nam theun 2 hydro power project regional economic...

report to

The World Bank

Robert Vernstromconsulting economistBangkok, Thailand662 2520186 fax 662 [email protected]

Nam Theun 2 Hydro Power Project

Regional EconomicLeast-Cost Analysis

Final Report

March 2005

The findings, interpretations and conclusions contained in this report arethose of the author and do not represent the views of the IBRD/IDA or ofthe Executive Directors of IBRD/IDA, the Electricity Generating Authorityof Thailand (EGAT), or the Nam Theun 2 Power Company Limited(NTPC).

The author wishes to thank the Electricity Generating Authority ofThailand (EGAT), Dr. Kajornsak Hotrabhavananda, Deputy Governor forPolicy and Planning, and Mr. Prutichai Chonglertvanichkul, Director –System Planning Division, for the extensive support of their experiencedprofessional team. Special thanks are due to Ms. Petchara Rompruek (Headof Power Development Planning), and her staff (including ManopTanglakmongkol, Nimit Sujiratanavimol, Thanawadee Deetae, andYoothapong Tancharoen, among others), without whose support theStudy would not have been possible. Countless hours were spent indiscussing and refining assumptions used in the Study, and many additionalhours were expended to complete the generation expansion planningscenarios discussed in this report.

The demand forecasting sections of this report were prepared with theexpert assistance of Dr. Tienchai Chongpeerapien, President of Businessand Economic Research Associates (BERA), a Bangkok consultant withmany years of experience working on load forecasting issues for the Thaipower sector.

Special thanks are due to Mr. Mark Segal, Mr. Darayes Mehta, and Mr.Robert Mertz, World Bank supervisors and advisors to the project, fortheir professional guidance and support.

TABLE OF CONTENTS

Executive Summary i

1 Introduction 9

1.1 Background 91.2 Study Objective 101.3 Organization of the Report 10

2 System Demand Assumptions 12

2.1 Overview of the Forecasting Methodology 122.2 Comparison of Forecast Results 192.3 Load Forecast Adopted for this Study 23

3 System Supply Assumptions 25

3.1 Installed and Planned System Capacity 253.2 Thermal Expansion Candidates 283.3 Fuel Price Projections 293.4 Thermal Candidate Plant Screening Analysis 313.5 NT2 – The Alternative Expansion Candidate 32

4 Methodology for the Study 35

4.1 The Least Cost Planning Methodology 354.1.1 The PROSCREEN II Model 354.1.2 How PROSCREEN is Applied in this Study 364.2 Cost-Risk Analysis Modeling Framework 37

5 Economic Evaluation 41

5.1 Economic Planning Assumptions 415.1.1 Basic Economic Assumptions 415.1.2 System Characteristics 425.1.3 NT2 Planning Assumptions for the Economic Analysis 435.2 Base Case Results 455.3 Cost-Risk Analysis 475.3.1 Sensitivity Analysis 495.3.2 Cost-Risk Analysis Results 52

6 Commercial Assessment 57

6.1 Commercial Planning Assumptions 576.1.1 Basic Commercial Assumptions 576.1.2 System Characteristics 576.1.3 The Cost of NT2 596.1.4 Private Sector Commercial View 596.2 Commercial Base Case Results 616.3 Cost-Risk Analysis 63

6.3.1 Sensitivity Analysis 636.3.2 Cost-Risk Analysis Results 67

7 Conclusion 69

A1 Terms of Reference 71

A2 Thailand Demand Forecast 77

A3 Fuel Price Assumptions 83

A4 Detailed Plant Data (Existing System) 93

A5 How PROSCREEN Works 99

A6 Economic Base Case with NT2 – Detail 103

TABLES AND FIGURES

Table S-1. Economic Cost-Risk Analysis Results v

Table S-2.Comparison of Economic and Commercial Analyses vi

Table S-3. Commercial Cost Risk Analysis Results vii

Table 1. Current Forecast Methods by Company and Class 14

Table 2. National GDP Growth Assumptions 15

Table 3. Integrated National Electricity Conservation Program 18

Table 4. National Conservation Program – Alternative View 19

Table 5. Historical Energy Requirements Forecasts (GWh) 20

Table 6. Historical Peak Demand Forecasts (MW) 21

Table 7. Implied Income Elasticity of Energy Requirements Forecasts 22

Table 8. Historical Forecast Accuracy 1/ 22

Table 9. Recommended Load Forecast for this Study 24

Table 10. Installed and Purchased Capacity (as of March 2003) 26

Table 11. Committed Plant Additions (after March 2003) 27

Table 12. Schedule of Retirements (FY2003-14) 28

Table 13. Candidate Power Plants for the Study (2003 Prices) 29

Table 14. Base Case Fuel Price Forecasts 31

Table 15. Screening Analysis of EGAT Candidate Plants 33

Table 16. The Cost-Risk Framework 38

Table 17. Capital Costs of NT2 (constant US$2003, 10% discount rate) 44

Table 18. Base Case “with NT2” 45

Table 19. Base Case “without NT2” 46

Table 20. Sensitivity of Results to Lower Demand 50

Table 21. Sensitivity of Results to the Price of Natural Gas 51

Table 22. Sensitivity to Changes in NT2 Capital Cost 52

Table 23. Economic Cost Risk Analysis Results 53

Table 24. Economic Cost-Risk Sensitivity Test 55

Table 25. Commercial Base Case 62

Table 26. Sensitivity of Results to Lower Demand 65

Table 27. Sensitivity of Results to Lower Natural Gas Prices 66

Table 28. Commercial Cost-Risk Analysis 67

Table 29. Commercial Cost-Risk Sensitivity Test 68

Table A2-1. EGAT Total Generation Requirement Forecast 78

Table A2-2. EGAT Total Sales Forecast 79

Table A2-3. MEA Purchases and Sales Forecast by Customer Class 80

Table A2-4. PEA Purchases and Sales Forecast by Customer Class 81

Table A2-5. Comparison of The August 2002 and January 2004 Forecasts 82

Table A3-1. Economic Fuel Price Projections (constant US$2003) 84

Table A3-2. Commercial Fuel Price Projections (current US$) 85

Table A4-1. Existing Installed Generating Capacity (as of Sep-03) 94

Table A4-2. Existing Hydro Power Plant Data 95

Table A4-3. Existing and Committed Small Power Producers (as of Sep-03) 96

Table A4-4. Schedule of Planned Plant Retirements 97

Table A6-1. Demand and Supply Balance – Economic Base Case with NT2 104

Table A6-2. System Costs by Plant Group – Economic Base Case with NT2 106

Table A6-3. Fuel Use by Type – Economic Base Case with NT2 108

Table A6-4. Fuel Type by Individual Plant – Economic Base Case with NT2 110

LIST OF ACRONYMS

AAGR average annual growth rateBOI Board of InvestmentBTU British Thermal Unit (standard measure of fuel heat content)CCGT combined cycle gas turbineCIDA Canadian International Development AgencyCOD commercial operation dateDAEDE Department of Alternative Energy Development and Efficiency (formerly

DEDP)DEDP Department of Economic Development and Promotion (now DAEDE)E&P exploration and productionEDP exploration, development, productionEGAT Electricity Generating Authority of ThailandEIA Energy Information Administration (U.S. Department of Energy)EPPO Energy Policy and Planning Office (formerly NEPO)ESI electricity supply industryGDP gross domestic productGHG greenhouse gasGMS Greater Mekong Sub-regionGOL Government of the Lao People’s Democratic RepublicGOT Government of the Kingdom of ThailandGPA gas purchase agreementGRP gross regional productGT gas turbineGWh gigawatt hour (one million kWh)HFO heavy fuel oilIBRD International Bank for Reconstruction and Development (official name

for the World Bank)IMF International Monetary FundIPP independent power producerkWh kilowatt hourLER low economic recovery (Sep-98 forecast scenario)LFCR levelized fixed charge rateLOLP loss of load probabilityMEA Metropolitan Electricity AuthorityMER medium economic recovery (Sep-98 forecast scenario)MM millionMOU memorandum of understandingMUV United Nations index of the unit value of manufactured exportsMW megawatt (one thousand kW)MWh megawatt hour (one thousand kWh)NEPO National Energy Policy Office (now EPPO)NESDB National Economic and Social Development Board

NPL non-performing loanNPV net present valueNSO National Statistics OfficeNT2 Nam Theun 2 hydro power projectNTPC Nam Theun Power CompanyPCF Prototype Carbon Fund administered by the World BankPDP power development program of EGATPE primary energy (required purchases from NT2, 6 a.m. to 10 p.m.)PEA Provincial Electricity AuthorityPPA power purchase agreementPTT Petroleum Authority of ThailandPV present valueRER rapid economic recovery (Sep-98 forecast scenario)RM reserve marginR/P reserves to production ratioSCF standard cubic foot (approximately 1000 Btu)SE1 secondary energy 1 (required purchases from NT2, 10 p.m. to 6 a.m.)SE2 secondary energy 2 (optional purchases from NT2, 10 p.m. to 6 a.m.)SPP small power producerTDRI Thailand Development Research InstituteTHB Thai Baht; in this study, US$1.00 = 40 THBTLFS Thailand Load Forecast Sub-committeeWACC weighted average cost of capitalWB World BankWCD World Commission on Dams

Executive Summary i

EXECUTIVE SUMMARY

S-1 Background and ObjectivesNam Theun 2 (NT2) is a planned hydroelectric project of a thousand megawatts inthe Lao PDR to be developed by a private company (NTPC). The Government ofLaos (GOL) is a 25 percent shareholder in NTPC. Upon anticipated commencementof commercial operation in 2009 (FY2010), NTPC will sell fixed amounts of power atpre-negotiated prices to the Electricity Generating Authority of Thailand (EGAT).

A World Bank Partial Risk Guarantee to NTPC is under consideration. This study isa component of the Bank’s on-going due diligence process. The work is a complementto an earlier study with the same name, the Regional Economic Least-Cost Analysis ofJune 2004 (RELC/2004),1 developed in cooperation with the Electricity Authority ofThailand (EGAT), utilizing EGAT’s least-cost planning tools. That study assessed theeconomic viability of NT2 from a regional2 perspective through a structured “cost-risk” analysis that evaluated the project in light of alternative outlooks on demand,natural gas prices and NT2 construction costs. The study was conducted solely froman economic perspective.

Rapidly changing events subsequent to the publication of RELC/2004 led The WorldBank to conclude that the earlier results should be completely reassessed. Mostsignificantly, NT2 costs have increased since early 2004, and the world hasexperienced a dramatic increase in fossil fuel prices. Both of these changes potentiallyimpact the viability of the project. Moreover, the Bank concluded that it would beuseful to conduct, along with the economic analysis, a parallel commercial analysis on atotally consistent basis. The current study reports the findings of the analysisconducted to achieve these expanded objectives.

Chapter 2 presents the demand forecast of the regional power system which hasbeen adopted for the current study. Chapter 3 presents detailed background on theexisting power supply system, and on candidate plants for future system expansion.

S-2 Study Objective and MethodologyThe study outcome is to be determined by means of a results profile known as the“Cost-Risk Framework”. This profile – explained in detail in Chapter 4 – provides forcalculating the probability-weighted present value (PV) costs of either implementingor not implementing NT2 for commercial operation in FY2010, given the interplay of

1 Robert Vernstrom, Regional Economic Least-Cost Analysis, Bangkok, June 2004. The World Bankfinanced and supervised the study. Throughout this document, the original study is referenced asRELC/2004, while the present study is referenced as RELC.

2 Throughout this document, the word “regional” refers Lao PDR and Thailand.

Executive Summary i i

several major uncertain factors – project cost, long-term demand for electricity, andlong-term economic value of natural gas as well as the suggested probabilities ofoccurrence for Base Case, Low and High estimates of these variables. The differencebetween the probability weighted PV cost of implementing the project in FY2010versus not implementing it at all is the decision criteria for this analysis. A lower netpresent value (NPV) “with NT2” would indicate that the project is an efficienteconomic investment for the regional power market.

The specific steps undertaken to complete the cost-risk analysis are summarized in thefollowing paragraphs:

Determine Base Case, Low, and High real economic values for the three keyuncertainties expected to have the most significant potential impact on theeconomic decision to develop NT2 – (i) project cost, (ii) growth rate ofelectricity demand, and (iii) the economic value of natural gas.

Define a probability of occurrence for each state (Base Case, Low, andHigh) of each variable.

Run the PROSCREEN expansion planning model under Economic BaseCase assumptions with NT2 as a candidate competing for a place in the least-cost expansion plan from its earliest expected commercial operation date ofFY2010. This initial analysis added NT2 to the system in FY2010, i.e., itspecified that the least-cost expansion plan included NT2 commencingoperation in October 2009. (By FY2010, EGAT's current capacity surplusis fully absorbed, and NT2 is selected as the least cost capacity addition toachieve the target reliability criterion of 15 percent.) This date wastherefore fixed for all subsequent "with NT2" model runs to conform to thelogic of the decision matrix (the decision being whether to develop NT2 forcommercial operation in October 2009 or not to do so).

Run the PROSCREEN generation expansion planning model with NT2commencing commercial operation in FY2010 for all combinations of theabove-defined uncertainties. The PROSCREEN “objective function” (i.e.,basis for comparison of results) is the present value of future investmentand operating costs over the Study Period.

Re-run each of the defined scenarios without NT2 so that demand must beserved from alternative resources.

Calculate the probability-weighted present value of costs for the “withNT2” and “without NT2” scenario groups.

Subtract the probability-weighted result “with NT2” from the result“without NT2” to determine the Study outcome.

Repeat the above analysis, converting all real economic values in the least-cost planning runs to nominal commercial values (i.e., using market pricesincluding inflation). This analysis is designed to test the long-term

Executive Summary i i i

sustainability of the PPA in a competitive commercial market environment.We refer to these cases as the Commercial model runs.

To complete the Cost-Risk Framework, a total of 18 scenario runs are required (9“with NT2” and 9 “without NT2”), or a total of 36 model runs for both theeconomic and commercial cost-risk assessments. These scenarios are formed fromcombinations of two planning variables – power demand and natural gas price. Threecases – Base, Low, and High – are used for each of these variables. The 9 scenariosrun with NT2 were expanded to 27 scenarios for the economic assessment bycombining manually the three cases for the construction cost of NT2 with the resultsof the other scenarios. High and low project cost is not evaluated in the commercialruns because the commercial arrangement is a fixed-price PPA.

A complete economic cost-risk analysis – requiring 18 PROSCREEN model runs byEGAT system planners – was prepared for the RELC/2004 study. Although theWorld Bank wished to update that economic analysis to incorporate currentinformation (i.e., current perspectives on Thai fuel prices and the most recent data onNT2 capital cost) and to conduct a parallel commercial analysis of equivalent scope, itwas considered unnecessary (and unreasonable!) to request twice the originalsupport (i.e., 36 model runs, each requiring considerable set-up and run time) fromthe EGAT System Planning Division.

It was therefore decided to focus the cost-risk analysis for the current study only onthe downside risks to NT2. Specifically, the analysis was limited to the base case andthose cases which could be expected to pose the greatest test to project viability, i.e.,conditions of lower than expected demand, lower than expected fuel prices, andhigher than anticipated NT2 capital costs.

The Base Case analysis is characterized as follows:

The Base Case load forecast is Thailand’s official Base Case of August 2002(see Chapter 2), augmented by a Lao PDR domestic load of 75 MW and upto 300 GWh per year.

The reliability criterion is a reserve margin of 15 percent.

The existing system corresponds to the summary in Table 10.

All “committed plants” as identified in Table 11 are presumed to commencecommercial operation according to schedule.

The schedule for plant retirements follows the assumptions detailed in Table12.

NT2 (995 MW) is added to the system in FY2010 (October 2009) in the“with NT2” scenarios.

Executive Summary i v

All other plants – including plants proposed for reconditioning and allgeneric expansion options (see Table 13) – are modeled as candidateswhich must compete for a place in the least cost economic plan.

Generation of existing plants and selected candidates is dispatched byPROSCREEN according to the following rules:

All non-thermal generation – notably domestic hydro plants and Laoimports – is dispatched first, without regard to cost, since capacitycosts are sunk and operating costs negligible. With the exception ofEGAT’s own hydro capacity, each of these resources is modeled as aseparate transaction, defined from contractual purchase price andoperating constraints.

NT2 energy is dispatched in two parts according to the monthlyvariation reported in Chapter 3, one to provide peak-period energyand a second to provide off-peak energy.

All thermal generation – the majority of the entire system – is subjectto economic dispatch, and each unit is run only when it is lowestcost. Exceptions are small power producers (SPPs), which areassumed to run at an 80 percent capacity factor.

S-3 Results of the Economic AssessmentThe Base Case economic analysis tells us that NT2 should be included in the region’sleast cost generation expansion plan. The accumulated present value of real resourcesavings to the region over the entire Study Period (FY2003-14 and beyond3) totalsUS$266 million at 2003 prices.4

The project outcome is determined by a cost-risk analysis, designed to determinewhether the same decision is justified given the high probability that future events willdiverge from Base Case assumptions.

The key decision variables for this study are defined in the study TOR (see AppendixA1). They are:

Capital cost of NT2. The World Bank has specified a cost range of +30percent (High capital cost) and –30 percent (Low capital cost); thesevalues are reported in Table 17.

3 The Study Period includes both the planning period (FY2003-14) and an "end effects" analysis whichutilizes sophisticated programming techniques to analyze differences between alternatives (e.g., due todifferent lives and operating characteristics) beyond the planning period. Without an end-effectsanalysis, results may be biased against commissioning capital-intensive units near the end of theplanning period.

4 The costs and benefits being evaluated in this report are in general restricted to the power sector,but for NT2 they include all the environmental and social costs that the project will fund directly asper agreement with the developer. The US$ 266 million represents a ‘savings” since the least-costplan without NT2 would come at greater total cost.

Executive Summary v

Regional demand forecast. The World Bank has specified a very wide range inorder to reflect the Bank's long-term experience with demand forecastperformance;5 the regional High and Low demand forecasts are summarizedin Table 9.

Natural gas price forecast. The World Bank commissioned a separatelyprepared forecast of natural gas prices taking into account region-specificpricing conventions with indexation factors based on its own worldpetroleum product price projections, with particular emphasis on the priceof natural gas since gas is the most competitive alternative fuel. The BaseCase projections are presented in Table 14; High and Low scenarios arereported in Appendix A3.

The TOR has further specified the probability of occurrence for each of the Base,High and Low case assumptions regarding demand, natural gas value and project cost.Each “expected” (i.e., Base Case) assumption value has a probability of 50 percent inthe cost-risk matrix, with the High and Low assumption values assigned a probabilityof 25 percent each.

Table S-1. Economic Cost-Risk Analysis Results

5 This experience also reflects extreme and unexpected events, such as the Asian economic crisis of1997, but that is not the primary consideration for the wide range adopted.

