr-inc.com.br). The main results of this scenario are presented below.

As a third step, both a generation and an interconnection expansion plans were optimized in order to identify interconnection projects and to coordinate the on-power date for regional generation projects. This allowed also to evaluate the benefits of a second level of regional coordination (Case RGP_RIP) related with the reduction in investment generation cost and the saving in operating cost, mainly associated with the reduction in fuel cost. This analysis is called also Regional Planning.

In a fourth step, four sensitivity analyses were done, two over the national generation plans case and two over the regional generation plans case, to evaluate the impact of important variables which could deeply affect the interconnections projects. The first sensitivity is related with the possible limitation to only one interconnection of 2000 MW from Egypt to Sudan (cases NGP_RIP_S1 and RGP_RIP_S1), and the second case considers a doubling of the capital costs of the interconnection projects (NGP_RIP_S2 and RGP_RIP_S2). The following Table 5-1 presents the definition and description of the different scenarios analyzed.



Table 5-1 Definition and description of the scenarios analyzed

Cases Name Description

NGP_EIC National Generation Plans and Existing Interconnection Capacity

National generation plans for each country to supply national load. The existing interconnections were considered only to save operating cost

NGP_UIC National Generation Plans and Unlimited Interconnection Capacity

National generation plans for each country to supply national load and infinite capacity of interconnections between countries to evaluate maximum surplus

NGP_RIP National Generation Plans and Regional Interconnection Plans

National generation plans for each country and regional interconnection plan for a first level of regional coordination, to maximize profitable power exchanges

NGP_RIP_S1 National Generation Plans and Regional Interconnection Plans Sensitivity 1

Similar to the case NGP_RIP considering limitation to only 2000 MW of interconnection capacity between Egypt and Sudan

NGP_RIP_S2 National Generation Plans and Regional Interconnection Plans Sensitivity 2

Similar to the case NGP_RIP considering a doubling of the capital costs of all interconnections projects

RGP_RIP Regional Generation Plans and Regional Interconnection Plans

Regional generation plans considering simultaneous Interconnection plans to supply in the most economical way the national load, independent of the location of the generation plants. In this case it was possible to displace, delay or advance generation in each country.

RGP_RIP_S1 Regional Generation Plans and Regional Interconnection Plans Sensitivity 1

Similar to the case RGP_RIP considering limitation to only 2000 MW of interconnection capacity between Egypt and Sudan

RGP_RIP_S2 Regional Generation Plans and Regional Interconnection Plans Sensitivity 2

Similar to the case RGP_RIP considering a doubling of the capital costs of all interconnection projects

5.2 Proposed Interconnections projects

As was done in the generation planning, interconnection projects had to be proposed to the planning software for optimization of the regional interconnection plans. These interconnections are categorized as:

- Existing: Will not be subject to any optimization - Committed: i.e. under construction or with Funds Secured. Will not be subject to any

optimization. The planned date of operation will be used - Studied: These projects have been studied. Their selection and schedule will be

optimized by the planning software. - Generic: These are additional lines that are similar in characteristics to the above

defined lines. They are proposed to the planning software which can choose multiple



instances of the same generic line. Hence the quantity of each generic project chosen and the dates are outputs of the planning software.

The generic projects were proposed by studying results of the preliminary runs of the optimization software seeing where the regional interconnection plan might require additional projects, and comparing different configurations for interconnections between any two neighbouring countries to choose the type of generics to feed to the model.

Table 5-2 Interconnection Projects

Name From To Voltage Distance Capacity Losses

Status Comm. date Km MW %

Existing Lines

UG-KY_132E Uganda Kenya 132 kV-AC 117 118 3.00 Existing

DC-RW_70E DRC Rwanda 70 kV-AC 0.2 52 3.00 Existing

DC-RW_110E DRC Rwanda 110 kV-

AC 16 100 3.00 Existing

DC-BR_70E DRC Burundi 70 kV-AC 14.5 45 3.00 Existing

RW-BR_110E Rwanda Burundi 110 kV-

AC 115 100 3.00 Existing

TZ-UG_132E Tanzania Uganda 132 kV-AC 85 59 3.00 Existing

Committed Lines

ET-SD_2C Ethiopia Sudan 220 kV-AC 321 200 5.24 Construction 2010

ET-DB_2C Ethiopia Djibouti 220 kV-AC 283 180 4.90 Construction 2011

UG-KY_2C Uganda Kenya 220 kV-AC 254 300 4.56 Construction 2014

DC-RW_2C DRC Rwanda 220 kV-AC 68 370 3.00 Construction 2014

DC-BR_2C DRC Burundi 220 kV-AC 105 330 3.00 Construction 2014

UG-RW_2C Uganda Rwanda 220 kV-AC 172 250 3.55 Committed 2014

Studied Lines

ET-SD_5S1 Ethiopia Sudan 500 kV-AC 544 1600 4.60 Studied

ET-SD_5S2 Ethiopia Sudan 500 kV-AC 544 1600 4.60 Studied

RW-BR_2S Rwanda Burundi 220 kV-AC 103 330 3.00 Studied

TZ-UG_2S Tanzania Uganda 220 kV-AC 85 700 2.29 Studied



Name From To Voltage Distance Capacity Losses

Status Comm. date Km MW %

TZ-KY_4S Tanzania Kenya 400 kV-AC 260 1520 3.11 Studied

TZ-RW_2S Tanzania Rwanda 220 kV-AC 115 320 2.87 Studied

TZ-BR_2S Tanzania Burundi 220 kV-AC 158 280 3.51 Studied

ET-KY_5dS Ethiopia Kenya 500 kV-DC 1120 2000 1.53 Studied

EG-SD_6dS Egypt Sudan 600 kV-DC 1665 2000 1.55 Studied

Generic Lines

ET-SD_5G Ethiopia Sudan 500 kV-AC 544 1600 4.60 Future

UG-KY_2G Uganda Kenya 220 kV-AC 254 440 4.56 Future

UG-KY_4G Uganda Kenya 400 kV-AC 254 1620 3.25 Future

UG-RW_2G Uganda Rwanda 220 kV-AC 172 520 3.55 Future

ET-KY_5dG Ethiopia Kenya 500 kV-DC 1120 2000 1.53 Future

EG-SD_6dG Egypt Sudan 600 kV-DC 1665 2000 1.55 Future

Note: Interconnections under study are identified by one “S” in the last part of their name. In the same way, existing and under construction Interconnections are identified with an “E” and “C” respectively. Generic Lines are identified by a “G”. A “d” identifies DC lines while numbers identify the voltage level (i.e. 6 600 KV).

5.3 National Generation Plans and Regional Interconnection Plans (NGP_RIP)

This scenario was developed to evaluate which interconnection projects can be justified as a result of only operating cost saving, without any changes in the national generation expansion plan. The Figure 5-1 shows the map of the Region with the interconnections projects and their in-service date (the map also includes the existing and committed lines)



Figure 5-1 EAPP Interconnections Case NGP_RIP



The Interconnection projects already studied: Tanzania-Kenya (1520 MW), Ethiopia-Kenya (2000 MW), Ethiopia-Sudan (2x1600 MW) and Egypt-Sudan (2000MW) entered in operation in the earliest date (2015 and 2016).

A second line of 2000 MW from Egypt to Sudan, a second line of 2000 MW from Ethiopia to Kenya as well as a line from Ethiopia to Sudan (1600 MW) enter into operation in 2020. A third line of 2000 MW from Egypt to Sudan enters into operation in 2025 with a final line from Ethiopia to Sudan (1600 MW).

The Interconnection Tanzania-Uganda (700 MW) entered in 2023 as well as the 440 MW Uganda-Kenya Line. The interconnection Uganda-Rwanda (520 MW) and the 1620 MW Interconnection Uganda-Kenya were not selected.

The new interconnection projects are justified because there’s cheaper generation surplus (e.g., hydro, geothermal, natural gas and Coal) in Ethiopia, Kenya and Tanzania, to replace mainly more expensive heavy fuel oil (HFO) based generation in Egypt (Figure 5-2). It’s important to note that the natural gas based generation in Egypt was limited at the same level observed in its national plan. However, an important quantity remains of generation based in HFO.

The increase of the hydro production in Ethiopia is a consequence of better use of the water available in the hydro plants (reduction in spillage). The interconnection Tanzania-Burundi/Rwanda is required for the Rusumo HPP which is committed in 2015.

Figure 5-2 Variation of some energy sources Case NGP_EIC vs Case NGP_RIP



The Figure 5-3 presents the net flows every five years between countries and the respective balance. It’s clear that the main flows go from south to north. Detailed balances for each country are in Appendix E. Bi-directional flows can be found in Appendix F. In addition, Diagrams in WBS 1500 show the maximum power transfer in both directions in MW for the years 2013; 2018; 2023; 2028; 2033 and 2038.