A. Present Values WITH NT2:Savings by

Case Probability Case Probability Case Probability Case Present Value Probability Scenarioh 0.25 h 0.25 h 0.25 hhh 46,808 0.01563 61 h 0.25 h 0.25 m 0.50 hhm 46,808 0.03125 61 h 0.25 h 0.25 l 0.25 hhl 43,741 0.01563 (6) h 0.25 m 0.50 h 0.25 hmh 46,808 0.03125 61 h 0.25 m 0.50 m 0.50 hmm 46,808 0.06250 61 h 0.25 m 0.50 l 0.25 hml 43,741 0.03125 (6) h 0.25 l 0.25 h 0.25 hlh 34,548 0.01563 (181) h 0.25 l 0.25 m 0.50 hlm 34,548 0.03125 (181) h 0.25 l 0.25 l 0.25 hll 32,214 0.01563 (259) m 0.50 h 0.25 h 0.25 mhh 46,603 0.03125 266 m 0.50 h 0.25 m 0.50 mhm 46,603 0.06250 266 m 0.50 h 0.25 l 0.25 mhl 43,536 0.03125 199 m 0.50 m 0.50 h 0.25 mmh 46,603 0.06250 266 m 0.50 m 0.50 m 0.50 mmm 46,603 0.12500 266 m 0.50 m 0.50 l 0.25 mml 43,536 0.06250 199 m 0.50 l 0.25 h 0.25 mlh 34,343 0.03125 24 m 0.50 l 0.25 m 0.50 mlm 34,343 0.06250 24 m 0.50 l 0.25 l 0.25 mll 32,009 0.03125 (54) l 0.25 h 0.25 h 0.25 lhh 46,399 0.01563 471 l 0.25 h 0.25 m 0.50 lhm 46,399 0.03125 471 l 0.25 h 0.25 l 0.25 lhl 43,331 0.01563 404 l 0.25 m 0.50 h 0.25 lmh 46,399 0.03125 471 l 0.25 m 0.50 m 0.50 lmm 46,399 0.06250 471 l 0.25 m 0.50 l 0.25 lml 43,331 0.03125 404 l 0.25 l 0.25 h 0.25 llh 34,138 0.01563 228 l 0.25 l 0.25 m 0.50 llm 34,138 0.03125 228 l 0.25 l 0.25 l 0.25 lll 31,804 0.01563 151

A. Probability-weighted Present Value WITH NT2 42,817 1.00000

B. Present Values WITHOUT NT2:

Case Probability Case Probability Case Present Value Probabilityh 0.25 h 0.25 hh 46,869 0.06250 h 0.25 m 0.50 hm 46,869 0.12500 h 0.25 l 0.25 hl 43,735 0.06250 m 0.50 h 0.25 mh 46,869 0.12500 m 0.50 m 0.50 mm 46,869 0.25000 m 0.50 l 0.25 ml 43,735 0.12500 l 0.25 h 0.25 lh 34,367 0.06250 l 0.25 m 0.50 lm 34,367 0.12500 l 0.25 l 0.25 ll 31,955 0.06250

B. Probability-weighted Present Value WITHOUT NT2 43,005 1.00000

Probability-weighted PV Savings (Cost) WITH NT2 188 (Result A minus Result B; 2003 USD million)

POWER DEMAND GAS PRICE

CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million)

SCENARIO RESULTS (2003 USD million)

Executive Summary v i

The results of the economic cost-risk analysis are summarized in Table S-1.6 Theanalysis concludes that the probability-weighted accumulated present value of realresource savings to the region as a result of the development of NT2 is US$188million in present value terms. This result is marginally lower than the Base Casepresent value of US$266 derived without incorporating probabilistic outcomes for keyvariables, but the result confirms project viability from an economic, real resourceperspective.

S-3 Results of the Commercial AssessmentIn parallel with the economic cost-risk analysis, a commercial cost-risk analysis is alsoperformed, as presented in Chapter 6. The key differences between the economicand the commercial analyses relate to both the purpose of the analysis and thevaluation of costs, as summarized in Table S-2.

Table S-2.Comparison of Economic and Commercial Analyses

6 As noted above, PROSCREEN modeling was limited to consideration of the downside risks to theNT2 project. In order to complete the full matrix, “Medium” scenario results have been used in thetable to substitute for the results what would have occurred with the current set of High demand andHigh natural gas price assumptions, since these scenarios were not evaluated for the current study.Simple logic and the results of RELC/2004 confirm that this procedure understates the economicadvantage of NT2, since scenarios with High demand and High natural gas prices would result inhigher net savings attributable to NT2 than these proxies indicate.

Economic Commercial

IssueAddressed

Is the project an efficientallocation of real resources?

Do the commercial arrangements badlydistort economic value? Does the PPAappear commercially sustainable?

Perspective Regional economy of Laos andThailand

Costs facing the power sectors of thetwo countries

Valuation Real [constant] dollar cost ofreal resources used forinvestment and operation

Nominal [current] dollar cost atmarket prices incurred by the powersector to provide electricity

Discount rate 10% real 10.45% nominal, the project weightedaverage cost of capital

Cost of NT2 Real investment cash flows PPA payments

Taxes androyalties

Excluded Included

Sunk costs Excluded Included

Environmentalcredit

Included Excluded

Executive Summary v i i

Notwithstanding the strongly positive economic preference for the project, thecommercial analysis is relevant because taxes, royalties and payment arrangementscreate a large difference between the economic and the commercial cost of supplyingelectricity in both the "with NT2" and "without NT2" project scenarios. In thesecircumstances it is important to evaluate the risk of the commercial arrangementsdistorting the contracting parties’ shared perception of the project’s economic benefitto the region.

Results of the commercial cost-risk analysis are reported in Table S-3. The risk-adjusted savings “with NT2” are estimated to be US$145 million.7 These resultsconfirm our Base Case conclusion that NT2 is a viable investment project from acommercial perspective.

Table S-3. Commercial Cost Risk Analysis Results

S-4 ConclusionEconomic and Commercial assessments of the project conclude that the decision topurchase NT2 power offers significant savings to the regional power system.

The economic evaluation, based on a probability-weighted real cost-risk analysis ofdownside risks, indicates a real savings (i.e., in present value terms at 2003 prices) onthe order of US$188 million will accrue to the region over the lifetime of the plant. 7 As previously explain for the economic cost-risk assessment, modeling was limited to consideration ofthe downside risks to the NT2 project, completing the matrix with a procedure which understates thenet advantage of NT2. See footnote 6.


Case Probability Case Probability Case Probability Case Present Value Probability Scenariom 1.00 h 0.25 h 0.25 mhh 61,939 0.06250 227 m 1.00 h 0.25 m 0.50 mhm 61,939 0.12500 227 m 1.00 h 0.25 l 0.25 mhl 58,900 0.06250 161 m 1.00 m 0.50 h 0.25 mmh 61,939 0.12500 227 m 1.00 m 0.50 m 0.50 mmm 61,939 0.25000 227 m 1.00 m 0.50 l 0.25 mml 58,900 0.12500 161 m 1.00 l 0.25 h 0.25 mlh 43,886 0.06250 (32) m 1.00 l 0.25 m 0.50 mlm 43,886 0.12500 (32) m 1.00 l 0.25 l 0.25 mll 41,529 0.06250 (109)







SCENARIO RESULTS (2003 USD million)POWER DEMAND GAS PRICE

CONSTRUCTION COST POWER DEMAND GAS PRICE

Executive Summary vi i i

Actual savings might be even higher under possible future conditions, such as higher-than-expected demand growth or higher-than-expected gas prices. Moreimportantly, however, the decision to purchase a major source of energy at fixed priceis robust to a wide range of behavior for the key uncertain factors that influence theproject’s long-term value-added. In particular, the individual scenarios show that theproject is very robust with respect to fossil fuel price volatility, a feature of energymarkets in recent decades that is expected to persist. As with any risk-return trade-off, the project is also subject to reduced net benefits if future economic conditionsare adverse from the perspective of NT2, i.e., lower-than-expected demand and gasprices.

The commercial analysis, based on market costs expressed in current prices, suggeststhat the decision to purchase NT2 power will result in a nominal savings in presentvalue terms on the order of US$145 million. This result indicates that the projectremains commercially viable even after large real resource benefits accruing to theregion in the economic analysis are paid by project sponsors directly to thegovernment of Lao PDR in the form of taxes, duties, and royalties, and indirectlythrough the funding of environmental and social programming.

I n t roduc t ion 9

1 INTRODUCTION

1.1 Background

Nam Theun 2 (NT2) is a planned hydroelectric project of a thousand megawatts8 inthe Lao PDR to be developed by a private company (NTPC). The Government ofLaos (GOL) is a 25 percent shareholder in NTPC. Upon anticipated commencementof commercial operation in 2009 (FY2010), NTPC will sell fixed amounts of power atpre-negotiated prices to the Electricity Generating Authority of Thailand (EGAT).While NT2 will be operated and maintained by NTPC, the facility will be under thefull dispatch control of EGAT.

The World Bank has supported the GOL in the development of the NT2 Project. Infact, a World Bank Partial Risk Guarantee to NTPC is under consideration.

This study is a component of the Bank’s on-going due diligence process. The work isa complement to an earlier study with the same name, the Regional Economic Least-Cost Analysis of June 2004 (RELC/2004),9 developed in cooperation with theElectricity Authority of Thailand (EGAT), utilizing EGAT’s least-cost planning tools.That study assessed the economic viability of NT2 from a regional10 perspectivethrough a structured “cost-risk” analysis that evaluated the project in light ofalternative outlooks on demand, natural gas prices and NT2 construction costs. Thestudy was conducted solely from an economic perspective.

Rapidly changing events subsequent to the completion of RELC/2004 led The WorldBank to conclude that the earlier results should be completely reassessed. Mostsignificantly, NT2 costs have increased since early 2004, and the world hasexperienced a dramatic increase in fossil fuel prices. Both of these changes potentiallyimpact the viability of the project. Moreover, the Bank concluded that it would beuseful to conduct, along with the economic analysis, a parallel commercial analysis on atotally consistent basis. According to the Bank’s operational guidelines, the economic 8 To avoid possible confusion, we wish to clarify the “exact” capacity of NT2. The developer (NTPC)identifies the capacity as 995 MW (plus 75 MW dedicated to Lao domestic consumption), the rating ofthe installed turbines. EGAT, however, designates the plant as 920 MW, the estimated minimummonthly delivery. The difference between the two numbers is (i) transmission losses to the purchase-point at the Thai border, and (ii) what one EGAT official calls a “margin of security” for the sake ofsystem reliability, so that EGAT can be certain of this minimum level of delivery. The contract permitsEGAT to request more than 100 percent of this capacity with permission from NTPC. For purposesof this study, which adopts a regional perspective, NT2 is defined as a 995 MW plant (i.e., 920 MWdelivered to Thailand plus 75 MW Lao domestic load). The contract is priced and largely defined interms of GWh, hence the MW accounting definition is not important for purposes of this analysis.

9 Robert Vernstrom, Regional Economic Least-Cost Analysis, Bangkok, June 2004. The World Bankfinanced and supervised the study. Throughout this document, the original study is referenced asRELC/2004, while the present study is referenced as RELC.

10 Throughout this document, the word “regional” refers Lao PDR and Thailand.

I n t roduc t ion 1 0

analysis is intended “…to determine whether the project creates more net benefits tothe economy than other mutually exclusive options for the use of the resources inquestion...” and will “…help meet economically efficient demand at the least economiccost.” The parallel commercial analysis is intended to determine if the agreedcommercial arrangements for the project badly distort the economic values and if theagreement appears to be commercially sustainable.

The current study reports the findings of the revised and updated analysis conductedto achieve these expanded objectives. Briefly, the study includes a thoroughcomparison of the real resource cost to the regional economy of power sectordevelopment “with” and “without” NT2. Results incorporate a probabilistic “cost-risk” assessment of this comparison over a range of project uncertainties, includingcapital costs, future gas prices, and Thai load growth. In addition to the realeconomic assessment, a commercial assessment (at nominal prices) is also reported.

The Terms of Reference presented in Appendix A1 detail the Bank's requirements forthe analysis.

1.2 Study Objective

The study outcome is to be determined by means of a results profile known as the“Cost-Risk Framework”. This profile – explained in detail in Chapter 4 – provides forcalculating the probability-weighted present value (PV) costs of either implementingor not implementing NT2 for commercial operation in FY2010, given the interplay ofseveral major uncertain factors – project cost, long-term demand for electricity, andlong-term economic value of natural gas as well as the suggested probabilities ofoccurrence for Base Case, Low and High estimates of these variables. The differencebetween the probability weighted PV cost of implementing the project in FY2010versus not implementing it at all is the decision criteria for this analysis. A lower netpresent value (NPV) “with NT2” would indicate that the project is an acceptableeconomic investment for the regional power market.

In addition to the real resource cost analysis outlined above, the study also includes acommercial assessment of the project under which the economic values are convertedto commercial values and expressed in nominal US dollars, in order to assess thepossible emergence of risks to the commercial sustainability of NT2 in the regionalpower market.

1.3 Organization of the Report

This study is above all a careful review of anticipated electricity demand and supply inthe region, and of the role of NT2 in meeting future requirements.

The next two chapters present the basic demand and supply assumptions adoptedfor the analysis. Chapter 2 reports on the methods used to forecast the power

I n t roduc t ion 1 1

market, and an analysis of results. Chapter 3 summarizes the existing supply system,as well as the cost of candidate plants which could provide future supply.

Chapter 4 presents the methodological approach for the study.

Chapter 5 presents the economic least-cost analysis and results. The chapter beginswith the Base Case evaluation of the project, and then continues with a systematic,probabilistic “cost-risk” assessment of the role of NT2 in light of a broad range offuture planning uncertainties.

Chapter 6 reports a parallel least-cost analysis from a commercial perspective. Thisanalysis is based on the same underlying assumptions as the economic analysisreported in Chapter 5, except that nominal market prices are used instead of realresource costs.

Chapter 7 presents a summary of results, and the conclusion of the study.

System Demand Assumptions 1 2

2 SYSTEM DEMAND ASSUMPTIONS

Load forecasting in Thailand is a collaborative effort of the major stakeholders. TheThailand Load Forecast Sub-committee (TLFS)11 considers all methodological issues,and reviews the work of participating agencies before integrating results into anational load forecast.

The methodologies applied in forecasting have been developed and refined for over adecade, originally with international consulting assistance funded by CIDA, theCanadian development agency. In fact, methods are continuously evolving, as theTLFS strives to refine its techniques with each succeeding forecast. The most recentload forecast of the TLFS was issued in January 2004, and adopted for EGAT’s 2004Power Development Plan. Reflecting recent GOT optimism regarding prospects foreconomic growth, this forecast projects more rapid growth in electricity consumptionthan the immediately preceding forecast of August 2002. RELC/2004 revealed thatmore rapid expansion of the power sector tends to increase the viability of NT2;hence, to provide a more severe Base Case test of the project's economic merit andreduce the risk of overstating Base Case demand, it was decided to conduct thecurrent study based on the more conservative demand forecast of August 2002.Appendix A2 provides a comparison of the two forecasts. However, this report reliesentirely on the lower August 2002 forecast.

Section 2.1 presents an overview of the forecasting methodology. Section 2.2 is areview of historical forecasting performance. Finally, Section 2.3 recommends BaseCase, High and Low demand forecasts for use in this study.

2.1 Overview of the Forecasting Methodology

The national load forecast employs at least five distinct methodologies, with theappropriate technique varying by

distribution company (MEA in greater Bangkok, and PEA in the rest of thecountry)

customer class (i.e., residential, small and large business, industrial, etc.), and

forecast horizon (i.e., short-term or long-term).

11 The committee is comprised of representatives from EPPO (formerly NEPO), EGAT, MEA, PEA,DAEDE (formerly DEDP), NESDB, the National Statistics Office (NSO), the Federation of ThaiIndustries, the Thailand Chamber of Commerce, the Association of Thai Power Generators, and theThailand Development and Research Institute (TDRI).


Four methods are used for energy forecasting. Two of these methods might bedescribed as “bottom up” in that they depend on detailed knowledge of end-users,while two others might be characterized as “top down,” since they depend onmacroeconomic trends. There is also an independent method for forecasting peakdemand. These methods are briefly summarized in the following paragraphs.

End-Use Model. Consumption for residential customers throughoutThailand is derived from comprehensive surveys of dwelling types byincome, and appliance utilization in each. Forecasts depend on growth innumber of households, appliance saturation, and expected applianceefficiency improvement.

Floor Space Model. Short-term (less than 5 years) consumption forlarge business (commercial customers > 30 kW) in the MEA service territoryis forecast based on available data on floor space by type of building. Dataon building stock is adjusted for factors such as demolition, constructiondeferral, occupancy rate, etc. Total consumption is then calculated fromsurvey data on energy use within each type of building. Again, factors areapplied to incorporate efficiency improvement into the forecast.

Energy Intensity Model. Gross domestic product (GDP) is carefullydisaggregated by region and by business sector so that energy consumptionrelationships by sector can be evaluated. Total consumption is derivedbased on historical consumption per unit of gross regional product (GRP),and the forecast growth in GRP by sector. The energy intensity model isused where “first hand” sources (e.g., Board of Expansion data, and surveysof available floor space) are unavailable, especially for longer-termforecasting.

Econometric Regression. When class consumption patterns are notattributed to clearly identifiable relationships (e.g., appliance usage, floorspace, sector energy intensity), econometric regression is used to define therelationship. The method is particularly applied to small business, and toother classes in which users have widely diverse consumptioncharacteristics.

Peak Demand Model. The TLFS has developed substantial loadresearch data by customer group over recent years through extensivesurveys, and applies this information to project demand from energyforecasts developed using the foregoing methods. The number of customerswithin each class is forecast based on regression analysis, and daily loadcurves derived from the load research data are used to forecast coincidentand non-coincident peak for each customer group. Peak losses are alsoforecast via regression equations for each customer class.

Table 1 summarizes the methods currently applied to each customer class.

Economic Growth (Income) Considerations in the Forecast


Growth in electricity demand is highly correlated to medium and long-term economicgrowth prospects (especially economic growth per consuming unit, e.g. per householdor per unit of industrial output). Each of the methods used by the TLFS considerincome, either directly or indirectly. For example, the end-use model forecasts end-use consumption by the stock of dwellings classed by income type. Similarly, the floorspace model directly measures economic expansion among large businesses. Theenergy intensity model relates energy requirements to anticipated growth in valueadded by business sector. Economic regression analysis typically incorporates anincome term (e.g., gross regional product by business sector) into its forecastequations.

Table 1. Current Forecast Methods by Company and Class

Customer Class MEA PEA

Residential End-Use model Same approach, by region

Industry Short-term: First-hand sources(e.g., BOI, applications forservice, targeted surveys)Long-term: Energy intensitymodel (energy intensity per unitof value added)

Same approach, by region

Large Business(>30 kW)

Short-term: Floor Space modelLong-term: Energy intensitymodel by business sector

Energy intensity model bybusiness sector by region

Small Business Econometric regression Same approach, by region

Other Classes Econometric regression Same approach

Peak Demand Daily load curves by customergroup applied to regression-derived customer forecasts byclass. System coincident peakderived from coincident peak ofeach class.

Same approach

Notes: (1) All methods incorporate adjustments for efficiency improvement over time; e.g. end-usemodels assume progressive improvement in efficiency of household appliances, and energyintensity models assume increasing energy efficiency per unit of value added.(2) EGAT direct customers are forecast by individual firm survey.