Figure 5-3 Balance and net flow between countries Case NGP_RIP

Balance Case NGP_RIP in GWh

Net Exchange NGP_RIP in GWh

Year Tanzania Uganda Burundi Eastern DRC Djibouti

Gen Load Net Gen Load Net Gen Load Net Gen Load Net Gen Load Net

2013 6,819 7,093 -273 3,575 3,575 0 205 170 35 472 303 169 107 663 -555 2018 11,866 10,722 1,144 5,428 4,874 554 394 339 55 1,806 392 1,414 306 886 -580 2023 18,501 14,422 4,079 7,129 6,465 665 470 576 -106 2,727 515 2,212 547 978 -431 2028 25,069 19,414 5,655 8,807 8,490 317 855 898 -43 4,839 682 4,157 595 1,078 -483 2033 30,263 26,207 4,056 11,315 10,708 607 1,693 1,299 394 8,887 904 7,984 663 1,188 -525 2038 40,910 36,935 3,975 14,296 13,086 1,210 1,626 0 1,626 6,316 1,187 5,129 740 1,308 -569

Year Kenya Ethiopia Sudan Egypt Rwanda

Gen Load Net Gen Load Net Gen Load Net Gen Load Net Gen Load Net

2013 11,527 12,149 -622 9,055 7,973 1,082 10,231 10,758 -527 175,491 174,790 701 1,190 499 691 2018 19,775 19,349 426 25,043 13,308 11,735 16,342 19,313 -2,971 221,462 233,210 -11,748 1,543 870 673 2023 31,883 28,460 3,423 32,349 19,939 12,410 34,525 31,729 2,796 282,846 307,530 -24,684 1,735 1,399 336 2028 48,697 41,880 6,817 37,478 29,412 8,066 64,812 49,938 14,874 363,644 402,130 -38,486 1,898 2,071 -173 2033 63,921 60,724 3,197 60,190 43,397 16,793 71,917 74,273 -2,356 492,080 520,720 -28,640 2,095 2,904 -809 2038 90,541 86,292 4,249 83,606 64,063 19,543 100,088 105,620 -5,532 641,228 666,800 -25,572 2,313 3,890 -1,577

Year UG->RW UG->TZ UG->KY TZ->KY KY->ET ET->SD ET->DB 2013 -895 273 622 0 0 527 555 2018 -934 428 1,060 2,779 4,265 15,420 580 2023 -1,890 481 2,074 5,112 10,609 22,588 431 2028 -2,718 179 2,856 7,056 16,729 24,312 483 2033 -6,291 574 6,324 5,907 15,429 31,696 525 2038 -3,577 730 4,057 4,525 12,830 31,805 569 Year RW->TZ BR->TZ RW->BR DC->BR DC->RW SD->EG EG->OT 2013 0 0 -35 0 169 0 701 2018 604 604 -141 690 724 12,449 701 2023 276 276 -195 577 1,636 25,385 701 2028 611 611 -1 655 3,501 39,186 701 2033 639 639 -402 647 7,337 29,340 701 2038 -90 -90 66 0 5,129 26,273 701



5.4 Regional Generation and Interconnection Plans (RGP_RIP) This scenario considers the possibility to optimize both the generation and interconnections in order to minimize the investment and operating cost for the whole Region. In that way the most expensive generation plants could be displaced or delayed and the cheaper projects could be advanced. As a result of the optimization, 7,143 MW of thermal projects were displaced in relation with the national plans, while cheaper hydro projects were advanced, mainly in Ethiopia, like Mandaya HPP (2000 MW) and Karodobi HPP (1200 MW), which are advanced from 2031 and 2036 in the NRP to 2020 and 2025 in the RGP_RIP, respectively; also Border HPP (1200 MW) which is not included in the NGP but is included in the RGP_RIP in 2032. The following Table 5-3 shows the thermal capacity displaced by country and the most important projects advanced with their respective levelized cost. The detailed expansion plan of this case, compared with the national plans, is included in the Appendix D.