Thus, the economic forecasts driving Thailand’s national load forecast are a crucialfactor in their accuracy. The Government of Thailand (GOT), through its NationalEconomic and Social Development Board (NESDB), forecasts anticipated nationalGDP, but typically only for five years (i.e., the next national plan). For long-termtrends, the TLFS has relied on the Thailand Development and Research Institute(TDRI) to project economic growth and to disaggregate the national GDP forecast byregion and by business sector. TDRI was hired to develop these trends for the


Sep-97 Sep-01Year Actual IMF/GOT RER MER LER NESDB

1992 8.2%1993 8.5%1994 8.5%1995 8.8%1996 5.7%1997 -1.5% 2.5%1998 -10.8% 3.5%1999 4.2% 5.5% 2.4% 0.6% -0.5%2000 4.3% 6.5% 5.4% 3.7% 2.5%2001 1.8% 6.5% 6.1% 4.4% 3.3%2002 6.4% 4.8% 3.7% 3.5%2003 6.4% 4.9% 3.8% 4.0%2004 6.1% 4.7% 3.6% 5.0%2005 5.9% 4.6% 3.5% 5.0%2006 5.9% 4.6% 3.6% 5.5%2007 6.2% 4.9% 3.9%2008 6.0% 4.7% 3.8%2009 5.8% 4.7% 3.9%2010 5.6% 4.6% 3.8%2011 5.3% 4.6% 3.8%

Average Annual Growth (%)2001-06 6.1% 4.7% 3.6% 4.6%2006-11 5.8% 4.7% 3.8%

Annual GDP Forecast Error (%, for full-year forecasts after 1997) 2/1998 14.3%1999 1.3% -1.8% -3.6% -4.8%2000 2.2% 1.1% -0.6% -1.8%2001 4.7% 4.3% 2.6% 1.5%

1/ RER - rapid economic recovery, MER - medium economic recovery, LER - low economic recovery 2/ Differernce between actual and forecast GDP growth rates.

Sep-98 Forecasts Assumptions 1/

September 1998 forecast, and is revising economic projections which will be applied infuture load forecasts. TDRI applies a very complex model to develop these results.12

Table 2. National GDP Growth Assumptions

National economic projections applied for recent load forecasts are compared inTable 2.

12 TDRI uses a “computable general equilibrium model (CGE)” for making macroeconomicprojections. This is the same type of model that NESDB uses to prepare official economic forecasts forthe five-year national plans. The model is very large and requires considerable time to readjust andcalibrate a new forecast series. The most time-consuming part of the projection process, however, isto allocate the 15-year macroeconomic forecast into MEA and PEA regions and the correspondingcustomer sub-groups specified by TLFS. For this task, TDRI needs to conduct detailed surveys inorder to establish baseline information for each regional forecast. The TLFS requires long temeconomic projections broken down at this high level of detail in order to run its end-use load forecastmodel. As a result, the process is very time consuming and costly.

While we have no reason to doubt the methodology employed by TDRI, or the accuracy of its results,the approach has the disadvantage that a new demand forecast cannot be easily produced in responseto alternative views of economic growth. Given the difficulty that all economists have experienced inforecasting national (and international) economic growth in recent years, this slow response timecould be disadvantageous.


The August 2002 load forecast adopted the Sep-98 (MER) economic outlook for theperiod following NESDB’s near-term prediction (i.e., 2006-11). The TLFS noted thatthe 4.7% average annual GDP growth under MER for the Ninth Plan (2001-06) wasvery close to the NESDB’s projection of 4.6% for the same period. Furthermore, theTLFS believed that the average long term annual growth rate of 4.7% assumed in theSep-98 (MER) was still a reasonable estimate. Therefore, the committee decided toadopt the NESDB short-term and MER long-term economic outlooks for the Aug-02load forecast.13

Recent economic growth trends – and medium-term forecasts – are more optimisticthan the foregoing assumptions reflect. Actual 2003 growth will be approximately 6percent; the GOV is projecting 2004 growth of about 8 percent. The World Bank iscautiously optimistic, expecting 6 percent growth in 2004, but expressing severalconcerns regarding the sustainability of high growth in the medium-term.

Specifically, the Bank notes that private consumption has been the chief driver ofrecent expansion, and that private investment's contribution to growth has been lessthan in previous economic recoveries and remains lower than that of many othercountries in the region. Corporate access to credit has been constrained by acautious banking sector and slow structural reforms. Export growth has beenrelatively strong, however, an appreciating exchange rate, capacity constraints, andgrowing competition in the region could restrain this growth. Further, the rate ofnon-performing loans (NPLs) has not declined and re-entry NPLs have increased.Progress in banking and capital market reform, and in legal reform, has been limited. Insummary, World Bank economists argue that Thailand will need to improve itscompetitiveness and productivity in order to convert the current recovery intosustained high growth over the medium-term.

Price Considerations in the Forecast

The load forecasting methodologies do not explicitly consider price as an independentvariable in forecasting demand. However, the impacts of historical price changes arecaptured in the forecasts. For example, surveys for the end-use forecasts reflect pricechanges through adjustments in appliance usage and saturation. Floor space modelscapture changes in energy use per unit of floor space which may have occurred inpart due to changes in electricity price.

Thus price is indirectly reflected in current forecasting methodologies.

Energy Conservation in the Forecast

In addition to incorporating adjustments for energy efficiency improvement in eachclass load forecast, the August 2002 Base Case is further adjusted downward toreflect the impact of a group of on-going electric energy conservation programs being

13 While it is beyond the scope of the current study to produce a new load forecast, it should benoted that recent economic performance of Thailand has exceeded forecasts, and analysts aregenerally optimistic regarding medium-term economic growth prospects.


undertaken by various GOT agencies, including EPPO (formerly NEPO), DAEDE(formerly DEDP), and EGAT.

Table 3 summarizes the complete package of conservation activities; this packagerepresents the official plan of the GOT adopted by the Cabinet. The final lines of thetable show the conservation program included in the Aug-02 Base Case forecast.(The forecast excludes 2,516 GWh of conservation savings achieved by FY2002;TLFS has assumed that this conservation is already reflected in base year consumptiondata.)

In fact, the TLFS has been very concerned about the effect of energy efficiencyimprovement on future electricity demand, and established a special working group tomake a detailed assessment of the various conservation-related programs. Thefindings of that group indicated that official estimates were probably too high, for thefollowing reasons:

Only about 15% of the planned electricity demand reduction in the next 10years is expected to come from mandatory programs where the set targetsare reasonable. The remaining 85% reduction in electricity demand isanticipated to come from numerous voluntary programs. The success ofthese programs will depend on their implementation procedures andconsumer willingness to participate. These factors are not yet clearlydefined.

Several programs have missed implementation deadlines, and many areexpected to face further delay. Other programs (e.g., switching streetlighting off late at night) have faced opposition from highway safetyengineers, and may not be implemented.

After considerable debate, the TLFS decided to reduce the amount of conservedelectricity by nearly 30% in the year 2011 for the Aug-02 load forecast. (An evengreater cut was considered, but it was decided to give the programs an opportunityto achieve targeted progress. A more critical evaluation will be incorporated intosubsequent load forecasts.) The forecast incorporates a total conservation savings of982 MW by 2011.


ResponsibleAgency 2003 2004 2005 2006 2007 2008 2009 2010 2011

1. GOT Cabinet Programs EPPO 1/ 1,670 1,785 1,907 2,038 2,175 2,317 2,481 2,637 2,797

2. Mandatory Programs DAEDE 2/ 559 848 1,064 1,280 1,280 1,280 1,280 1,280 1,280 - Buildings 193 330 394 458 458 458 458 458 458 - Factories 156 280 404 529 529 529 529 529 529 - Government Buildings 210 238 266 293 293 293 293 293 293

3. SME Programs EPPO 271 612 1,068 1,332 1,597 1,864 2,132 2,401 2,672 - Value Engineering 48 112 176 240 304 368 432 496 560 - SME Standards 131 306 480 655 830 1,005 1,179 1,354 1,529 - Research Projects 92 194 412 437 463 491 521 551 583

4. Residential Programs EPPO 656 838 987 1,144 1,386 1,523 1,667 1,820 1,922 - HH Design Standards 198 252 313 381 457 539 629 727 834 - EGAT DSM Program EGAT 429 409 389 369 349 328 308 288 268 - MEP Program 3/ - 125 210 295 435 495 555 615 615 - Efficiency Labeling 29 52 76 99 145 160 175 190 205

5. Recycling Progam EPPO 19 22 35 67 101 116 121 138 158

Total Planned Conservation Program 3,174 4,105 5,061 5,862 6,540 7,101 7,682 8,277 8,830

Conservation in Aug-02 Forecast - GWh 4/ 658 1,589 2,545 3,346 4,024 4,585 5,166 5,761 6,314 Conservation in Aug-02 Forecast - MW 5/ 102 247 396 520 626 713 803 896 982 % of planned conservation program 21% 39% 50% 57% 62% 65% 67% 70% 72%

1/ Energy Policy and Planning Office (formerly NEPO).2/ Department of Alternative Energy Development and Efficiency (formerly DEDP).3/ Minimum efficiency standards for household appliances.4/ Aug-02 forecast excluded 2,516 GWh assumed to have already been realized in the forecast base year (FY 2002).5/ Estimate based on system load factor; a conservative assumption since some programs target load shifting and peak reduction.

ProgramPlanned Conservation Savings (GWh)

Table 3. Integrated National Electricity Conservation Program

The conservation program outlined in Table 3 is part of a 10-year master plandeveloped by responsible GOT agencies, which emphasized technical/economicpotential rather than financial/legal constraints.14

Table 4 presents an informal “order of magnitude” alternative view of conservationpotential based on the Consultant’s discussions with conservation planners. Thisalternative scenario is presented for discussion purposes only, intended to crudelyquantify the widely held opinion that the program in Table 3 may be unduly optimisticwith regard to potential savings. The alternative view in Table 4 suggests that onlyhalf of the conservation assumed in the Aug-02 forecast may be achieved by 2011,and perhaps three-quarters of that target by 2016. In other words, the load forecastcurrently used by EGAT almost certainly assumes greater conservation than theelectricity sector will actually achieve over the forecast period.15

14 Most of the funding for energy conservation will come from the “ENCON Fund’, which is financedthrough a targeted tax on petroleum products of THB 0.40 per liter.

15 Unlike some of the other programs, EGAT’s own DSM Program has been proceeding according toplan. The program is funded directly by EGAT (vs. the ENCON Fund), and conservation savings areprojected to exceed the level forecast in the consolidated national conservation plan (Table 3). InTable 4, we have adopted EGAT’s forecast of DSM savings through FY2006, and have conservativelyassumed no increases thereafter.


Table 4. National Conservation Program – Alternative View

EPPO is currently developing a more realistic program guided on funding and otherlimitations. As of the publication of this study, a conservation action plan is not yetfinalized. Significantly, however, EPPO reports Cabinet-level approval for a majorreduction in national energy consumption, expressed as a target energy elasticity of1.0 versus the current level of 1.3 or more (see Section 2.2). Although this is aworthwhile objective, it is perhaps premature to presume the schedule for meeting ofthis goal, given that no action plan is in place, and no performance record exists fromwhich to define a realistic pace for achieving the target.

It is important to put these conservation savings in perspective. The total savings aresignificant – on the order of 1,000 MW by 2011 (Table 3) or 2016 (Table 4).However, these capacity and associated energy savings represent less than one-year’snational demand growth (even when assuming a low demand forecast); hence, theydo not obviate the need for continued expansion of the generating system.

2.2 Comparison of Forecast Results

The TLFS has prepared a total of 12 national load forecasts since 1993. Tables 5 and6 summarize the Energy Requirements and Peak Demand projections from many ofthese forecasts, excluding those prepared immediately before and after the onslaughtof the Asian economic crisis in July 1997. The crisis, with its profound impact on theThai economy, including electricity consumption, rendered earlier forecasts irrelevantfor future planning.16 Even the first “post-crisis” forecast (September 1997) provednaively optimistic in its outlook for economic recovery. (Thai forecasters, likeeconomists everywhere, simply did not foresee the depth and duration of the crisis.)It can be observed that the forecasts in the tables are progressively lower.

16 The highest forecast (April 1996) projected peak demand in fiscal year 2002 to be over 40 percent(7,000 MW) above the recorded peak of 16,681 MW. That same forecast also projected demand in2011 to exceed 42,000 MW, 45% more than the August 2002 forecast.

ResponsibleAgency 2003 2004 2005 2006 2007 2008 2009 2010 2011 2016

1. GOT Cabinet Programs EPPO 1,670 1,785 1,907 2,038 2,175 2,317 2,481 2,637 2,797 3,599

2. Mandatory Programs DAEDE 20 146 272 398 524 650 776 902 1,028 1,280

3. SME Programs EPPO 54 122 214 266 319 373 426 480 534 921

4. Residential Programs EPPO 586 588 726 905 1,068 1,237 1,491 1,643 1,800 2,684 - incl. EGAT DSM Prgm EGAT 536 488 546 530 530 530 530 530 530 530

5. Recycling Progam EPPO 19 22 35 67 101 116 121 138 158 257

Total Conservation - Alternative View 2,350 2,664 3,153 3,675 4,188 4,694 5,296 5,800 6,318 8,740

Alternative Conservation Forecast - GWh 3/ 292 606 1,095 1,617 2,129 2,635 3,238 3,742 4,259 6,682 Alternative Conservation Forecast - MW 4/ 45 94 170 251 331 410 504 582 662 1,039 % of planned conservation program 9% 15% 22% 28% 33% 37% 42% 45% 48% 76% % of Aug-02 conservation forecast 44% 38% 43% 48% 53% 57% 63% 65% 67% 106%

1/ Informal Consultant estimate based on discussions with participants.2/ Assuming slower start-up (1-2 year delay), slower growth (original program or scaled back program spread over 10 years), but continuing growth after 2011.3/ Excludes 2,058 GWh assumed to have already been realized in the forecast base year (FY 2002).4/ Estimate based on system load factor; a conservative assumption since some programs target load shifting and peak reduction.

ProgramPlanned Conservation Savings (GWh) 1/, 2/


Table 5. Historical Energy Requirements Forecasts (GWh)

The forecast of September 1998 was much more successful at incorporating thepotential implications of the crisis on electricity consumption. It included threescenarios based on anticipated speed of economic recovery – rapid (RER), medium(MER), and low (LER). Two subsequent forecasts (February 2001 and August 2002)have refined these results in response to revised economic growth scenarios from theGovernment of Thailand (NESDB), and incorporated conservation program planning.

The dramatic changes in near-term expectations regarding national electricityrequirements are obvious in Tables 5 and 6. But it is equally interesting to observefrom the tables that expected average annual growth rates for medium to long-termprojections show little variation. For the period 2001-06, the annual rate of growthin demand is between 5.9 and 6.5 percent in five of the eight forecasts. Two others –the Sep-98 RER (“rapid economic recovery”) and LER (“low economic recovery”) –were intended as High and Low scenarios to bracket a medium (“MER”) forecast. Forthe period 2006-11, five forecasts project average annual generation growth between5.7 and 6.3 percent.

Fiscal Actual Jun-93 Dec-94 Oct-95 Feb-01 Aug-02Year GWh RER MER LER Base Base

1993 62,180 62,797 1994 69,651 69,407 1995 78,880 76,388 78,023 1996 85,924 83,896 85,571 89,375 1997 92,725 91,178 92,879 97,849 1998 92,134 99,334 100,383 105,938 1999 90,414 106,891 108,160 114,029 96,904 93,178 91,834 2000 96,781 115,136 116,795 122,289 103,709 97,858 94,570 2001 103,165 124,158 126,025 131,698 111,475 103,685 98,108 103,946 2002 108,383 132,330 134,041 140,032 120,148 110,436 102,429 110,945 108,036 2003 141,138 142,849 149,076 129,080 117,341 106,947 118,540 114,754 2004 150,283 152,529 158,989 138,647 124,532 111,736 126,449 122,024 2005 159,668 162,187 168,894 149,439 132,228 116,980 134,794 130,232 2006 169,545 171,745 178,706 161,378 141,300 122,756 143,748 139,000 2007 179,533 181,745 188,881 174,490 151,322 129,738 152,743 147,835 2008 190,380 193,505 200,739 188,005 162,438 137,996 162,438 157,064 2009 201,642 204,956 212,213 200,949 173,532 146,979 173,532 168,004 2010 213,395 216,428 223,645 214,215 184,213 156,032 184,213 178,079 2011 225,720 228,445 235,564 227,993 194,930 164,381 194,930 188,446 2012 206,660 199,378 2013 219,134 211,146 2014 232,106 223,437 2015 245,948 236,364 2016 260,262 249,878

Average Annual Growth (%)2001-06 6.4% 6.4% 6.3% 7.7% 6.4% 4.6% 6.7% 6.1%2006-11 5.9% 5.9% 5.7% 7.2% 6.6% 6.0% 6.3% 6.3%2011-16 6.0% 5.8%

Forecasts by Publication DateSep-98


Table 6. Historical Peak Demand Forecasts (MW)

This similarity of result is surprising, given that each forecast started from a differentbase and with different macroeconomic expectations (the associated national GDPforecast, as reported in Table 2). Table 7 shows the simple income (GDP) elasticity ofdemand implied by each energy requirements forecast.17

These elasticities have typically ranged from 1.30 to 1.40, with many individual yearelasticities falling outside this narrow band.18 Considering that income elasticity wasnot a basis for energy forecasting of many consumer categories, the implied elasticitiesare surprisingly stable across these recent forecasts.19 Interestingly, however, thehighest of these forecasts (Sep-98 RER) had lower-than-average income elasticities,and the lowest forecast (Sep-98 LER) has somewhat higher-than-average incomeelasticities, in later forecast years. This confirms that income elasticities were not thebasis for these forecasts.

17 Clearly, a far more meaningful elasticity measure would be income per consuming unit by customerclass (e.g., electricity consumption growth per consuming unit of industrial value added per companyor per commercial establishment). We have used a far less detailed approach, since our objective isonly to confirm to reasonableness of the Base Case forecast.

18 The TLFS has independently estimated income (GDP) elasticity of demand. We understand thatthese unpublished investigations estimated an average income elasticity of about 1.4.

19 The actual experience reported in Table 7 for the period 1995-2001 tells a somewhat differentstory; electricity demand appears to have been far more stable than the performance of the incomevariables, causing remarkable variance of the implied elasticity from year to year.

Fiscal Actual Jun-93 Dec-94 Oct-95 Feb-01 Aug-02Year GWh RER MER LER Base Base

1993 9,730 9,978 1994 10,709 10,975 1995 12,268 11,993 11,993 1996 13,311 13,103 13,103 13,637 1997 14,506 14,193 14,193 14,892 1998 14,180 15,315 15,315 16,075 1999 13,712 16,446 16,446 17,268 14,972 14,499 14,287 2000 14,918 17,685 17,685 18,527 16,037 15,254 14,762 2001 16,126 19,029 19,029 19,899 17,286 16,214 15,398 16,184 2002 16,681 20,237 20,237 21,139 18,678 17,308 16,150 17,388 16,700 2003 21,440 21,440 22,368 20,042 18,399 16,892 18,587 17,843 2004 22,690 22,690 23,654 21,597 19,611 17,746 19,913 19,029 2005 23,997 23,997 24,995 23,223 20,818 18,588 21,222 20,295 2006 25,371 25,371 26,392 24,958 22,168 19,467 22,552 21,648 2007 26,835 26,835 27,894 26,950 23,728 20,575 23,951 23,020 2008 28,409 28,409 29,467 29,021 25,450 21,861 25,450 24,450 2009 30,044 30,044 31,073 31,090 27,232 23,268 27,232 26,143 2010 31,749 31,749 32,756 33,132 28,912 24,671 28,912 27,711 2011 33,532 33,532 34,509 35,216 30,578 25,951 30,587 29,321 2012 32,405 31,014 2013 34,352 32,842 2014 36,366 34,743 2015 38,519 36,754 2016 40,699 38,851

Average Annual Growth (%)2001-06 5.9% 5.9% 5.8% 7.6% 6.5% 4.8% 6.9% 6.1%2006-11 5.7% 5.7% 5.5% 7.1% 6.6% 5.9% 6.3% 6.3%2011-16 5.9% 5.8%

Sep-98Forecasts by Publication Date


Table 7. Implied Income Elasticity of Energy Requirements Forecasts

Table 8 summarizes forecast performance in terms of accuracy for each year afterpublication, excluding the “crisis years.” With few exceptions, demand and energyforecasts have been accurate to within a couple of percent in their early years.(Perhaps the error observed in the October 1995 energy forecast was an earlywarning of the pending crisis.) This performance suggests that the short-termforecasting models employed by the TLFS have performed well. In the longer term,the dramatic distortions of the 1997 Asian economic crisis make it difficult to assessthe accuracy of Thailand’s forecasting models under a period of more stable marketconditions.

Table 8. Historical Forecast Accuracy 1 /

Years Jun-93 Dec-94 Oct-95 Feb-01Forecast RER MER LER Base

Energy Requirements 1 -3.2% -1.1% 4.0% 7.2% 3.1% 1.6% 0.8%2 -2.4% -0.4% 5.5% 7.2% 1.1% -2.3% 2.4%3 -1.7% 0.2% 8.1% 0.5% -4.9%4 10.9% 1.9% -5.5%

Peak Demand1 -2.2% -2.2% 2.4% 9.2% 5.7% 4.2% 0.4%2 -1.6% -1.6% 2.7% 7.5% 2.3% -1.0% 4.2%3 -2.2% -2.2% 7.2% 0.5% -4.5%4 12.0% 3.8% -3.2%

1/ Percent by which forecast exceeded (fell short of) requirement in each full yearafter publication.

Sep-98Forecasts by Publication Date

Years Jun-93 Dec-94 Oct-95 Feb-01Forecast RER MER LER Base

Energy Requirements Forecasts1 -3.2% -1.1% 4.0% 7.2% 3.1% 1.6% 0.8%2 -2.4% -0.4% 5.5% 7.2% 1.1% -2.3% 2.4%3 -1.7% 0.2% 8.1% 0.5% -4.9%4 10.9% 1.9% -5.5%

Peak Demand Forecasts1 -2.2% -2.2% 2.4% 9.2% 5.7% 4.2% 0.4%2 -1.6% -1.6% 2.7% 7.5% 2.3% -1.0% 4.2%3 -2.2% -2.2% 7.2% 0.5% -4.5%4 12.0% 3.8% -3.2%

1/ Cumulative percent by which forecast exceeded (fell short of) actual requirementin each full year after publication.

Forecasts by Publication DateSep-98

Feb-01 Aug-02Year Actual RER MER LER Base Base

1994 1.41 1995 1.51 1996 1.57 1997 n/m1998 0.06 1999 n/m2000 1.64 1.30 1.37 1.18 2001 3.66 1.23 1.35 1.14 2002 1.23 1.36 1.20 1.92 2003 1.17 1.28 1.16 1.71 1.55 2004 1.22 1.31 1.25 1.33 1.27 2005 1.33 1.36 1.35 1.32 1.35 2006 1.35 1.49 1.39 1.21 1.22 2007 1.30 1.46 1.46 1.29 1.31 2008 1.29 1.55 1.66 1.34 1.32 2009 1.18 1.44 1.69 1.44 1.47 2010 1.19 1.33 1.62 1.33 1.30 2011 1.21 1.28 1.43 1.28 1.28

Average Annual Growth (%)2001-06 1.53 1.26 1.36 1.27 1.50 1.34 2006-11 1.24 1.41 1.57 1.34 1.33

1/ Energy forecasts adopted Sep-98 (MER) economic growth forecast after 2006.n/m - not meaningful

Sep-98 Forecasts Assumptions


2.3 Load Forecast Adopted for this Study

The August 2002 Base Case load forecast20 is the planning basis for EGAT’s PDP2003, and is used for the current study. It is a technically and methodologically soundbasis for future system planning.

Due to the unique regional perspective of the present study, there are differencesbetween the Base Case forecast used in this report and the August 2002 loadforecast. Specifically, the Base Case forecast includes Lao domestic load which isassumed to grow enough to utilize its allocated share of total NT2 project output.Thus, starting in FY2010, the August 2002 forecast is increased by 300 GWh of netgeneration and 75 MW of peak demand.21

Low and High demand forecasts, as requested by the World Bank, reflect a wide bandof future loads. Based on the Bank's extensive experience with long-term loadforecast accuracy around the world, the Bank specified the Low and High Casedemand forecasts to be symmetrically keyed off the Base Case forecast using thefollowing equations, reflecting the percentage gap between these forecasts that theBank considers appropriate by year 10 of the forecast period:

(1+grL)^10 = 0.75*(1+grB)^10 [for the low case]

(1+grH)^10 = 1.25*(1+grB)^10 [for the high case]

where “grB” means Base Case growth rate of demand, “grL” means Low Casegrowth rate of demand and “grH” means High Case growth rate of demand.

Thus, the Low Case forecast is set to a growth rate at which the capacity and energyrequirements in FY2012 are 75 percent of the Base Case requirements. Symmetrically,the High Case load forecast in FY2012 is 125 percent of the Base Case requirement.The constant annual growth rates implied by these results are applied to all forecastyears.

Table 9 summarizes all three forecast scenarios adopted for this study. The averageannual growth rates of these scenarios range from a Low of about 3.4 percent to aHigh of nearly 9 percent. This wide band subsumes the range of futures that havebeen projected in the recent past: (i) the GOT's very optimistic economic growthand energy conservation targets, (ii) the World Bank's more cautious growthperspective coupled with slower energy elasticity improvement, and (iii) the slower

20 For readers who would like to review the August 2002 forecast in greater detail, complete resultsby customer class for MEA, PEA, and direct customers of EGAT are reported in Appendix A2.

21 A necessary corollary of this assumption is that Laos’ alternative to NT2 for meeting this portion ofits demand would be import of electricity from Thailand. Further, this load increment is presumed tomirror the Thai load curve, a simplifying assumption that avoids separate modeling of the Lao system.Given planned changes to that system over coming years (including regional grid integration andpossible introduction of TOU tariffs to flatten the curve), modeling of the future Lao system would bespeculative at best.


growth outlook that drives the Base Case forecast. The volatility of recent economicprognostications highlights the futility of projecting long-term economic performancewith accuracy; it is reassuring to know that the current analysis incorporatesconsideration of this uncertainty.

Note that the forecasts presented in the table exclude station use in order toconform to the requirements of the model (“PROSCREEN II”) used for least-costexpansion planning. Net generation and net peak forecasts are shown; theseforecasts are on the order of 2 percent lower than the Base Case forecast reported inTables 5 and 6.

Table 9. Recommended Load Forecast for this Study

High Base Low High Base Low2002 - 104,970 - - 16,328 - 2003 114,246 111,310 108,557 17,774 17,350 16,889 2004 124,343 118,506 112,267 19,349 18,520 17,470 2005 135,331 126,516 116,103 21,063 19,749 18,070 2006 147,291 135,039 120,070 22,928 21,057 18,691 2007 160,307 143,847 124,173 24,959 22,440 19,334 2008 174,474 153,214 128,417 27,170 23,896 19,998 2009 189,892 164,204 132,805 29,577 25,599 20,685 2010 206,974 174,688 137,643 32,272 27,263 21,471 2011 225,238 185,141 142,336 35,124 28,889 22,207 2012 245,116 196,153 147,190 38,229 30,598 22,967 2013 266,751 208,007 152,209 41,608 32,442 23,754 2014 290,298 220,372 157,400 45,287 34,358 24,568 2015 315,926 233,649 162,769 49,292 36,435 25,410 2016 343,819 247,466 168,320 53,652 38,590 26,280

Average Annual Growth (%)2002-06 8.8% 6.5% 3.4% 8.9% 6.6% 3.4%2006-11 8.9% 6.5% 3.5% 8.9% 6.5% 3.5%2011-16 8.8% 6.0% 3.4% 8.8% 6.0% 3.4%2002-16 8.8% 6.3% 3.4% 8.9% 6.3% 3.5%2002-12 8.9% 6.5% 3.4% 8.9% 6.5% 3.5%

1/ All cases exclude station use; forecasts reflect net generation and net peak as utilized by the PROSCREEN model.

2/ All cases include Lao domestic load (300 GWh, 75 MW) from FY2010, theenergy and demand assumed to be fully absorbed from NT2 project output.

RECOMMENDED LOAD FORECAST (net, including Lao Load) 1/,2/Gross Energy Requirement (GWh) Peak Demand (MW)

System Supply Assumptions 2 5

3 SYSTEM SUPPLY ASSUMPTIONS

This Chapter of the report describes the existing power system and the optionsavailable for system expansion in order to provide for the demand growth identified inChapter 2.

Section 3.1 summarizes the existing power system. Section 3.2 describes candidatesfor system expansion, including their capital and operating costs. Assumed fuel pricesfor the system are presented in Section 3.3. Section 3.4 is a preliminary screeninganalysis of thermal expansion candidates that illustrates their competitive advantagesat different utilization factors. Finally, Section 3.5 discusses the non-thermalalternative for meeting future expansion requirements – NT2.

3.1 Installed and Planned System Capacity

The study adopts PDP 2003, as published by EGAT in April 2003, as the basis fordefining the existing system, committed additions and retirements. All tables andcalculations reported in this and subsequent chapters of the report assume the samebase as PDP 2003.22

Table 10 summarizes EGAT’s installed and purchased capacity as of March 2003.EGAT’s own system is dominated by thermal capacity, accounting for over half of thetotal. These units are predominantly gas-fired, although more than 2000 MW oflignite capacity are still in service. Purchased power is a major source of supply,accounting for over 40 percent of total available capacity. Although not shown in thetable, this segment, too, is predominantly gas-fired thermal. Large thermal units –whether oil, lignite, or gas-fired, including purchased power from IPPs and SPPs – havean availability factor of at least 80 percent. (Detailed data by plant is presented inAppendix A4.)

Thailand’s hydro capacity is almost entirely reservoir storage. (The exception is 136MW Pak Mun Dam.) Dependable hydro generation, exogenously estimated usinghistorical records from each site, represents the level of energy assumed to be availableby month at the 90 percent confidence level. Capacity factors are relatively low.

Lao imports represent purchases of energy from Theun Hinboun and Huay Hohydroelectric plants whose collective capacity factor is about 65 percent.

22 It should be noted, however, that there are minor discrepancies between actual and plannedinstalled capacity as of end-FY2003 due to minor delays and adjustments in scheduled plant additions(see Appendix A4).


Table 10. Installed and Purchased Capacity (as of March 2003)

Table 11 summarizes committed plant additions from March 2003.23 The table isdivided into four groups – EGAT plants, IPPs, SPPs, and NT2 – with a total capacityof nearly six thousand MW including NT2. The first three plants listed are underconstruction and scheduled to commence commercial operation in FY2003-04. Thesecond group (3,447 MW) includes three IPP plants whose firm contracts have facedlong delays due to multiple factors including the Asian economic slowdown andconcerted environmental opposition; these issues have been resolved and schedulesare now considered firm. The third group (197 MW) includes SPP plants (90 MWmaximum plant capacity) under contract for commissioning in the next three years.(Only plants approved by the Energy Conservation Fund as of March 2003 areincluded.)

23 The study assumes installed capacity of 25,697 MW as of September 2003, equal to September2002 installed capacity of 23,530 plus 2,167 MW added in FY2003; the FY2003 additions are dividedbetween Table 10 (1,848 MW) and Table 11 (319 MW).

No. ofPlants MW %

1. Hydroelectric 20 2,886 11% - Plants >100 MW 6 2,640 10% - Plants 5-100 MW 8 244 1% - Smaller Plants 6 3 0%

2. Thermal 3 6,030 24% - Oil/Gas 2 3,630 14% - Lignite 1/ 1 2,400 9%

3. Combined Cycle (Gas) 4 5,075 20%

4. Gas Turbine 3 778 3% - Gas 2 412 2% - Diesel 1 366 1%

5. Diesel 1 6 0%

6. Renewable 1 0.5 0%

7. Purchased Power 38 10,602 42% - Privatized Plants 2/ 3 5,671 22% - IPP 3/ 4 2,463 10% - SPP 28 1,828 7% - Lao Imports 4/ 2 340 1% - Malaysia Tie (TNB) 1 300 1%

TOTAL 70 25,378 100%

1/ Excluding 3 x 75 MW at Mae Moh retired but providing cold reserve. 2/ Includes Khanom 824 MW, Rayong 1232 MW, Ratchaburi 3615 MW. 3/ Includes Independent Power 700 MW, Tri Energy 700 MW, Bowin Power 713 MW, Eastern Power 350 MW. 4/ Includes Theun Hinboun Hydro 340 MW, Houay Ho Hydro 126 MW.

Installed CapacityPlant / Fuel Type


Table 11. Committed Plant Additions (after March 2003)

Nam Theun 2 is also a committed plant in EGAT’s generation expansion plan,scheduled for commercial operation in FY2010. Although the plant is included in thetotals reported in Table 11, NT2 is treated as an expansion candidate for purposes ofthe economic analysis in this study.

Retirements scheduled for the period FY2003-1424 are summarized in Table 12. Wehasten to add that this retirement schedule is a drastic oversimplification, reflectingmainly the “planned life” for each plant type.25 It is EGAT policy to assume fixed unitlives for planning purposes. However, should units be performing well as theyapproach their planned retirement date, a plant-specific study is undertaken todetermine whether extending the service life would be cost-effective, given anyrequired investment for reconditioning.

24 As explained in the following chapter, FY2003-14 is the planning period for our analysis.

25 The Khanom Thermal plant is an exception, scheduled for early retirement in FY2007 when a farmore efficient gas-fired combined cycle plant is expected to be available in the South.

CapacityMW

1. EGAT Projects 1,307 - Lam Takhong Pumped Storage 500 - Krabi Thermal #1 300 - Lan Krabu GT 122 - Khanom CC 385

2. IPP Contracts 1/ 3,447 - BLCP Power - Unit 1 673 - BLCP Power - Unit 2 673 - Gulf Power 700 - Union Power Development - Unit 1 700 - Union Power Development - Unit 2 700

3. SPP Contracts 2/ 197 - Phase I Contracts 69 - Phase II Contracts (Renewables) 128

4. Nam Theun 2 Hydro 3/ 995

TOTAL 5,945

1/ Includes committed plants with planned COD after March 2003 as reported in PDP 2003 (April 2003) 2/ SPP plants approved but not in operation as of March 2003. 3/ This regional study defines NT2 as 995 MW, inclusive of the 75 MW Lao domestic load it will also serve; PDP 2003 defines the plant as 920 MW delivered to the Thai system.

FY2007FY2007FY2008FY2008FY2009

FY2010

FY2003-05FY2003-05

FY2003-04FY2003-04

FY2007

PlantEGAT Planned

Commissiong Date 1/

FY2003-04

CapacityMW

1. EGAT Projects 1,307 - Lam Takhong Pumped Storage 500 - Krabi Thermal #1 300 - Lan Krabu GT 122 - Khanom CC 385

2. IPP Contracts 1/ 3,447 - BLCP Power - Unit 1 673 - BLCP Power - Unit 2 673 - Gulf Power 700 - Union Power Development - Unit 1 700 - Union Power Development - Unit 2 700

4. SPP Contracts 2/ 197 - Phase I Contracts 69 - Phase II Contracts (Renewables) 128

5. Nam Theun 2 Hydro 3/ 995

TOTAL 4/ 4,950

1/ Includes committed plants with planned COD after March 2003 as reported in PDP 2003 (April 2003) 2/ SPP plants approved but not in operation as of March 2003. 3/ This regional study defines NT2 as 995 MW, inclusive of the 75 MW Lao domestic load it will also serve; PDP 2003 defines the plant as 920 MW delivered to the Thai system. 4/ Total does not include NT2.

FY2007FY2007FY2008FY2008FY2009

FY2010

FY2003-05FY2003-05

PlantEGAT Planned

Commissiong Date 1/

FY2004FY2004FY2004FY2007


Table 12. Schedule of Retirements (FY2003-14)

EGAT has concluded that life extension is economically justified for thermal capacityat South Bangkok (units 3 through 5), and Bang Pakong;26 these reconditioned unitsare included in PDP 2003. The current study evaluates these four retiring thermalunits as candidates for reconditioning (see Section 3.2). Only two retiring plants arenot considered for reconditioning – Bank Pakong Combined Cycle (units 1 and 2)due to excess environmental emissions, and Khanom Thermal (units 1 and 2) in theSouth due to the availability of significantly lower cost energy.

3.2 Thermal Expansion Candidates

EGAT has identified a number of candidate plants for long-term system expansion.This Study has focused on four new candidate options which might be expected tomeet future capacity requirements. These are: (i) oil-fired steam thermal, (ii) coal-firedsteam thermal, (iii) gas-fired combined cycle, and (iv) gas turbines. The study alsoconsiders reconditioning of a group of large thermal units scheduled for retirementduring the study period (i.e., South Bangkok Thermal and Bang Pakong Thermal). Allof these candidates are summarized in Table 13.

The capital costs, lives, and operating cost assumptions for each candidate have beenreviewed and approved by the World Bank based on both (i) discussions regardingEGAT’s recent experience, and (ii) the Bank’s own experience with large powerprojects in other countries. In particular, the Bank wished to have the study reflectevidence of a spread of US$200/kW between the cost of gas turbine (GT) andcombined-cycle (CCGT) capacity to reflect EPC cost differences (includingdevelopment cost margins). Hence, Bank-recommended values of US$250/kW for GTcapacity and US$450/kW for CCGT capacity have been adopted.

26 Parallel investigations by EGAT have concluded that life extension is not justified for South Bangkokunits 1-2 or the combined cycle units at Bang Pakong.

Unit CapacityNo(s). MW Date(s) Age at retirement

1. Thermal 2,030 - South Bangkok 1-2 2x200 Sep-2006, 2007 36

3-5 3x310 Sep-2009, 2010, 2012 35 1/ - Khanom Thermal 1-2 2x75 Jan-07 26,18 2/ - Bang Pakong 1 550 Sep-13 30 1/

2. Combined Cycle 760 - Bang Pakong 1-2 2x380 Sep-2007, 2008 25 3/

3. Gas Turbine 140 - Lan Krabu various 140 depends on available gas 30+

TOTAL 4/ 2,790

1/ Under PDP 2003, these units are to be "repowered" (I.e., reconditioned for service as after this date). 2/ Early retirement due to availability of lower cost generation. 3/ Retired due to environmental emissions. 4/ Total excludes Lan Krabu

Planned Retirement SchedulePlant by Type


Table 13. Candidate Power Plants for the Study (2003 Prices)

3.3 Fuel Price Projections

Fuel price forecasts for this study have been developed in cooperation with EGATand the World Bank. In general, the Bank adopted EGAT’s assumptions for coal andlignite, but conducted an independent analysis to establish petroleum product prices.