Table 5-3 Generation capacity displaced or advanced Case RGP_RIP

Country Thermal Capacity Displaced in MW

Type of Fuel

Levelized Cost US$/MWh

Ethiopia 1,960 Diesel Oil 237 Djibouti 112 Diesel Oil 189 Rwanda 550 Diesel Oil 176 Burundi 600 Diesel Oil 176 Sudan 1,821 Crude/Gasoil 112/140 Tanzania 2,300 Coal 104 Uganda 300 Gasoil 162 Total 7,143

Project Hydro Capacity Advanced in MW From -> To Levelized Cost

US$/MWh Mandaya (Ethiopia) 2000 2031 -> 2020 29 Karadobi (Ethiopia) 1600 2036 -> 2025 30 Border (Ethiopia) 1200 Out -> 2030 34

The Figure 5-4 shows the interconnection projects included in this scenario as a result of the optimization of the regional plan and the Figures 5-5 shows the net flows of energy between countries for every five years, including also the balance for each country. The detailed balances for each country are included in the appendix E. The Bi-directional flows are included in appendix F.



Figure 5-4 EAPP Interconnections Case RGP_RIP

Note: Rusumo Falls has a capacity of 58 MW and shares its production between the three countries indicated in the figure. However, the transmission lines shown are not for the sole purpose of this transfer but for further exchanges among the countries involved, hence the capacity of the lines is much bigger than that of Rusumo Falls which acts as a substation/injection at that point.



Figure 5-5 Balance and net flow between countries Case RGP_RIP

Balance Case RGP_RIP in GWh

Net Exchange RGP_RIP in GWh

Year UG->RW UG->TZ UG->KY TZ->KY KY->ET ET->SD ET->DB 2013 -663 272 625 0 0 475 547 2018 -46 409 1,126 3,370 5,921 13,863 579 2023 5 945 1,652 3,477 8,041 22,409 426 2028 48 1,278 1,627 4,456 10,530 27,813 477 2033 680 4,225 1,662 229 5,352 27,709 525 2038 895 3,614 401 -5,905 2,989 22,186 562 Year RW->TZ BR->TZ RW->BR DC->BR DC->RW SD->EG EG->OT 2013 0 0 -31 0 130 0 701 2018 618 618 84 504 542 12,334 701 2023 286 286 -46 540 540 24,054 701 2028 678 678 -198 773 773 38,833 701 2033 1,143 1,143 -66 916 916 23,878 701 2038 555 555 -177 843 843 19,246 701

Year Tanzania Uganda Burundi Eastern DRC Djibouti Gen Load Net Gen Load Net Gen Load Net Gen Load Net Gen Load Net

2013 6,820 7,093 -272 3,810 3,575 235 201 170 31 433 303 130 115 663 -547 2018 12,446 10,722 1,724 6,363 4,874 1,489 369 339 30 1,438 392 1,046 307 886 -579 2023 16,382 14,422 1,960 9,066 6,465 2,601 368 576 -208 1,595 515 1,080 552 978 -426 2028 21,237 19,414 1,823 11,443 8,490 2,953 1,001 898 103 2,228 682 1,546 601 1,078 -477 2033 19,925 26,207 -6,282 17,274 10,708 6,566 1,592 1,299 293 2,735 904 1,832 663 1,188 -525 2038 26,307 36,935 -10,628 17,996 13,086 4,910 1,670 -843 2,513 2,874 1,187 1,687 747 1,308 -562

Year Kenya Ethiopia Sudan Egypt Rwanda Gen Load Net Gen Load Net Gen Load Net Gen Load Net Gen Load Net

2013 11,524 12,149 -625 8,995 7,973 1,022 10,283 10,758 -475 175,491 174,790 701 1,000 499 502 2018 20,773 19,349 1,424 21,829 13,308 8,521 17,784 19,313 -1,529 221,577 233,210 -11,633 1,078 870 208 2023 31,373 28,460 2,913 34,733 19,939 14,794 33,374 31,729 1,645 284,177 307,530 -23,353 1,094 1,399 -305 2028 46,327 41,880 4,447 47,172 29,412 17,760 60,959 49,938 11,021 363,997 402,130 -38,133 1,730 2,071 -341 2033 64,186 60,724 3,462 66,279 43,397 22,882 70,442 74,273 -3,831 497,543 520,720 -23,177 2,385 2,904 -519 2038 94,785 86,292 8,493 83,821 64,063 19,758 102,680 105,620 -2,940 648,255 666,800 -18,546 2,529 3,890 -1,361



The Table 5-4 presents the interconnection projects for the case RGP_RIP with the optimal date to enter in operation, compared with the case NGP_RIP. The main differences between both cases are the projects UG-KY_2G1 (440 MW) and KY-ET_5dG1 (2000 MW) which enter in the case NGP_RIP but not in the case RGP_RIP. The main reason is because in the NGP there are more generation plants in Uganda and Kenya to export to the north, and then these interconnections are attractive in term of benefits for the whole Region.