One of the most critical determining factors for this study is the value of natural gasto be used in combined cycle gas turbines, since these are the most likely economicalternatives to NT2. The following discussion summarizes the methodology employedby the Bank in deriving natural gas prices. (Notwithstanding the uniquecharacteristics of gas markets, other petroleum products have been valued in a similarmanner.) A more comprehensive discussion of the analysis is presented in AppendixA3.

The economic value of natural gas has been calculated based on:

the cost of discovery, development and production for local supply,

border price for Myanmar supply,

removal of taxes and royalties from domestic production,

addition of the PTT marketing margin and

Capacity Capital Cost Life Heat Rate Fixed O&M Var. O&M FOR MaintenanceType MW US$/kW 1/ years Btu/kWh $/kW-yr $/MWh 2/ % weeks

Oil-fired Thermal 700 792 30 8,870 19.56 0.597 6.0% 6

Coal-fired Thermal 3/ 700 1,100 30 9,560 24.49 0.983 7.0% 6

Combined Cycle 4/ 700 510 25 7,050 18.00 7.000 4.5% 3

Gas Turbine 5/ 230 310 15 11,000 10.46 4.200 10.0% 2

South Bangkok 6/ 310 * 15 * * * 6.0% 6

Bang Pakong 6/ 550 * 15 * * * 6.0% 6

1/ Assumed expenditure profiles (%): year 0 year -1 year -2 year -3 year -4Thermal 19.0% 23.5% 34.5% 13.5% 9.5%Combined Cycle 23.0% 48.0% 29.0%Gas Turbine 41.6% 49.6% 8.8%

2/ Relatively higher VOM assumed for CCGT and GT, based on experience reported by IPP developers in the region.3/ VOM includes limestone for FGD4/ 2GT multi-shaft assumed5/ Excluding land and land rights.6/ South Bangkok and Bang Pakong thermal units are candidates for reconditioning (life extension); this option only permitted in the year immediately following retirement: SBT3 - 2010, SBT4 - 2011, SBT5 - 2013, BKT1 - 2014. Asterisk (*) indicates costs and efficiencies are included in the model's database and used in the analysis, but not identified here for reasons of confidentiality.


the estimated LRMC of gas transmission on a postage stamp basis.

Although the World Bank does not have access to individual gas contracts, it isunderstood that the gas pricing structure, valid for the duration of the contract, isspecified in Thai Baht, incorporating an indexation formula which adjusts the priceover time according to the following factors:

the fob price of 3.5%S HFO Singapore,

a petroleum industry machinery inflation index reflecting USD inflation,

the Thai CPI reflecting Thai domestic inflation,

an exchange rate adjuster, and

a constant.

Given that our project numeraire is US dollars, the machinery index, the Thai CPIindex and the exchange rate adjuster are offsetting in future price projections (basedon purchasing power parity method of exchange rate projection). When working inUS$ prices, therefore, the only non-offsetting element of the index is the HFOadjuster, having a weight of about 30% in the total index.

In addition, PTT charges EGAT and IPPs a marketing margin of 1.75% of the salesprice, plus a postage-stamp pipeline toll.

Moving from the commercial value of natural gas to an economic value furtherrequires removal of all transfers – royalties and taxes – from the commercial price andthe substitution of the commercial pipeline tolls with estimated incremental variableoperating costs for pipeline transportation, insofar as the infrastructure is a sunk costfrom an economic perspective. Finally, resulting nominal economic natural gas valuesare converted into real values by deflating the nominal series by the MUV index.27

Base Case fuel price projections adopted for this study are summarized in Table 14.High and Low scenario fuel price projections are reported in Appendix A3.

It is possible that natural gas prices facing Thailand beyond 2014 could be higher thanthose projected up to 2014. Much depends on future demand, domestic discoveryvolumes and related costs and the longer-term costs of imported gas, the extent ofsuch cost escalation being extremely difficult to project. Long-term values have lowpresent value; nevertheless we have avoided projecting cost escalation over the verylong term in order to minimize the risk of over-stating NT2's comparative worth.

27 The MUV index is more formally identified as the United Nations’ Index of Unit Value ofManufactured Exports from the G-% industrial countries to developing country markets expressed inU.S. dollars.


Table 14. Base Case Fuel Price Forecasts

3.4 Thermal Candidate Plant Screening Analysis

The Study TOR requests a preliminary screening analysis based on real economiccosts in order to confirm the expectation that natural gas-fired units are the primaryalternatives to NT2.

The analysis has been prepared for the candidate generating units summarized inTable 13, assuming the fuel price forecasts from Table 14. Each candidate has beenevaluated at constant prices, using a real economic discount rate of 10 percent.

Table 15 shows the results of this analysis. The graph in the table plots the unit costof one kWh from each source as a function of the rate of capacity utilization.28

The table shows that gas turbines are the clear thermal choice for capacity utilizationbelow 25 percent (i.e., peaking duty). Gas-fired combined cycle appears to be theclear choice for higher capacity utilization. Even at very high capacity factors, the cost

28 Because plant capacities have already been adjusted for the effect of forced outages andmaintenance, each effective kW can be used up to 100 percent of the time.

Real Economic Prices - Base CaseFiscal Hvy Oil 3.5% Diesel Lignite Import CoalYear Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.55 2.55 2.55 3.39 6.10 1.21 1.54 2004 2.56 2.65 2.55 4.48 8.68 1.20 2.33 2005 2.51 2.60 2.49 4.06 7.88 1.19 2.22 2006 2.41 2.50 2.40 3.58 6.93 1.17 2.00 2007 2.37 2.46 2.36 3.43 6.65 1.15 1.77 2008 2.33 2.42 2.32 3.28 6.37 1.14 1.66 2009 2.31 2.41 2.30 3.26 6.33 1.12 1.54 2010 2.30 2.39 2.29 3.25 6.29 1.11 1.54 2011 2.29 2.38 2.28 3.23 6.26 1.10 1.55 2012 2.28 2.37 2.27 3.24 6.28 1.08 1.56 2013 2.27 2.37 2.27 3.25 6.30 1.06 1.57 2014 2.27 2.36 2.27 3.26 6.32 1.05 1.58

Average Annual Growth (%)2003-2014 -1.1% -0.7% -1.1% -0.4% 0.3% -1.3% 0.2%

Natural Gas - USD/mmbtu

Nominal Commercial Prices - Base Case

Fiscal Hvy Oil 3.5% Diesel Lignite Import CoalYear Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.95 2.95 2.95 3.56 8.54 1.21 1.56 2004 3.63 3.63 3.63 5.11 11.43 1.20 2.49 2005 3.48 3.48 3.48 4.57 10.46 1.20 2.34 2006 3.34 3.34 3.34 4.02 9.48 1.19 2.11 2007 3.32 3.30 3.32 3.89 9.25 1.19 1.89 2008 3.30 3.30 3.30 3.76 9.01 1.19 1.78 2009 3.32 3.34 3.32 3.77 9.02 1.18 1.67 2010 3.34 3.37 3.33 3.77 9.04 1.19 1.67 2011 3.36 3.38 3.34 3.78 9.05 1.19 1.69 2012 3.38 3.42 3.37 3.82 9.12 1.18 1.72 2013 3.40 3.46 3.39 3.86 9.20 1.18 1.74 2014 3.42 3.50 3.41 3.90 9.27 1.18 1.76

Average Annual Growth (%)2003-2014 1.4% 1.6% 1.3% 0.8% 0.8% -0.2% 1.1%



of combined cycle is at or below the cost of coal-fired units. Oil appears to be non-competitive at the real fuel prices adopted for the current study.

3.5 NT2 – The Alternative Expansion Candidate

Contractually, in the EGAT-NTPC power purchase agreement (PPA), NT2 is treatedas three separate transactions:

the first transaction is a firm power purchase of 4406 GWh per year(allocated to peak-period hours [6 a.m. to 10 p.m.] and according toexpected monthly generation) at the Primary Energy Tariff (“PE”) specifiedin the contract;

the second transaction is a purchase of 948 GWh annually during off-peakhours at the Secondary Energy 1 Tariff (“SE1”) specified in the contract;this transaction is treated as non-firm so that PROSCREEN does notrecord a further increment to installed capacity; and

a third transaction (not required, but at the option of EGAT) is a purchaseof an additional 282 GWh at the Secondary Energy 2 Tariff (“SE2”).


Table 15. Screening Analysis of EGAT Candidate Plants

OIL COAL COMB.CYC GTPlant Characteristics 700 MW 700 MW 700 MW 230 MW Oil Coal Gas

Life (years) 30 30 25 15 1 3.39 1.54 2.55 FOR (%) 6% 7% 4.5% 10% 2 4.48 2.33 2.56 Maintenance (wks) 6 6 3 2 3 4.06 2.22 2.51 Availability factor 0.83 0.82 0.90 0.87 4 3.58 2.00 2.41 Heat rate (Btu/kWh) 8,870 9,560 7,050 11,000 5 3.43 1.77 2.37

6 3.28 1.66 2.33 Cap.Cost ($/kW) 792 924 510 310 7 3.26 1.54 2.31 Expend.Profile (%) 8 3.25 1.54 2.30

-4 9.5% 9.5% 9 3.23 1.55 2.29 -3 13.5% 13.5% 10 3.24 1.56 2.28 -2 34.5% 34.5% 29.0% 6.8% 11 3.25 1.57 2.27 -1 23.5% 23.5% 48.0% 49.6% 12 3.26 1.58 2.27 0 19.0% 19.0% 23.0% 41.6% 13 3.26 1.58 2.26

Levelized Cap.Cost 104.39 121.79 65.35 44.62 14 3.26 1.58 3.65 Fixed O&M ($/kW-yr) 19.56 24.49 18.00 10.46 15 3.26 1.58 3.65 Variable O&M ($/kWh) 0.00060 0.00096 0.00700 0.00420 16 3.26 1.58 3.65 Levelized Fuel ($/kWh) 0.03083 0.01657 0.01883 0.03208 17 3.26 1.58 3.65 Fuel Price Sensitivity 1.00 1.00 1.00 1.00 18 3.26 1.58 3.65 Discount rate 10% 19 3.26 1.58 3.65

20 3.26 1.58 3.65 21 3.26 1.58 3.65 22 3.26 1.58 3.65 23 3.26 1.58 3.65 24 3.26 1.58 3.65 25 3.26 1.58 3.65 26 3.26 1.58 3.65 27 3.26 1.58 3.65 28 3.26 1.58 3.65 29 3.26 1.58 3.65 30 3.26 1.58 3.65

Economic Fuel Prices (Constant US$/mmbtu)

Levelized Cost of GenerationCandidate Units ($/kWh)

$0.00

$0.05

$0.10

$0.15

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percent Ulilization of Effective kW

US

$ p

er

kW

h

Oil Coal Combined Cycle Gas Turbine


For purposes of the current study, total planned generation is allocated by monthbased on a review of historical data (1953-99) provided by NTPC, as summarized inthe following chart:

For the economic [real resource] analysis presented in Chapter 5, Base Caseinvestment and operating costs of the NT2 project are based on real cash flow dataderived from the project lenders’ financial model, excluding transfers and sunk costs,but including incremental sponsor development costs that reflect use of real resources

For the commercial evaluation at nominal market prices presented in Chapter 6,negotiated PPA payments per kWh purchased are taken as the project cost ratherthan actual developer cash flows, since NT2 generation is being purchased at thatagreed price.

Costs for associated transmission in Thailand and Laos are also included in eachanalysis. Even when these costs are not borne by the project sponsor (as is the casewith associated transmission in Thailand), these investments represent real resourcecosts required to deliver NT2 energy from the powerhouse to end-users.

PE SE1 SE2Jan 370.4 62.2 18.5 Feb 331.0 46.2 13.7 Mar 362.1 44.0 13.1 Apr 349.8 30.0 8.9 May 361.8 77.7 23.1 Jun 355.9 114.7 34.1 Jul 386.4 147.2 43.8 Aug 391.2 107.1 31.9 Sep 382.6 98.5 29.3 Oct 389.2 88.6 26.4 Nov 363.4 70.0 20.8 Dec 362.2 61.8 18.4 Total 4,406.0 948.0 282.0

NT2 GWh by Month (1953-99)

Methodology for the Study 3 5

4 METHODOLOGY FOR THE STUDY

The primary focus of the current study is an economic analysis to determine whetherthe NT2 Project has a satisfactory economic cost-risk profile in the context of theregional power market. The main distinguishing characteristics of this second stageanalysis are threefold:

all values reflect real economic resource costs (to the greatest extentfeasible);

the scope of work includes both the Thai and Laotian electricity markets;and

the risk analysis consists of an integrated multi-event probabilisticframework that produces one overall quantitative result showing whetherimplementing the NT2 project in October 200929 would be an acceptableeconomic investment for the power sector.

Section 4.1 introduces the least-cost generation expansion planning methodologyadopted for this study. Section 4.2 describes the cost-risk framework used todetermine the Study outcome.

4.1 The Least Cost Planning Methodology

4.1.1 The PROSCREEN II ModelPROSCREEN II, the least-cost generation expansion planning model currently usedby EGAT, has been adopted for use in this study.30 This model is widely used byutilities throughout the world. Specifically, three modules within the model are used:(i) the Load Forecast Adjustment (LFA) module, (ii) the Generation and Fuels (GAF)module, and (iii) the PROVIEW module. These modules:

organize the necessary load data (annual/seasonal energy and peak load andload shape) which define capacity requirements to maintain a specified levelof system reliability;

29 Sensitivity analysis evaluated alternative start-dates, and concluded that Oct-09 (i.e., the beginning ofFY2010) is the least-cost.

30 Indeed, without the full support of EGAT generation planners, this study would not have beenpossible.


assemble the necessary data on unit operating characteristics, fuel costs, saleand purchase arrangements for evaluation of alternative generationresource plans, and calculate the production cost and reliability associatedwith these plans; and

determine the least-cost plan for meeting system demand under aprescribed set of constraints by simulating the operation of the utility todetermine the cost and reliability effects of alternative system resourceadditions.

EGAT conducts its least-cost generation expansion planning at current, financial prices,i.e., including annual inflation, and not adjusting market prices to economic prices byexcluding transfer payments (taxes, duties, and subsidies). This policy is consistentwith a gradual industry-wide trend away from traditional economic analysis as utilitiesmove toward privatization and away from government subsidies and preferentialtreatment. As noted in Chapter 1, however, this study is a regional evaluation ofexpansion options using real resource costs, and therefore cost assumptions divergefrom values currently assumed for EGAT planning.31

For the interested reader, a more complete explanation of how PROSCREEN works ispresented in Appendix A5.

4.1.2 How PROSCREEN is Applied in this StudyTo summarize, we have adopted the following assumptions for PROSCREEN least-cost expansion planning runs in the current study:

All plants defined as “committed” (Table 11) are “fixed” in the plan atnegotiated cost/timing. These units are considered as part of the system;they are not “selected” as least cost by the model.

Non-thermal resources are dispatched without regard to cost:

Hydro capacity, according to an exogenously determined level ofmonthly dependable generation;

Lao imports from Theun Hinboun and Huay Ho plants;

SPP contracts (and commitments), assuming a capacity factor of 80percent.

31 The World Bank has outlined detailed requirements in the TOR (see Appendix A1) regardingmodeling approach, and specified a large number of input assumptions. Further, the Bank recognizesthe unique perspective of a study based on real regional resource costs, and acknowledges that themethods and values used in this study for its purposes are completely without prejudice to differentones that EGAT may consider as more appropriate for its own operating context and requirements.


With the exception of EGAT’s own hydro capacity, each of these resourcesis modeled as a separate transaction, defined from contractual purchaseprice and operating constraints.

NT2 is treated as two transactions ("PE" and "SE1"; see Section 3.5) withan October 2009 starting date (FY2010) when it is included in the analysis.

Thermal resources, including both EGAT’s existing thermal capacity andavailable IPP capacity, are economically dispatched based on cost. IPPs arenot required to run, but in general are dispatched, since they are relativelylow-cost gas-fired units.32

Implicit in this modeling approach is the assumption (based on recentstudies) that the Lao alternative to NT2 for meeting that portion of itsdemand in the CR-2 region would be import of thermal-fired electricityfrom Thailand.33

4.2 Cost-Risk Analysis Modeling Framework

As specified in the TOR, the study outcome is to be determined by means of theresults profile shown in Table 16 (the “Cost-Risk Framework”). This profile providesfor calculating the probability-weighted present value (PV) costs of eitherimplementing or not implementing NT2 for commercial operation in FY2010, giventhe interplay of several major uncertain factors – project cost, long-term demand forelectricity, and long-term economic value of natural gas as well as the suggestedprobabilities of occurrence for Base Case, Low and High estimates of these variables.The difference between the probability-weighted PV cost of implementing the projectin FY2010 versus not implementing it at all is the decision criteria for this analysis. Alower net present value (NPV) “with NT2” indicates that the project is an acceptableeconomic investment for the regional power market.

In addition to the real resource cost analysis outlined above, the study also includes acommercial assessment of the project under which the economic values are convertedto commercial values and expressed in nominal US dollars, in order to assess thecommercial sustainability of NT2 in the regional power market. This effort parallelsthe analytical framework shown in Table 16, although construction cost is notincluded as a cost-risk variable for the commercial evaluation because a powerpurchase agreement has already been negotiated and signed.34

32 Thermal capacity at Krabi is dispatched without regard to cost, as transmission constraintsnecessitate its use for reliability in the South.

33 Power System Development Plan for Lao PDR – Final Report, Maunsell Limited in association withLahmeyer GmbH, August 2004. The study offers a strategic plan for the power sector for the period2005-2020.

34 Moreover, fixed-price construction contracts including contingencies have already been negotiated,and developer costs incpororate premiums for risk (see Section 5.1.3).


The specific steps undertaken to complete the cost-risk analysis are summarized in thefollowing paragraphs:

Table 16. The Cost-Risk Framework

Determine Base Case, Low, and High real economic values for the three keyuncertainties – (i) project cost, (ii) growth rate of electricity demand, and(iii) the economic value of natural gas – expected to have the mostsignificant potential impact on the economic decision to develop NT2.

Define a probability of occurrence for each state (Base Case, Low, andHigh) of each variable. In fact, these probabilities are specified in theproject TOR, and shown in Table 16. It should be noted that theprobabilities were selected based on judgment – backed by World Bank

A. Present Values WITH NT2:

Case Probability Case Probability Case Probability Case Present Value Probabilityh 0.25 h 0.25 h 0.25 hhh <Scenario PV> 0.01563 h 0.25 h 0.25 m 0.50 hhm <Scenario PV> 0.03125 h 0.25 h 0.25 l 0.25 hhl <Scenario PV> 0.01563 h 0.25 m 0.50 h 0.25 hmh <Scenario PV> 0.03125 h 0.25 m 0.50 m 0.50 hmm <Scenario PV> 0.06250 h 0.25 m 0.50 l 0.25 hml <Scenario PV> 0.03125 h 0.25 l 0.25 h 0.25 hlh <Scenario PV> 0.01563 h 0.25 l 0.25 m 0.50 hlm <Scenario PV> 0.03125 h 0.25 l 0.25 l 0.25 hll <Scenario PV> 0.01563 m 0.50 h 0.25 h 0.25 mhh <Scenario PV> 0.03125 m 0.50 h 0.25 m 0.50 mhm <Scenario PV> 0.06250 m 0.50 h 0.25 l 0.25 mhl <Scenario PV> 0.03125 m 0.50 m 0.50 h 0.25 mmh <Scenario PV> 0.06250 m 0.50 m 0.50 m 0.50 mmm <Scenario PV> 0.12500 m 0.50 m 0.50 l 0.25 mml <Scenario PV> 0.06250 m 0.50 l 0.25 h 0.25 mlh <Scenario PV> 0.03125 m 0.50 l 0.25 m 0.50 mlm <Scenario PV> 0.06250 m 0.50 l 0.25 l 0.25 mll <Scenario PV> 0.03125 l 0.25 h 0.25 h 0.25 lhh <Scenario PV> 0.01563 l 0.25 h 0.25 m 0.50 lhm <Scenario PV> 0.03125 l 0.25 h 0.25 l 0.25 lhl <Scenario PV> 0.01563 l 0.25 m 0.50 h 0.25 lmh <Scenario PV> 0.03125 l 0.25 m 0.50 m 0.50 lmm <Scenario PV> 0.06250 l 0.25 m 0.50 l 0.25 lml <Scenario PV> 0.03125 l 0.25 l 0.25 h 0.25 llh <Scenario PV> 0.01563 l 0.25 l 0.25 m 0.50 llm <Scenario PV> 0.03125 l 0.25 l 0.25 l 0.25 lll <Scenario PV> 0.01563

A. Probability-weighted Present Value WITH NT2 #VALUE! 1.00000


Case Probability Case Probability Case Present Value Probabilityh 0.25 h 0.25 hh <Scenario PV> 0.06250 h 0.25 m 0.50 hm <Scenario PV> 0.12500 h 0.25 l 0.25 hl <Scenario PV> 0.06250 m 0.50 h 0.25 mh <Scenario PV> 0.12500 m 0.50 m 0.50 mm <Scenario PV> 0.25000 m 0.50 l 0.25 ml <Scenario PV> 0.12500 l 0.25 h 0.25 lh <Scenario PV> 0.06250 l 0.25 m 0.50 lm <Scenario PV> 0.12500 l 0.25 l 0.25 ll <Scenario PV> 0.06250

B. Probability-weighted Present Value WITHOUT NT2 #VALUE! 1.00000

Probability-weighted PV Savings (Cost) WITH NT2 #VALUE! (Result A minus Result B; 2003 USD million)





studies from other projects – about relationship between extent ofvariance and its probability of occurrence, as well as the presumption thatthe base case should have a higher probability of occurrence while Highand Low values should have high-enough probabilities so that they have ameasurable impact on cost-risk analysis results.

Run the PROSCREEN expansion planning model under Economic BaseCase assumptions with NT2 as a candidate competing for a place in the least-cost expansion plan from its earliest expected commercial operation date ofFY2010. This initial analysis added NT2 to the system in October 2009,i.e., it specified that the least-cost expansion plan included NT2commencing operation in October 2009. This date was therefore fixed forall subsequent "with NT2" model runs to conform to the logic of thedecision matrix (the decision being whether to develop NT2 for commercialoperation in October 2009 or not to do so).35

Run the PROSCREEN expansion planning model with NT2 commencingcommercial operation in October 2009 (FY2010) for all combinations of theabove-defined uncertainties. The PROSCREEN “objective function” (i.e.,basis for comparison of results) is the present value of future investmentand operating costs over the Study Period. The expansion plan with thelowest NPV is the preferred alternative.

Re-run each of the defined scenarios without NT2 so that demand must beserved from alternative resources.

Calculate the probability-weighted present value of costs for the “withNT2” and “without NT2” scenario groups.

Subtract the probability-weighted result “with NT2” from the result“without NT2” to determine the Study outcome.

Repeat the above analysis, converting all real economic values in the least-cost planning runs to nominal commercial values (i.e., using market pricesincluding inflation). Whereas the economic assessment defines the projectcost as the real resources utilized in constructing and operating NT2, thecommercial assessment defines the project cost according to the commercialterms set forth in the power purchase agreement

To complete the Cost-Risk Framework, a total of 18 scenario runs are required (9“with NT2” and 9 “without NT2”), or 36 model runs to complete the frameworkfrom both the economic and commercial perspectives. These scenarios are formedfrom combinations of two planning variables – power demand and natural gas price.Three cases– Base, Low, and High – are used for each of these variables. The 9scenarios run with NT2 are expanded to 27 scenarios in the economic assessment bycombining manually the three cases for the construction cost of NT2 with the results

35 The sensitivity of results to a delay in commercial operation date was also evaluated, as reported inChapter 5.


of the other scenarios. (High and low project cost is not evaluated in the commercialruns because the commercial arrangement is a fixed-price PPA.)

For each scenario, the combined probability is simply the product of the probabilitiesof each of its components. For example, the probability of the “with NT2” Base Caseor “mmm” scenario (i.e., “medium” values for each possible outcome) is equal to 0.125(0.50 x 0.50 x 0.50), and the probability of the “without NT2” Base Case ("mm"scenario) is 0.25 (0.50 x 0.50). Similarly, the probability of the “with NT2” scenarioassuming all “high” outcomes (“hhh”) is 0.015625 (0.25 x 0.25 x 0.25). When allscenarios are considered, of course, the probabilities for the "with NT2" and "withoutNT2" scenario groups each sum to 1.00.

A complete cost-risk analysis – requiring 18 PROSCREEN model runs by EGATsystem planners – was prepared for the RELC/2004 study. Although the World Bankwished to update that economic analysis to incorporate current information (i.e.,current perspectives on Thai fuel prices and the most recent data on NT2 capitalcost) and to conduct a parallel commercial analysis of equivalent scope, it wasconsidered unnecessary (and unreasonable!) to request twice the original support(i.e., 36 model runs, each requiring considerable set-up and run time) from the EGATSystem Planning Division.


Chapters 5 and 6, which present these economic and commercial analyses, explain thespecific Base Case, Low, and High values adopted for each variable in the cost-riskanalyses.

Economic Evaluation 4 1

5 ECONOMIC EVALUATION

The objective of this chapter is to evaluate whether NT2 is a part of the least-costgeneration expansion plan for meeting future regional electricity needs when it isevaluated using the real economic cost of the resources required. The cost-riskanalytical framework outlined in Chapter 4 is applied to give a comprehensive,probabilistic answer to this question which systematically incorporates the range ofuncertainties – construction costs, load growth, fuel prices – assumed in this study toface the regional electricity sector in the coming years.

Section 5.1 summarizes the basic assumptions adopted for system expansion planning.Section 5.2 presents Base Case results. Section 5.3 reports the results of the cost-riskanalysis. Section 5.4 discusses the sensitivity of results to changes in specific variables.

5.1 Economic Planning Assumptions

5.1.1 Basic Economic AssumptionsThe World Bank has specified the following economic basis for the real resourceanalysis of NT2:

All costs exclude internal fiscal transfers (e.g. taxes, duties, and subsidies)

All values are expressed in constant US dollars of 200336

The discount rate is 10% real

The MUV index (a UN index of the unit value of manufactured exportsfrom G-5 industrial countries to developing country markets, expressed inUS dollars) is used as the price deflator to restate future year prices in real2003 US dollars; the MUV index averages 0.7 percent per annum through2015.

A fixed exchange rate of 40 Thai Baht per US dollar was used for planningpurposes.

36 RELC/2004 was conducted at 2003 prices. Given low inflation expectations, it was decided not torestate all PROSCREEN assumptions to 2004 prices; this adjustment would require substantialadditional work for no difference of consequence in the results.


5.1.2 System CharacteristicsIn general, system characteristics adopted for the current analysis follow EGAT’sPower Development Plan for 2003 (PDP2003) as published in April 2003.Characteristics common to both the Economic and Commercial runs ofPROSCREEEN, as detailed in Chapter 4, are summarized below:

The Base Case load forecast is Thailand’s official Base Case of August 2002(see Chapter 3), augmented by a Lao PDR domestic load of 75 MW and300 GWh.

The reliability criterion is a reserve margin of 15 percent, EGAT’s currentreserve criterion to assure system reliability.




NT2 (995 MW) is added to the system in October 2009 (FY2010) in the“with NT2” scenarios.37

All other plants – including plants proposed for reconditioning and allgeneric expansion options (see Table 13) – are modeled as candidateswhich much compete for a place in the least cost economic plan. (Notethat candidates for “reconditioning” – South Bangkok thermal (units 3-5)and Bang Pakong (unit 1) – are only permitted to enter the expansion planin the year following scheduled retirement.)


All non-thermal generation – notably domestic hydro plants and Laoimports – is dispatched first, without regard to cost. With theexception of EGAT’s own hydro capacity, each of these resources ismodeled as a separate transaction, defined from contractualpurchase price and operating constraints.

NT2 energy is dispatched in two parts according to the monthlyvariation reported previously in Chapter 3, one to provide peak-period energy and a second to provide off-peak energy. Optionaloff-peak generation is not assumed.

37 Project-associated transmission works in Laos are included in the project cost. Project-associatedincremental transmission costs for Thailand do not presume any other future hydro exports fromLaos to Thailand, due to the uncertainty of these exports.


All thermal generation – the majority of the entire system – is subjectto economic dispatch, and run only when it is lowest cost.Exceptions are small power producers (SPPs), which are assumed torun at an 80 percent capacity factor.38

The cost of NT2 is evaluated differently in the Economic and Commercial analyses.The following section discusses the NT2 cost assumptions for the economic projectassessment.

5.1.3 NT2 Planning Assumptions for the Economic AnalysisAs already noted, the Base Case economic analysis has been run in two modes – “withNT2” included in the expansion plan for commercial operation from October 2009(FY2010), and “without NT2” in the plan.39

Base Case economic investment and operating costs of the NT2 project are based onreal cash flow data derived from the lenders' financial model [version of December2004], excluding transfers and sunk costs, but including incremental sponsordevelopment costs that reflect use of real resources.40

The total capital cost of NT2 will be US$870 million, equivalent to a present value ofUS$600 million at 2003 prices. Associated transmission (including lines andsubstations, but excluding sunk costs) has a capital cost of US$135 million, equivalentto a present value of US$82 million. Table 17 summarizes the investment coststreams.

Low and High estimates of construction costs for NT2 and associated transmissionhave been specified in the TOR to be ±30% of the expected construction cost usedfor the Base Case. These costs are reported at the bottom of Table 17.

Operating costs for NT2 have likewise been derived from the project lenders’ financialmodel. The real annual cost of O&M is estimated as US$16.28 million per year.

Both the investment and operating costs include substantial environmental and socialcosts to be borne by the project sponsors by agreement with GOL.

38 This is a reasonable assumption given the high percentage of this output which is fossil fueled(predominantly by gas).

39 As discussed in Section 4.2 above, the starting date was fixed based on a PROSCREEN run in whichNT2, treated as a candidate, was added to the least cost plan in October 2009. FY2010 (Oct-09) isconsidered to be the earliest possible commercial operation date (COD); Section 5.3 reports thesensitivity of results to delayed starting dates.

40 For a commercial evaluation at market prices, negotiated PPA payments per kWh purchased aretaken as the project cost rather than actual developer cash flows, since NT2 generation is beingpurchased at that agreed price. This valuation is also used for the commercial project assessmentreported in the next chapter.


Table 17. Capital Costs of NT2 (constant US$2003, 10% discount rate)

The TOR requests that the Consultant determine whether there is any “systematicbias” in the estimated construction costs for NT2 (i.e., whether the Base Caseestimated project cost reported here can be assumed to be the expected projectcost). There is evidence that the Base Case project cost estimate is not systematicallybiased either positively or negatively:

As with planning for any large hydropower project, NT2 developer planninghas included comprehensive activity scheduling to assure efficient projectdevelopment at least cost. Moreover, NT2 project developers have reliedon fixed-price bidding for key civil and electro-mechanical contracts. Facedwith fixed prices, contract bidders necessarily undertake an evaluation ofthe risks they are undertaking. Further, these fixed-price contracts includeboth physical and price contingencies, further protecting the developeragainst a wide range of unforeseen cost overruns.

NT2 project developers have also employed sophisticated risk models totrace the linkages from randomly selected project activity delays, and theircumulative impact on the critical path to final project completion. In otherwords, complex models have been utilized to ascertain if randomly selecteddelays might cause subsequent delays that could not be mitigated so as toachieve targeted project deadlines. The Base Case project cost estimateincludes a quantified estimate of the risk premium associated with suchunanticipated delays. Thus, there is a risk “insurance” against unexpectedcost overruns already incorporated into the Base Case cost estimatesreported in Table 17.

Discount TotalFiscal Factor @ Cost PV of Cost Cost PV of Cost PV of CostYear 10% USD million USD million USD million USD million USD million2003 0.9535 2004 0.8668 73.0 63.28 1.4 1.2 2005 0.7880 161.0 126.9 6.3 5.0 2006 0.7164 206.5 147.9 6.1 4.4 2007 0.6512 208.7 135.9 28.8 18.8 2008 0.5920 126.8 75.1 69.2 41.0 2009 0.5382 94.5 50.8 15.6 8.4 2010 0.4893 - - 7.4 3.6

Base Case 870.4 599.9 135.0 82.4 682.3

High Case 130% 1,131.5 779.8 175.5 107.1 886.9 - increase 261.1 180.0 40.5 24.7 204.7 Low Case 70% 609.3 419.9 94.5 57.7 477.6 - decrease 261.1 180.0 40.5 24.7 204.7

NT2 Associated Transmission


5.2 Base Case Results

Table 18 summarizes the results of the Base Case scenario “with NT2” included inthe expansion plan from FY2010. (A detailed summary of these results is presented inAppendix A6.)

A total of 15,706 MW are added to the system during the planning period. NT2, ofcourse, accounts for 995 MW of new capacity, about 6 percent of the total. Afurther 4,792 MW represent capacity that is already committed (i.e., not competingfor a place in the plan). All of the candidates selected to meet future load are gas-fired. Recommended additions include 10,500 MW of combined cycle capacity and690 MW of gas turbine capacity. Reconditioned thermal plants account for a further1,480 MW.

The lower panel of Table 18 shows the present value (PV) of this expansion program.The PV of total cost over the planning horizon is US$26,628 million. AfterPROSCREEN calculates the end-effects of this expansion program in order to avoidany biases which might result from a short planning horizon, the estimated total PV ofcosts over the Study Period is US$46,603 million.

Table 18. Base Case “with NT2”

Table 19 presents results of an expansion planning model run identical to the onespecified for Table 18 except that NT2 is not included. The table shows therecommended expansion plan in the absence of the 995 MW from NT2. This caserequires a total of 11,200 MW of combined cycle plant over the Planning Period, with1,150 MW of gas turbine plant and the same reconditioning – a net increase of 1,160MW.

Fiscal Installed ReserveYear MW Addition Retirement CC GT Recondition Import Margin2003 23,830 37.4%2004 24,715 886 33.5%2005 24,775 60 25.5%2006 24,604 20 (191) 16.9%2007 25,996 1,727 (335) 15.9%2008 27,723 1,400 (373) 700 16.0%2009 29,451 700 (373) 1,400 15.1%2010 31,376 (310) 700 230 310 995 15.1%2011 33,236 (310) 1,400 460 310 15.1%2012 35,336 2,100 15.5%2013 37,436 (310) 2,100 310 15.4%2014 39,536 (550) 2,100 550 15.1%

Total 39,536 4,792 (2,752) 10,500 690 1,480 995

Notes: CC - gas-fired combined cycle, GT - gas turbine.

PRESENT VALUE OF COSTS(US$ million) With NT2 A. Planning Period (2003-2014) 26,628 B. End-Effects Period 19,976 C. Study Period (A + B) 46,603

Committed Plant Planned Additions (including NT2)


Table 19. Base Case “without NT2”

The middle panel of Table 19 compares the PV of total costs required for each of theBase Case generation expansion plans, both “with” and “without” NT2. Assumingthat all assumptions adopted for the Base Case analysis prove correct, the estimated

Fiscal Installed ReserveYear MW Addition Retirement CC GT Recondition Import Margin (%)2003 23,830 37.4%2004 24,715 886 33.5%2005 24,775 60 25.5%2006 24,604 20 (191) 16.9%2007 25,996 1,727 (335) 15.9%2008 27,723 1,400 (373) 700 16.0%2009 29,451 700 (373) 1,400 15.1%2010 31,551 (310) 2,100 310 15.7%2011 33,411 (310) 1,400 460 310 15.7%2012 35,271 1,400 460 15.3%2013 37,371 (310) 2,100 310 15.2%2014 39,701 (550) 2,100 230 550 15.6%

Total 39,701 4,792 (2,752) 11,200 1,150 1,480 -


PRESENT VALUE OF COSTS(US$ million) With NT2 Without NT2 A. Planning Period (2003-2014) 26,628 26,724 B. End-Effects Period 19,976 20,145 C. Study Period (A + B) 46,603 46,869

PV of Savings with NT2 A. Planning Period (2003-2014) 97 B. End-Effects Period 169 C. Study Period (A + B) 266 % of total cost 0.57%

Planned Additions (excluding NT2)Committed Plant

Savings (Cost) Due to Selecting Nam Theun 2Difference in Accumulated Present Value (US$ million)

-40

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with NT2 without NT2


PV of total costs over the Study Period is US$46,603 million when NT2 is included inthe plan, and US$46,869 million when NT2 is excluded.

The graph at the bottom of Table 19 charts the annual cumulative benefits associatedwith the decision to proceed with NT2. Each point on the “without NT2” linerepresents the annual accumulated difference in costs over the “with NT2” case. (Apositive difference indicates a real resource savings associated with developing NT2,while negative numbers would indicate a real resource cost.) The chart suggests thatthe decision to purchase NT2 power will produce a significant savings over the studyhorizon. The accumulated present value of savings to the region over the entireStudy Period totals US$266 million at 2003 prices.41 While small in relation to thecost of the entire expansion plan, these savings are equivalent to almost 40 percent ofthe total economic cost of NT2 development.

5.3 Cost-Risk Analysis

The Base Case tells us that NT2 should be included in the region’s least costgeneration expansion plan assuming that the assumptions adopted for decision-making are correct. The objective of cost-risk analysis is to determine whether thesame decision is justified given the high probability that future events will diverge fromthe Base Case assumptions.

As specified by the World Bank, the study outcome is determined by means of theresults profile shown in Table 1 (the “Cost-Risk Framework”). This profile providesfor calculating the probability-weighted present value (PV) costs of eitherimplementing or not implementing NT2 for commercial operation in FY2010, giventhe interplay of several major uncertain factors – project cost, long-term demand forelectricity, and long-term economic value of natural gas as well as the suggestedprobabilities of occurrence for Base Case, Lower and Higher estimates of thesevariables. The difference between the probability weighted PV cost of implementingthe project in FY2010 versus not implementing it at all is the decision criteria for thisanalysis. A lower net present value (NPV) “with NT2” would indicate that theproject is an acceptable economic investment for the regional power market.

The key decision variables for this study are defined in the study TOR (see AppendixA1). They are:

Capital cost of NT2. The World Bank has specified a cost range of +30percent (High capital cost) and –30 percent (Low capital cost); thesevalues are reported in Table 17.