Table 5-4 Schedule of the interconnection projects selected Cases RGP_RIP and NGP_RIP

Name From To Voltage Capacity Invest Year in-operation

MW M$ RGP_RIP NGP_RIP

TZ-KY_4S Tanzania Kenya 400 kV-AC 1520 117.0 2015 2015

TZ-UG_2S Tanzania Uganda 220 kV-AC 700 30.4 2015 2023

TZ-RW_2S Tanzania Rwanda 220 kV-AC 320 37.6 2015 2015

TZ-BR_2S Tanzania Burundi 220 kV-AC 280 47.9 2015 2015

ET-KY_5dS Ethiopia Kenya 500 kV-DC 2000 845.3 2016 2016

ET-SD_5S1 Ethiopia Sudan 500 kV-AC 1600 255.4 2016 2016

ET-SD_5S2 Ethiopia Sudan 500 kV-AC 1600 255.4 2016 2016

EG-SD_6dS Egypt Sudan 600 kV-DC 2000 1,033.9 2016 2016

UG-RW_2G1 Uganda Rwanda 220 kV-AC 520 51.3 2016 OUT

ET-KY_5dG1 Ethiopia Kenya 500 kV-DC 2000 845.3 OUT 2020

ET-SD_5G1 Ethiopia Sudan 500 kV-AC 1600 255.4 2020 2020

EG-SD_6dG1 Egypt Sudan 600 kV-DC 2000 1,033.9 2020 2020

UG-KY_2G1 Uganda Kenya 220 kV-AC 440 71.0 OUT 2023

ET-SD_5G2 Ethiopia Sudan 500 kV-AC 1600 255.4 2025 2025

EG-SD_6dG2 Egypt Sudan 600 kV-DC 2000 1,033.9 2025 2025

5.5 Sensitivity analysis Four sensitivity analyses were done, two over the national generation plan and two over the regional generation plan, to evaluate the impact of important variables which could affect the interconnections projects. The first sensitivity is related with the possible limitation to only one interconnection of 2000 MW from Egypt to Sudan (cases NGP_RIP_S1 and RGP_RIP_S1), and the second case considers a doubling of the capital costs of the interconnection projects (NGP_RIP_S2 and RGP_RIP_S2).

5.5.1 National Generation Plans

The Table 5-5 shows the schedule of the interconnection projects for the sensitivity analysis of the case NGP_RIP. In general there are no important variations in the schedule of the new interconnections projects for the different scenarios; the interconnections UG-KY_4G1 (1620 MW) is selected in 2016 for the scenario NGP_RIP_S1 and in 2023 for NGP_RIP_S2. UG-RW_2G1 (520 MW) is selected in 2016 for both scenarios NGP_RIP_S1 and



NGP_RIP_S2. TZ-UG_2S is advanced to 2015 in both sensitivities. All interconnections projects already studied enter in service in the earliest available date.

Table 5-5 Schedule of the interconnection projects selected Cases NGP_RIP (Base, S1, S2)


MW M$ NGP_RIP NGP_RIP_S1 NGP_RIP_S2

TZ-KY_4S Tanzania Kenya 400 kV-AC 1520 117.0 2015 2015 2015

TZ-UG_2S Tanzania Uganda 220 kV-AC 700 30.4 2023 2015 2015

TZ-RW_2S Tanzania Rwanda 220 kV-AC 320 37.6 2015 2015 2015

TZ-BR_2S Tanzania Burundi 220 kV-AC 280 47.9 2015 2015 2015

ET-KY_5dS Ethiopia Kenya 500 kV-DC 2000 845.3 2016 2016 2016

ET-SD_5S1 Ethiopia Sudan 500 kV-AC 1600 255.4 2016 2016 2016


EG-SD_6dS Egypt Sudan 600 kV-DC 2000 1,033.9 2016 2016 2016

UG-RW_2G1 Uganda Rwanda 220 kV-AC 520 51.3 OUT 2016 2016

UG-KY_4G1 Uganda Kenya 400 kV-AC 1620 114.6 OUT 2016 2023

ET-KY_5dG1 Ethiopia Kenya 500 kV-DC 2000 845.3 2020 2020 2020

ET-SD_5G1 Ethiopia Sudan 500 kV-AC 1600 255.4 2020 2020 2020

EG-SD_6dG1 Egypt Sudan 600 kV-DC 2000 1,033.9 2020 OUT 2020

UG-KY_2G1 Uganda Kenya 220 kV-AC 440 71.0 2023 2023 2023

ET-SD_5G2 Ethiopia Sudan 500 kV-AC 1600 255.4 2025 2025 2025

EG-SD_6dG2 Egypt Sudan 600 kV-DC 2000 1,033.9 2025 OUT 2025

Note: Interconnections under study are identified by one “S” in the last part of their name. In the same way, existing and under construction Interconnections are identified with an “E” and “C” respectively.

5.5.2 Regional Generation Plans

The Table 5-6 shows the schedule of the interconnection projects for the sensitivity analysis of the case RGP_RIP. For this case the variations are more important in relation with the changes observed in the case NGP_RIP. The main reason for that situation is because in the Regional Plans the generation projects could change simultaneously with the changes in the interconnections projects, while in the national plans all generation projects are fixed in the sensitivity analysis in relation with the base case. The main changes in the interconnections projects are the following:

• The project TZ-KY_4S is delayed in the case RGP_RIP_S2 from 2015 to 2020

• The project UG-RW_2G1 is displaced in both sensitivities

• The project UG-KY_4G1 is included in 2016 for the sensitivity 1 and in 2023 for the sensitivity 2.

• The project ET-KY_5dG1 is included in 2020 in both sensitivities

• The projects ET-SD_5G1 and ET-SD_5G2 are delayed from 2020 and 2025 to 2032 for the sensitivity 1

• The project UG-KY_2G1 is included in 2016 in the sensitivity 1 and in 2023 for the sensitivity 2.



Table 5-6 Schedule of the interconnection projects selected Cases RGP_RIP (Base, S1, S2)


MW M$ RGP_RIP RGP_RIP_S1 RGP_RIP_S2

TZ-KY_4S Tanzania Kenya 400 kV-AC 1520 117.0 2015 2015 2020

TZ-UG_2S Tanzania Uganda 220 kV-AC 700 30.4 2015 2032 2015TZ-RW_2RS Tanzania Rwanda 220 kV-AC 320 37.6 2015 2015 2015

TZ-BR_2RS Tanzania Burundi 220 kV-AC 280 47.9 2015 2015 2015

ET-KY_5dS Ethiopia Kenya 500 kV-DC 2000 845.3 2016 2016 2016



EG-SD_6dS Egypt Sudan 600 kV-DC 2000 1,033.9 2016 2016 2016

UG-RW_2G1 Uganda Rwanda 220 kV-AC 520 51.3 2016 OUT OUT


ET-KY_5dG1 Ethiopia Kenya 500 kV-DC 2000 845.3 OUT 2020 2020

ET-SD_5G1 Ethiopia Sudan 500 kV-AC 1600 255.4 2020 2032 2020EG-SD_6dG1 Egypt Sudan 600 kV-DC 2000 1,033.9 2020 OUT 2020


ET-SD_5G2 Ethiopia Sudan 500 kV-AC 1600 255.4 2025 2032 2025EG-SD_6dG2 Egypt Sudan 600 kV-DC 2000 1,033.9 2025 OUT 2025

Note: Interconnections under study are identified by one “S” in the last part of their name. In the same way, existing and under construction Interconnections are identified with an “E” and “C” respectively.

5.6 Benefit-Cost analysis In this section, an analysis of the net benefits of the different levels of regional coordination is performed. For the computation of the benefits each case is compared with the references case where there is no regional coordination (NGP_EIC). The gross benefit is defined as the savings in generation costs (investment and variable O&M including fuel) and the net benefit subtracts from this value the investment and O&M of the interconnections. The present value (as of January 2013) of benefits and costs are evaluated using a discount rate of 10%.

The Table 5-7 and the Figure 5-6 show the benefits for each scenario analyzed.