Regional demand forecast. The World Bank has specified a very wide range inorder to reflect accumulated international experience with load forecast

41 The US$ 266 million represents a ‘savings” since the least-cost plan without NT2 would come atgreater total cost.


accuracy over time; the regional High and Low demand forecasts aresummarized in Table 10.

Natural gas price forecast.42 The World Bank has developed its own fuel priceprojections, with particular emphasis on the price of natural gas since it isthe most competitive alternative fuel. The Base Case projections arepresented in Table 15; High and Low scenarios are reported in AppendixA3.43

For each of these three key variables, the TOR specifies base case, low case and highcase assumptions, as well as the probabilities of occurrence associated with each. Basecase assumption values are assigned a 50 percent probability of occurrence, while theLow and High case assumption values are assigned probabilities of 25 percent each.

Based on these assumptions, a total of 27 possible scenarios are required to representall probable outcomes “with NT2”, and 9 possible scenarios to represent all possibleoutcomes “without NT2”.

A complete cost-risk analysis – requiring 18 PROSCREEN model runs by EGATsystem planners – was prepared for the RELC/2004 study. Although the World Bankwished to update that economic analysis to incorporate current information (i.e.,current perspectives on Thai fuel prices and the most recent data on NT2 capitalcost) and to conduct a parallel commercial analysis of equivalent scope, it wasconsidered unnecessary (and unreasonable!) to request twice the original support(i.e., 36 model runs, each requiring two or more hours of set-up and run time) fromthe EGAT System Planning Division.


Section 5.3.1 reports the impact of these individual variables on the least-costexpansion plan. Section 5.3.2 then presents their collective impact in the resultingcost-risk analysis.

42 Since natural gas is the primary fuel alternative to NT2, this report uses the terms "natural gasprice forecast" and "fuel price forecast" interchangeably; readers should be reminded that either termrefers to the complete sets of fossil fuel forecasts (Base Case, High, and Low) presented in AppendixA3.

43 The high and low variance is based one standard deviation around the WB's oil price forecast forthat portion of the gas value determined by movement of international oil prices.


5.3.1 Sensitivity AnalysisThis section reports the sensitivity of the Base Case results to changes in the values ofindividual variables. As noted above, these sensitivities involve variables that can beexpected to delineate the downside risk to the project:

Sensitivity to a lower demand forecast

Sensitivity to a lower forecast for natural gas and other fuels

Sensitivity to changes is NT2 capital cost

Sensitivity to a Lower Demand Forecast

The spread between the base and low demand forecasts adopted for this study isdramatic: By FY2012, the Low Case is only 75 percent of the Base Case. Notsurprisingly, system expansion requirements are reduced as a result. Table 20compares the expansion plans required under the two load forecasts.

The table suggests that savings "with NT2" would be substantially reduced withlower-than-expected demand (US$24 million vs. US$266 in the Base Case). Thisresult follows from the fact that new gas-fired generation is not required in the “withNT2” case, and not until FY2014 in the “without NT2” case. With lower demand, anon-NT2 scenario allows for slower accumulation of generation capacity than ascenario in which NT2 is committed for FY2009 regardless of the demand level.

Sensitivity to Lower Natural Gas Prices

Differences between high and low fuel price forecasts adopted for the study are notas dramatic as the spread noted for the demand forecast. This result is due to thefact that the value of natural gas in the Thai power market is only partially influencedby the oil price range. (The prices adopted for these sensitivity scenarios are reportedin Appendix A3.) When scenarios are run with low fuel prices, gas remains the fuel ofchoice for incremental capacity both “with NT2” and "without NT2".

As might be expected, the low gas price scenario results in lower total Study Periodsavings (US$226 million) than in the Base Case scenario (US$266 million). Thedifference can be attributed entirely to reduced gas prices, since capacity additionsmirror the Base Case in both “with NT2” and “without NT2” cases.

Table 21 compares the Base Case results with the expected savings from NT2assuming lower fuel prices.


Table 20. Sensitivity of Results to Lower Demand

Fiscal InstalledYear MW CC GT Recondition Import2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,023 2009 27,351 2010 28,346 310 995 2011 28,346 310 2012 28,346 2013 28,346 310 2014 28,346 550

Total 28,359 - - 1,480 995

Fiscal InstalledYear MW CC GT Recondition Import2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,023 2009 27,351 2010 27,351 310 2011 27,351 310 2012 27,351 2013 27,351 310 2014 28,281 700 230 550

Total 28,281 700 230 1,480 -



PV of Savings with NT2 A. Planning Period (2003-2014) (76) B. End-Effects Period 100 C. Study Period (A + B) 24 % of total cost 0.07%

LOW DEMAND SCENARIO

Low Demand

Planned Additions (excluding NT2)

Planned Additions (including NT2)


-80

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with NT2 Economic Base Case Low Demand


Table 21. Sensitivity of Results to the Price of Natural Gas

Fiscal InstalledYear MW CC GT Recondition Import2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,723 700 2009 29,451 1,400 2010 31,376 700 230 310 995 2011 33,236 1,400 460 310 2012 35,336 2,100 2013 37,436 2,100 310 2014 39,536 2,100 550

Total 39,536 10,500 690 1,480 995

Fiscal InstalledYear MW CC GT Recondition Import2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,723 700 2009 29,451 1,400 2010 31,551 2,100 310 2011 33,411 1,400 460 310 2012 35,271 1,400 460 2013 37,371 2,100 310 2014 39,701 2,100 230 550

Total 39,701 11,200 1,150 1,480 -




Low Gas Price



LOW GAS PRICE SCENARIO


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with NT2 Economic Base Case Low Gas Price


Sensitivity to Changes in NT2 Capital Cost

Sensitivity analyses reflecting changes in the load forecast and in fuel prices requirecompletely new runs of the PROSCREEN model for both the “with NT2” and“without NT2” cases, since modifying these parameters will impact the entire systemexpansion plan.

Changes in the capital cost of NT2, however, only affect the cost of a single plant, soreliable estimates of the resulting impact on the least-cost system expansion plan canbe prepared by simply adjusting the present value cost of the Base Case “with NT2”by the present value of the change in NT2 capital cost implied by the High and Lowcapital cost scenarios. (The required adjustments are summarized in Table 17.)

Table 22 compares the Base Case results with the expected savings from NT2assuming higher and lower capital costs for NT2. Not surprisingly, the decrease(increase) in savings produced by a 30 percent increase (decrease) in cost is dramatic.Even under the high capital cost assumption, however, NT2 produces a real netbenefit to the regional economy (US$61 million). These higher costs, coupled witheither low demand or low gas prices, would eliminate this real net benefit.

Table 22. Sensitivity to Changes in NT2 Capital Cost

5.3.2 Cost-Risk Analysis ResultsThe results of the economic cost-risk analysis are summarized in Table 23. Aspreviously noted, the framework is incomplete, since High demand and High gas pricescenarios have not been prepared. The review of downside risks represents only 56percent of a complete cost-risk assessment. However, it must be noted that thescenarios excluded would be expected to record greater net benefits “with NT2” thanthe reported cases. For example, either higher demand or higher fuel costs wouldprovide greater net benefits than the Base Case.44

44 This conclusion is both logical and confirmed by the results for these cases in RELC/2004.

PRESENT VALUE OF COSTS Without NT2(US$ million) BASE CASE LOW HIGH A. Planning Period (2003-2014) 26,628 26,628 26,628 26,724 B. End-Effects Period 19,976 19,771 20,181 20,145 C. Study Period (A + B) 46,603 46,399 46,808 46,869

PV of Savings with NT2 A. Planning Period (2003-2014) 97 97 97 B. End-Effects Period 169 374 (36) C. Study Period (A + B) 266 471 61 % of total cost 0.57% 1.01% 0.13%

Note: NT2 capital cost adjustments for the high and low cases has been allocated entirelyto the End-Effects Period; PROSCREEN would allocate these adjustments to thePlanning Period as well.

With NT2


Table 23. Economic Cost Risk Analysis Results

Taking all evaluated potential outcomes into account, a system expansion planfeaturing the commissioning of NT2 in October 2009 is the correct decision from aneconomic least-cost perspective. Even when only downside risks are evaluated, theprobability-weighted PV of total savings over the entire Study Period is estimated tobe US$162 million, equivalent to US$0.006 per kWh sold from the NT2 project.

A review of the cost-risk matrix indicates that NT2 capital cost is the variable havingthe greatest impact on results. High capital costs decrease the savings by US$205million when other variables are held constant (i.e., from US$266 to US$ 61 million),while Low capital costs increase savings by US$205 million.

Low demand reduces savings by substantially, to US$24 million. Despite the symmetryof input assumptions, results for a High demand case would not be symmetrical


Case Probability Case Probability Case Probability Case Present Value Probability Scenarioh 0.25 h 0.25 h 0.25 hhh - - h 0.25 h 0.25 m 0.50 hhm - - h 0.25 h 0.25 l 0.25 hhl - - h 0.25 m 0.50 h 0.25 hmh - - h 0.25 m 0.50 m 0.50 hmm 46,808 0.06250 61 h 0.25 m 0.50 l 0.25 hml 43,741 0.03125 (6) h 0.25 l 0.25 h 0.25 hlh - - h 0.25 l 0.25 m 0.50 hlm 34,548 0.03125 (181) h 0.25 l 0.25 l 0.25 hll 32,214 0.01563 (259) m 0.50 h 0.25 h 0.25 mhh - - m 0.50 h 0.25 m 0.50 mhm - - m 0.50 h 0.25 l 0.25 mhl - - m 0.50 m 0.50 h 0.25 mmh - - m 0.50 m 0.50 m 0.50 mmm 46,603 0.12500 266 m 0.50 m 0.50 l 0.25 mml 43,536 0.06250 199 m 0.50 l 0.25 h 0.25 mlh - - m 0.50 l 0.25 m 0.50 mlm 34,343 0.06250 24 m 0.50 l 0.25 l 0.25 mll 32,009 0.03125 (54) l 0.25 h 0.25 h 0.25 lhh - - l 0.25 h 0.25 m 0.50 lhm - - l 0.25 h 0.25 l 0.25 lhl - - l 0.25 m 0.50 h 0.25 lmh - - l 0.25 m 0.50 m 0.50 lmm 46,399 0.06250 471 l 0.25 m 0.50 l 0.25 lml 43,331 0.03125 404 l 0.25 l 0.25 h 0.25 llh - - l 0.25 l 0.25 m 0.50 llm 34,138 0.03125 228 l 0.25 l 0.25 l 0.25 lll 31,804 0.01563 151



Case Probability Case Probability Case Present Value Probabilityh 0.25 h 0.25 hh - h 0.25 m 0.50 hm - h 0.25 l 0.25 hl - m 0.50 h 0.25 mh - m 0.50 m 0.50 mm 46,869 0.25000 m 0.50 l 0.25 ml 43,735 0.12500 l 0.25 h 0.25 lh - l 0.25 m 0.50 lm 34,367 0.12500 l 0.25 l 0.25 ll 31,955 0.06250







around the Base Case. Since NT2 is fully utilized in the Base Case, there is limitedopportunity for increased benefits due to an increase in system load.

A Low natural gas price reduces total savings by US$67 million, although the netbenefit “with NT2” is still significant (US$199 million).

Only combinations of adverse future conditions from the perspective of NT2 (highcapital costs, low demand and/or low gas prices) produce unfavorable results.Collectively, these events have a relatively low probability of occurrence.

Reaching a conclusion based on an incomplete cost-risk results matrix may be a causefor concern given even a low probability of negative outcomes. That concern ismitigated in the case of this analysis by the fact that the omitted scenarios containassumptions that favor the NT2 project. Nevertheless, for sake of completeness, wehave completed the entire cost-risk framework based on the very conservativeassumption that every “High” demand or gas price scenario will achieve savingsidentical to its closest “Medium” counterpart scenario (e.g., the “High demand, Highgas price” scenario is assigned the savings of the “Medium demand, Medium gas price”scenario) even though we know, both intuitively and from our modeling forRELC/2004, that these scenarios would be expected to produce additional savings.

This approach is mathematically equivalent to assigning a 75 percent probability tothe “Medium” results and a “zero” percent probability to future events would proveadvantageous to NT2 (i.e., construction cost at the low cost estimate, demand at thehigh load forecast, and natural gas price at the high fuel price forecast).

Results of this cost-risk sensitivity test are reported in Table 24. The risk-adjusted realresource savings “with NT2” are estimated to be US$188 million. These resultsconfirm our Base Case conclusion that NT2 is a viable investment project from aneconomic perspective, and suggest that the net benefits accruing from the inclusion ofNT2 in the least-cost plan appear to be relatively robust even after consideration ofdownside risks to the project.


Table 24. Economic Cost-Risk Sensitivity Test


Case Probability Case Probability Case Probability Case Present Value Probability Scenarioh 0.25 h 0.25 h 0.25 hhh 46,808 0.01563 61 h 0.25 h 0.25 m 0.50 hhm 46,808 0.03125 61 h 0.25 h 0.25 l 0.25 hhl 43,741 0.01563 (6) h 0.25 m 0.50 h 0.25 hmh 46,808 0.03125 61 h 0.25 m 0.50 m 0.50 hmm 46,808 0.06250 61 h 0.25 m 0.50 l 0.25 hml 43,741 0.03125 (6) h 0.25 l 0.25 h 0.25 hlh 34,548 0.01563 (181) h 0.25 l 0.25 m 0.50 hlm 34,548 0.03125 (181) h 0.25 l 0.25 l 0.25 hll 32,214 0.01563 (259) m 0.50 h 0.25 h 0.25 mhh 46,603 0.03125 266 m 0.50 h 0.25 m 0.50 mhm 46,603 0.06250 266 m 0.50 h 0.25 l 0.25 mhl 43,536 0.03125 199 m 0.50 m 0.50 h 0.25 mmh 46,603 0.06250 266 m 0.50 m 0.50 m 0.50 mmm 46,603 0.12500 266 m 0.50 m 0.50 l 0.25 mml 43,536 0.06250 199 m 0.50 l 0.25 h 0.25 mlh 34,343 0.03125 24 m 0.50 l 0.25 m 0.50 mlm 34,343 0.06250 24 m 0.50 l 0.25 l 0.25 mll 32,009 0.03125 (54) l 0.25 h 0.25 h 0.25 lhh 46,399 0.01563 471 l 0.25 h 0.25 m 0.50 lhm 46,399 0.03125 471 l 0.25 h 0.25 l 0.25 lhl 43,331 0.01563 404 l 0.25 m 0.50 h 0.25 lmh 46,399 0.03125 471 l 0.25 m 0.50 m 0.50 lmm 46,399 0.06250 471 l 0.25 m 0.50 l 0.25 lml 43,331 0.03125 404 l 0.25 l 0.25 h 0.25 llh 34,138 0.01563 228 l 0.25 l 0.25 m 0.50 llm 34,138 0.03125 228 l 0.25 l 0.25 l 0.25 lll 31,804 0.01563 151






POWER DEMAND GAS PRICE

CONSTRUCTION COST POWER DEMAND GAS PRICE SCENARIO RESULTS (2003 USD million)


Commercial Assessment 5 7

6 COMMERCIAL ASSESSMENT

The objective of this chapter is to evaluate whether NT2 is part of the region’s least-cost generation expansion plan for meeting the future electricity needs when this planis evaluated at nominal market prices (versus the real resource costs discussed inChapter 5). The cost-risk analytical framework outlined in Chapter 4 is applied togive a single answer that incorporates uncertainties associated with future loadgrowth and fuel prices.

Section 6.1 summarizes the basic assumptions adopted for system expansion planningat nominal market prices. Section 6.2 presents Base Case results, and Section 6.3reports the results of the commercial cost-risk analysis.

6.1 Commercial Planning Assumptions

6.1.1 Basic Commercial AssumptionsThe World Bank has specified the following basis for the commercial analysis of NT2:

All costs represent market prices; as such they include internal fiscal transfers(e.g. taxes, duties, and subsidies)

All values are expressed in nominal (i.e., current year) US dollars

The discount rate is 10.45% nominal, the estimated weighted average costof capital.

The MUV Index (a UN index of the unit value of manufactured exportsfrom G-5 industrial countries to developing country markets, expressed inUS dollars) is used as the price inflator to restate any constant US dollarcosts or revenues into their future year nominal equivalents; the MUVindex averages 0.7 percent per annum through 2015.

An exchange rate of 40 Thai Baht per US dollar was used for planningpurposes.

6.1.2 System CharacteristicsAs previously noted in the economic analysis of Chapter 5, system characteristicsadopted for the current study follow EGAT’s Power Development Plan for 2003(PDP2003) as published in April 2003. Characteristics common to both the


Economic and Commercial runs of PROSCREEEN, as detailed in Chapter 4, aresummarized below:

The Base Case load forecast is Thailand’s official Base Case of August 2002(see Chapter 3), augmented by a Lao PDR domestic load of 75 MW and300 GWh.

The reliability criterion is a reserve margin of 15 percent, EGAT’s currentreserve criterion to assure system reliability.




NT2 (995 MW) added to the system in October 2009 (FY2010) in the“with NT2” scenarios.

All other plants – including plants proposed for reconditioning and allgeneric expansion options (see Table 13) – are modeled as candidateswhich much compete for a place in the least cost economic plan. (Notethat candidates for “reconditioning” – South Bangkok thermal (units 3-5)and Bang Pakong (unit 1) – are only permitted to enter the expansion planin the year following scheduled retirement.)


All non-thermal generation – notably domestic hydro plants and Laoimports – is dispatched first, without regard to cost. With theexception of EGAT’s own hydro capacity, each of these resources ismodeled as a separate transaction, defined from contractualpurchase price and operating constraints.

NT2 energy is dispatched as two transactions, one to provide peak-period energy at the Primary Energy tariff (“PE”), and a second toprovide off-peak energy at the Secondary Energy tariff (“SE1”).Optional off-peak generation is not assumed.

All thermal generation – the majority of the entire system – is subjectto economic dispatch, and run only when it is lowest cost.Exceptions are small power producers (SPPs), which are assumed torun at an 80 percent capacity factor.45

45 This is a reasonable assumption given the high percentage of this output which is fossil fueled(predominantly by gas).


6.1.3 The Cost of NT2The cost of NT2 is evaluated differently in the Economic and Commercial analyses. Inthe commercial analysis, NT2 is modeled as a power purchase based on the actualPPA tariff over a 25-year period. The 995 MW plant is available from FY2010(October 2009).

The power purchase tariff for each tariff period is set by contract at a specific annualvalue. There is no escalation formula; rather, the starting tariff is escalated by a fixedannual factor of approximately 1.038 percent in order to achieve the negotiatedlevelized tariff over the life of the project. Rates have a Thai Baht component; for ouranalysis these have been re-stated in dollar-terms at the study exchange rate (40THB/US$). Actual tariffs are not reported here for the sake of confidentiality.46

Additionally, the cost of each kWh is increased by US$0.00615, the estimatedlevelized cost of incremental transmission investments required to deliver all plannedLao hydro purchases from the Thai border to the nearest 500 kV line (fortransmission to the Bangkok metropolitan area).47

The commercial analysis in PROSCREEN requires additional assumptions, as explainedin the following section.

6.1.4 Private Sector Commercial ViewOur commercial analysis at nominal prices must reflect market-based financialconditions. The majority of national generating capacity is already privatized, and it ispresumed that all future capacity will be developed by the private sector. Theappropriate planning criteria for commercial decision-making is a weighted averagecost of capital, discount rate, and levelized fixed charge rates which reflect the costsof private developers who will be competing for these projects. Were candidatesdefined based on a lower cost of capital they would likely appear less expensive incomparison with projects developed by the private sector, such as NT2 andcommitted IPPs.