Table 5-7 Benefit-Cost Analysis Present Values in MUS$

Cases Generation Cost Intercon Total Benefit

Invest O&M Total Cost Cost Gross 1 Net 2 Yearly 3

NGP_EIC 107,318 247,666 354,984 0 354,984 0 0 0

NGP_RIP 107,318 218,006 325,325 4,465 329,790 29,659 25,194 969

NGP_RIP_S1 107,318 225,872 333,190 3,458 336,648 21,794 18,336 705

NGP_RIP_S2 107,318 217,998 325,316 8,812 334,128 29,668 20,856 802

RGP_RIP 100,980 217,758 318,738 3,795 322,533 36,246 32,451 1,248

RGP_RIP_S1 103,593 223,929 327,522 2,698 330,220 27,462 24,764 952

RGP_RIP_S2 101,267 218,382 319,649 7,311 326,960 35,335 28,024 1,078

1 Total generation cost of each scenario less scenario NGP_EIC 2 Gross benefit less Interconnection Cost 3 Net benefit divided by 26 years

Figure 5-6 Benefit-Cost Analysis

As expected, the maximum benefit is obtained for the case where there’s coordination in the generation and interconnection expansion plans of the systems (RGP_RIP). The net benefit for this case amount to 32,451 MUS$ (equivalent to 1,248 MUS$/year) The lowest benefit is for the case NGP_RIP_S1 where there is no coordination in the generation expansion plan and the import capacity of Egypt is limited to only 2000 MW, for this case the net benefit



amounts to 18,336 MUS$ (equivalent to 705 MUS$/year). The second higher net benefit is for the case RGP_RIP_S2, in which the capital costs of all interconnection projects double in relation with the base case; for this case the net benefit amount 28,024 MUS$ (equivalent to 1,078 MUS$/year).

It is worth noting that the first level of regional coordination of interconnection projects potentially gives a sizable regional benefit (969 MUS$/year) as compared to the reference case while the second level of coordination (generation and interconnections) increase this benefit only marginally (to 1,248 MUS$/year).



6 IDENTIFIED PROJECTS FOR FURTHER ANALYSIS IN PHASE II

After the analysis for the national and regional plans in the preceding sections, a group of generation and interconnection projects have been identified that will be analyzed in further detail in phase II of this study.

Projects which have been identified for the first five years of the study horizon (2013 – 2017) will undergo a more detail analysis.

6.1 Generation projects

The potential list of regional generation projects was identified in section 7 of the WBS 1200 report: Generation Supply Study and Planning Criteria. Based on the analysis of the national plans and the regional plans in the present report (sections 4 and 5), the list of identified generation projects is shown in Table 6-1 below. These generation projects were selected because they have regional scope (identified as the best options either in the national and or regional plans). In some cases their on-power date is advanced in the regional plans (earlier than in the national plan), indicating that they are providing additional regional benefits.

Table 6-1 Identified Generation Projects for Phase II

Country Plant Name Type Installed Cap (MW)

Eastern DRC

Ruzizi III Hydro 145

Ruzizi IV Hydro 287

Piana Mwanga Hydro 29

Bengamisa Hydro 48

Babeda I Hydro 50

Semliki Hydro 28

Mugomba Hydro 40

Ethiopia

Mandaya * Hydro 2000

Gibe III Hydro 1870

Border * Hydro 1200

Gibe IV Hydro 1468

Karadobi * Hydro 1600

Rwanda Kivu I Diesel 100

Kivu II Diesel 200

Tanzania Stieglers Gorge (I, II, III) * Hydro 1200

Uganda

Karuma Hydro 700

Ayago Hydro 550

Murchison Falls Hydro 750 (*) projects with regional benefits: benefits increase when these are advanced with respect to the on-power date in the national plans.



6.2 Interconnection Projects

Several interconnection projects have been identified after the analysis of the national and the regional plans. These are indicated in Table 6-2 below.

Table 6-2 Identified Interconnection Projects for Phase II


Capacity (MW)

Year in Operation Status Comments

Tanzania Kenya 400 kV

2 circuits 260 Km

1520 2015*

Ongoing FS, detailed

design and tender

documents preparation

In the initial years helps to improve regional dispatch (reducing costs and deficits) and later makes possible trade in and out of Tanzania, taking advantage of hydro surpluses in Ethiopia and surpluses created by new projects in Tanzania’s national plan such as Ruhudji HPP (2016), Mnazibay NG (2017), Rumakali HPP (2018) and later from the Stieglers Gorge project (phase 1, 2 and 3). The advance of this interconnection to 2015 is to improve the regional dispatch. In general the flows go from Tanzania to Kenya, except in 2015. Bidding for line construction may start at the end of 2011.

Tanzania Uganda 220 kV

2 circuits 85 Km

700 2023* Future

In the initial years helps to improve regional dispatch (reducing costs and deficits) and later makes viable the export of surpluses in Uganda from hydro projects in the national plan such as Karuma HPP (2016) and Ayago HPP (2023/28).

Rusumo Rwanda 220 kV 1 circuit 115 Km

320 2015*

FS completed

Lines associated to the Rusumo Falls HPP connecting the project with the grids of Tanzania, Rwanda and Burundi. Rusumo Burundi

220 kV 1 circuit 158 Km

280 2015*

Rusumo Tanzania220 kV 1 circuit 98 Km

350 2015*



From To Type Capacity (MW)



bipole 1120 Km

2000 2016*

Design and tender

document preparation


Allows for exports of hydro surplus in Ethiopia to the south and makes viable trade of surpluses in Kenya from the large Geo-thermal developments in the nation al plan. New design study aims at highly optimistic completion of phase I (1000 MW) of the project by 2013 and phase II upgrade to 2000 MW by 2019.


bipole 1120 Km

2000 2020* Future Allows for exports of hydro surplus in Ethiopia to the south and makes viable trade to the north from large hydro developments in Tanzania (Stieglers Gorge phases 1,2, and 3)


4 circuits 570 Km

3200 2016* FS completed

Allows exports to the north from surplus hydro in Ethiopia. Several projects in the Ethiopian national plan contribute to the surplus: Gibe III HPP (1870 MW), Chemoya Yeda HPP (280 MW), and Halele Worabesa HPP (422 MW) which are expected to be completed by 2013.


2 circuits 544 Km

1600 2020* Future

Allows exports to the north from additional surplus hydro in Ethiopia. Several projects in the Ethiopian national plan contribute to the surplus: Baro I, II HPP (500 MW) and Genji HPP (200 MW) in 2020 and Mandaya HPP (2000 MW) in 2021.


2 circuits 544 Km

1600 2025* Future

Allows exports to the north from additional surplus hydro in Ethiopia. Several projects in the Ethiopian national plan contribute to the surplus: Karadobi HPP (1600 MW) in 2025 eventually Border HPP (1200 MW) in 2030.


bipole 1665 Km

2000 2016* FS completed

Allows imports from Ethiopian hydro surplus. Several projects in the Ethiopian national plan contribute to the surplus: Gibe III HPP (1870 MW), Chemoya Yeda HPP (280 MW), and Halele Worabesa HPP (422 MW) which are expected to be completed by 2013.






bipole 1665 Km

2000 2020* Future Allows imports from Ethiopian hydro surplus. Several projects in the Ethiopian national plan contribute to the surplus: Baro I, II HPP (500 MW) and Genji HPP (200 MW) in 2020 and Mandaya HPP (2000 MW) in 2021.


bipole 1665 Km

2000 2025* Future Allows imports from Ethiopian hydro surplus. Several projects in the Ethiopian national plan contribute to the surplus: Karadobi HPP (1600 MW) in 2025 eventually Border HPP (1200 MW) in 2030.

Uganda Kenya 220 kV

2 circuits 254 Km

440 2023 Future Allows for exports from hydro surpluses in Uganda associated with the Ayago HPP (550 MW) in 2023/28.

Uganda Kenya 220 kV

2 circuits 254 Km

300 2014 Under construction

Runs from Lessos substation in Kenya to Bujagali substation passing through Tororo substation in Uganda, duplicating the existing 132kV line.

Uganda Rwanda 220 kV

2 circuits 172 Km

250 2014

Detailed and Tender

Documents preparation study starts

in 2011

Line from Mbarara to Mirama (border Uganda) to Birembo/Kigali (Rwanda)

Rwanda DRC 220 kV 1 circuit 68 Km

370 2014 Under

construction Line between new substation at Kibuye Methane Gas plant in Rwanda and Goma (DRC), thus completing the loop around lake Kivu.





DRC Burundi 220 kV 1 circuit 105 Km

330 Expected in 2014

FS, detailed engineering and tender documents preparation


Line from future substation Kamanyola/Ruzizi III (DRC) to Bujumbura (Burundi). Study Includes 220kV line between a new substation in Bujumbura to Kiliba (DRC).

Burundi Rwanda 220 kV 330 2016 FS update to

start early 2011

Line Rwegura (Burundi) – Kigoma (Rwanda), previous FS recommended 110kV. Feasibility Study update to re-examine 220kV option and re-route line to feed intermediate locations.

Notes:

(*) Project enters in the earliest on power date.

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