For this study, the weighted average cost of capital (WACC) has been calculated asfollows:

46 Confidentiality is an issue of some importance to this Study; power purchase tariffs of negotiatedIPPs have been withheld from the Consultant as per contractual agreement with developers regardingconfidentiality. We understand and respect this concern.

47 As clarified by EGAT transmission planners, the levelized cost is based on transmitting 3,300 MWfrom agreed border crossing points to Tha Tako (near Nakhorn Sawan), the closest 500 kVconnection point. Specifically three 500kV double-circuit lines are included: (i) Tha Tako –Chayaphum, (ii) Chayaphum – Udorn – Nong Khai, and (iii) Chayaphum – Roi Et – Mukdahan.Planned additional reinforcement investments are excluded from the calculations.

Share Rate (%) WeightDebt (before tax) 0.70 8.5% 6.0%Equity 0.30 15.0% 4.5%

10.45%

Component


Debt and equity shares (70:30) are a compromise. Our discussions withinvestment bankers indicate that most large power projects will be financedon project basis (i.e., with no recourse to the developer), and hence nothighly leveraged (e.g., 1.5:1). However, once up and running for severalyears, it is not uncommon for these projects to be refinanced at higherleverage (e.g., 2.5 or 3:1)

The cost of debt before tax is assumed (rather than the more commonlyencountered tax shield adjustment in the WACC formula) upon thespecific recommendation of the authors of PROSCREEN.48

The assumed cost of debt (8.5 percent) is higher than some readers mightexpect for two reasons. First, this is a rate for long-term analysis, and so itshould reflect more than current short-term borrowing rates. Second,rates typically quoted in the market are variable rates which can fluctuatewith market conditions (e.g., LIBOR+X); a power project must typically“swap” (at a cost!) into a fixed rate to assure predictable cash flow.

Equity returns are in the range 16–18 percent before tax according toinvestment bankers. We have picked the middle of the scale, i.e., 15 percentafter tax.

Further, we have adopted the above WACC (10.45 percent) as the discount rate forthe analysis.

Finally, we have calculated the levelized fixed charge rate for candidate additions asrecommended by the authors of PROSCREEN:

48 It is unclear whether this recommendation is due to uncertainty regarding the tax benefit, orwhether it is accounted for internally within the model.

LEVELIZED FIXED CHARGE RATE by project life Gas Combined Coal / OilTurbine Cycle Thermal

life (yrs): 15 25 30WACC ) 1/ 0.1045 0.1045 0.1045 + Sink.Fund Depreciation ) 0.0304 0.0095 0.0056 + Levelized Income Tax 2/ 0.0169 0.0186 0.0196 + Other Taxes 3/ 0.0050 0.0050 0.0050 = 0.1568 0.1376 0.1347

1/ Sum of these two items is equal to the capital recovery factor.2/ Levelized tax calculated as recommended by PROSCREEN:

= (Cap Recovery Factor - Applicable Depreciation)x (1 - debt share x debt cost / WACC)x (tax rate / (1 - tax rate)) assuming a 35 percent tax rate

3/ A notional amount to reflect additional costs such as property and other taxes, insurance, etc.


6.2 Commercial Base Case Results

The economic analysis presented in Chapter 5 concludes that NT2 – when analyzedfrom the perspective of real resource costs – will generate substantial savings to theregion – on the order of US$266 million. The objective of the commercial risk analysisis to determine the project's commercial sustainability after transfer payments imposedon the project beyond the real resource costs are also considered. Examples of thesetransfers include taxes, duties, and royalties. Commercial costs also include developersunk costs at the time of analysis. Further, the analysis is based on commercial termsof capital recovery at current prices.

Table 25 summarizes the results of the Commercial Base Case scenario with NT2included in the expansion plan from FY2010. A total of 15,706 MW are added to thesystem during the planning period. In addition to NT2 (995 MW), this total includes4,792 MW of committed capacity, (i.e., not competing for a place in the plan). All ofthe candidates selected to meet future load are gas-fired. Recommended additionsinclude 10,500 MW of combined cycle plant, 690 MW of gas turbines, and 1,480 MWof reconditioned thermal plants – the same program recommended in the economicBase Case analysis.

The PV of total cost over the Study Period is US$61,939 million when NT2 isincluded in the expansion plan.

Table 25 also presents results of a planning model run in which NT2 is not included inthe plan. This case requires two more combined cycle units (1400 MW) in FY2010,but one less in FY2012; it also requires additional gas turbine units FY2011 andFY2014. The estimated PV of total costs over the Study Period is US$62,166.

In summary, the Base Case commercial analysis suggests that the decision to purchaseNT2 power will have a net benefit on the order of US$227 million. This resultindicates that the large real resource benefits accruing to the region fromdevelopment of NT2 in the economic analysis is slightly reduced when the above-noted transfer payments associated with the project are treated as project costs.Under Base Case commercial assumptions, however, the project remains viable from apurely commercial perspective.

The economic analysis indicates that NT2 has a clear benefit to the region. The BaseCase commercial result confirms this conclusion.


Table 25. Commercial Base Case

Fiscal Installed ReserveYear MW Addition Retirement CC GT Recondition Import Margin2003 23,830 37.4%2004 24,715 886 33.5%2005 24,775 60 25.5%2006 24,604 20 (191) 16.9%2007 25,996 1,727 (335) 15.9%2008 27,723 1,400 (373) 700 16.0%2009 29,451 700 (373) 1,400 15.1%2010 31,376 (310) 700 230 310 995 15.1%2011 33,236 (310) 1,400 460 310 15.1%2012 35,336 2,100 15.5%2013 37,436 (310) 2,100 310 15.4%2014 39,536 (550) 2,100 550 15.1%

Total 39,536 4,792 (2,752) 10,500 690 1,480 995

Fiscal Installed ReserveYear MW Addition Retirement CC GT Recondition Import Margin (%)2003 23,830 37.4%2004 24,715 886 33.5%2005 24,775 60 25.5%2006 24,604 20 (191) 16.9%2007 25,996 1,727 (335) 15.9%2008 27,723 1,400 (373) 700 16.0%2009 29,451 700 (373) 1,400 15.1%2010 31,551 (310) 2,100 310 15.7%2011 33,411 (310) 1,400 460 310 15.7%2012 35,271 1,400 460 15.3%2013 37,371 (310) 2,100 310 15.2%2014 39,701 (550) 2,100 230 550 15.6%

Total 39,701 4,792 (2,752) 11,200 1,150 1,480 -





Committed Plant

Committed Plant



-40

0

40

80

120

160

200

240

2010 2015 2020 2025 2030 2035

US

$ m

illi

on

with NT2 without NT2


6.3 Cost-Risk Analysis

As specified in the TOR, the study outcome is determined by means of the resultsprofile shown in Table 16 (the “Cost-Risk Framework”) according to themethodology described in Section 4.2. The results of the economic cost-risk analysisbased on real resource costs are presented in Section 5.3, and summarized in Table23.

A cost-risk analysis has also been prepared as part of the commercial evaluation. Theframework is identical to that shown in Table 16, and the objective remains the same– to determine whether the same decision is justified if future events diverge from theBase Case assumptions. The commercial cost-risk analysis considers only two keydecision variables – the demand forecast and the price of natural gas – since thecommercial value reflecting NT2 cost has been fixed through a firm power purchaseagreement.

The demand forecast for the Base Case, High and Low scenarios is describedin Section 2; it is the same forecast applied for the economic assessment.

As discussed in Section 3.3, the World Bank has developed its own fuel priceprojections, with particular emphasis on the price of natural gas since it is themost competitive alternative fuel. The Base Case commercial projections arepresented in Table 14; High and Low scenarios are reported in Appendix A3.

The TOR specifies the probability of each assumption value. Each “expected” (i.e.,Base Case) assumption has a probability of 50 percent in the cost-risk matrix, withthe High and Low assumptions assigned a probability of 25 percent each. (As notedearlier, a combination of experience, judgment and – when available – historicalevidence went into the selection of these probabilities.)

For reasons noted in Section 5.3, it was not possible to prepare separatePROSCREEN models for all possible scenarios in the cost-risk framework. It wastherefore decided to focus the cost-risk analysis for the current study only on thedownside risks to NT2. Specifically, the analysis was limited to the base case and thosecases which could be expected to pose the greatest test to project viability, i.e.,conditions of lower than expected demand, lower than expected fuel prices.

Section 6.3.1 reports the impact of these individual variables on the least-costexpansion plan. Section 6.3.2 then presents their collective impact in the resultingcommercial cost-risk analysis.

6.3.1 Sensitivity AnalysisThis section reports the sensitivity of the Base Case results to changes in the values ofindividual variables. As noted above, these sensitivities involve variables that can beexpected to delineate the downside risk to the project:


Sensitivity to a lower demand forecast

Sensitivity to a lower forecast for natural gas and other fuels

Sensitivity to a Lower Demand Forecast

The spread between the base and low demand forecasts adopted for this study isdramatic: By FY2012, the Low Case is only 75 percent of the Base Case. Notsurprisingly, system expansion requirements are reduced as a result. Table 26summarizes the expansion plans required under the Low load forecast, and the graphcompares this result with the Base Case results reported in Table 25.

Table 26 suggests that lower-than-expected demand “with NT2” would come at acost (US$32 million vs. US$266 savings in the Base Case) equal to about 3 percent ofthe total stream of PPA payments for NT2 power over twenty-five years. This resultfollows from the fact that new gas-fired generation is not required in the “withoutNT2” case until FY2014. With perfect knowledge confirming dramatically lower-than-expected demand for electricity in the region, NT2 could be delayed beyond itsscheduled FY2010 COD.

Sensitivity to Lower Natural Gas Prices

Differences between high and low fuel price forecasts adopted for the study are notas dramatic as the spread noted for the demand forecast. (The prices adopted forthese sensitivity scenarios are reported in Appendix A3.) Although natural gas priceshave recently reached historical levels, long-term forecasts do not presume that thistrend will continue unabated. In Thailand, the price of gas is closely linked to thedemand for electricity, as the power sector accounts for over 70 percent of totalnatural gas demand. With low demand, supplies of domestic gas will be more thansufficient to meet domestic requirements at least over the planning period.

When scenarios are run with low fuel prices, gas remains the fuel of choice forincremental capacity both “with NT2” and "without NT2".

Details of the Low natural gas price scenarios are presented in Table 27. Under theassumption of low gas prices, the decision to develop NT2 results in a PV savings ofUS$161 million, about 30 percent less than the Base Case result (US$227 million).Savings can be attributed directly to fuel costs, since expansion plans for the low gasprice sensitivity are identical to the Base Case.


Table 26. Sensitivity of Results to Lower Demand

Fiscal InstalledYear MW CC GT Recondition Import2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,023 2009 27,351 2010 28,346 310 995 2011 28,346 310 2012 28,346 2013 28,346 310 2014 28,346 550

Total 28,346 - - 1,480 995

Fiscal InstalledYear MW CC GT Recondition Import2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,023 2009 27,351 2010 27,351 310 2011 27,351 310 2012 27,351 2013 27,351 310 2014 28,281 700 230 550

Total 28,281 700 230 1,480 -



PV of Savings with NT2 A. Planning Period (2003-2014) (112) B. End-Effects Period 80 C. Study Period (A + B) (32) % of total cost -0.07%

LOW DEMAND SCENARIO

Low Demand




-120

-80

-40

0

40

80

120

160

200

240

2010 2015 2020 2025 2030 2035

US

$ m

illi

on

with NT2 Commercial Base Case Low Demand


Table 27. Sensitivity of Results to Lower Natural Gas Prices

Fiscal InstalledYear MW CC GT Recondition Import2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,723 700 2009 29,451 1,400 2010 31,376 700 230 310 995 2011 33,236 1,400 460 310 2012 35,336 2,100 2013 37,436 2,100 310 2014 39,536 2,100 550

Total 37,495 10,500 690 1,480 995

Fiscal InstalledYear MW CC GT Recondition Import2003 23,830 2004 24,715 2005 24,775 2006 24,604 2007 25,996 2008 27,723 700 2009 29,451 1,400 2010 31,551 2,100 310 2011 33,411 1,400 460 310 2012 35,271 1,400 460 2013 37,371 2,100 310 2014 39,701 2,100 230 550

Total 39,701 11,200 1,150 1,480 -





Low Gas Price

LOW GAS PRICE SCENARIOPlanned Additions (including NT2)


-40

0

40

80

120

160

200

240

2010 2015 2020 2025 2030 2035

US

$ m

illio

n

with NT2 Commercial Base Case Low Gas Price


Table 28. Commercial Cost-Risk Analysis

6.3.2 Cost-Risk Analysis ResultsThe results of the commercial cost-risk analysis are summarized in Table 28. Aspreviously noted, the framework is incomplete, since High demand and High gas pricescenarios have not been prepared. The review of downside risks represents only 56percent of a complete cost-risk assessment. However, it must be noted that thescenarios excluded would be expected to record greater net benefits “with NT2” thanthe reported cases.

Taking all evaluated potential outcomes into account, a system expansion planfeaturing the commissioning of NT2 in October 2009 is the correct decision from aneconomic least-cost perspective. Even when only downside risks are evaluated, theprobability-weighted PV of total savings over the entire Study Period is estimated tobe US$118 million, equivalent to more than US$0.004 per kWh sold from the NT2project.

A Low natural gas price reduces total savings by US$105 million, although the netbenefit “with NT2” is still significant (US$161 million). In contrast, Low demandwould mean that the decision to develop NT2 in FY2010 would come at a cost ofUS$32 million. Results are least favorable for NT2 when combinations of adversefuture conditions (e.g., low demand and low gas prices) are considered.

Reaching a conclusion based on an incomplete cost-risk results matrix may be a causefor concern given even a low probability of negative outcomes. To address this


Case Probability Case Probability Case Probability Case Present Value Probability Scenariom 1.00 h 0.25 h 0.25 mhh - - m 1.00 h 0.25 m 0.50 mhm - - m 1.00 h 0.25 l 0.25 mhl - - m 1.00 m 0.50 h 0.25 mmh - - m 1.00 m 0.50 m 0.50 mmm 61,939 0.25000 227 m 1.00 m 0.50 l 0.25 mml 58,900 0.12500 161 m 1.00 l 0.25 h 0.25 mlh - - m 1.00 l 0.25 m 0.50 mlm 43,886 0.12500 (32) m 1.00 l 0.25 l 0.25 mll 41,529 0.06250 (109)



Case Probability Case Probability Case Present Value Probabilityh 0.25 h 0.25 hh - h 0.25 m 0.50 hm - h 0.25 l 0.25 hl - m 0.50 h 0.25 mh - m 0.50 m 0.50 mm 62,166 0.25000 m 0.50 l 0.25 ml 59,060 0.12500 l 0.25 h 0.25 lh - l 0.25 m 0.50 lm 43,854 0.12500 l 0.25 l 0.25 ll 41,420 0.06250







concern, we have completed the entire cost-risk framework based on the veryconservative assumption that every “High” demand or gas price scenario will achievesavings identical to its closest “Medium” counterpart scenario (e.g., the “High demand,High gas price” scenario is assigned the savings of the “Medium demand, Medium gasprice” scenario) even though we know, both intuitively and from our modeling forRELC/2004, that these scenarios would be expected to produce additional savings.

This approach is mathematically equivalent to assigning a 75 percent probability tothe “Medium” results and a “zero” percent probability to future events would proveadvantageous to NT2 (i.e., construction cost at the low cost estimate, demand at thehigh load forecast, and natural gas price at the high fuel price forecast).

Results of this cost-risk sensitivity test are reported in Table 24. The risk-adjustedsavings “with NT2” are estimated to be US$145 million. These results confirm ourBase Case conclusion that NT2 is a viable investment project from a commercialperspective.

Table 29. Commercial Cost-Risk Sensitivity Test


Case Probability Case Probability Case Probability Case Present Value Probability Scenariom 1.00 h 0.25 h 0.25 mhh 61,939 0.06250 227 m 1.00 h 0.25 m 0.50 mhm 61,939 0.12500 227 m 1.00 h 0.25 l 0.25 mhl 58,900 0.06250 161 m 1.00 m 0.50 h 0.25 mmh 61,939 0.12500 227 m 1.00 m 0.50 m 0.50 mmm 61,939 0.25000 227 m 1.00 m 0.50 l 0.25 mml 58,900 0.12500 161 m 1.00 l 0.25 h 0.25 mlh 43,886 0.06250 (32) m 1.00 l 0.25 m 0.50 mlm 43,886 0.12500 (32) m 1.00 l 0.25 l 0.25 mll 41,529 0.06250 (109)









Conc lu s ion 6 9

7 CONCLUSION

Economic and Commercial assessments of the project conclude that the decision topurchase NT2 power offers significant savings to the regional power system.

The economic evaluation, based on a probability-weighted real cost-risk analysis ofdownside risks, indicates a real savings (i.e., in present value terms at 2003 prices) onthe order of US$188 million will accrue to the region over the lifetime of the plant.

Actual savings might be even higher under possible future conditions, such as higher-than-expected demand growth or higher-than-expected gas prices. Moreimportantly, however, the decision to purchase a major source of energy at fixed priceis robust to a wide range of behavior for the key uncertain factors that influence theproject’s long-term value-added. In particular, the individual scenarios show that theproject is very robust with respect to fossil fuel price volatility, a feature of energymarkets in recent decades that is expected to persist. As with any risk-return trade-off, the project is also subject to reduced net benefits if future economic conditionsare adverse from the perspective of NT2, i.e., lower-than-expected demand and gasprices.

The commercial analysis, based on market costs expressed in current prices, suggeststhat the decision to purchase NT2 power will result in a nominal savings in presentvalue terms on the order of US$145 million. This result indicates that the projectremains commercially viable even after large real resource benefits accruing to theregion in the economic analysis are paid by project sponsors directly to thegovernment of Lao PDR in the form of taxes, duties, and royalties, and indirectlythrough the funding of environmental and social programming.

Terms of Reference 7 1

A1 Terms of Reference

Terms of Reference for Determining the Economic Least-Cost Justification forthe Nam Theun 2 Regional Hydro-electric Power Project

[A] Context

The World Bank has received the Thailand Power Scenario Study (TPSS)49 andacknowledges its valuable contribution to understanding the commercial rationale ofthe Nam Theun 2 (NT2) Project in the context of the Thai power system. Elementsfrom the TPSS are adopted as indicated in this terms of reference (ToR), whichdescribes the next stage of the economic due diligence the Bank requires50 todetermine whether the project has a satisfactory economic cost-risk profile for theregional51 power market. The main distinguishing characteristics of this second stageanalysis are threefold: (i) to the greatest extent feasible, all values reflect real economicresource costs, (ii) the scope of work includes both the Thai and Laotian electricitymarkets, and (iii) the risk analysis consists of an integrated multi-event probabilisticframework that produces one overall quantitative result showing whetherimplementing the NT2 project for 2009 would be an acceptable economic investmentfor the power sector.

The Bank acknowledges that the full participation of the Electricity GeneratingAuthority of Thailand (EGAT) is important to the conduct of this study. The Bankexpects the Consultant to work with EGAT much in the manner done for the TPSS.Because the multiple scenario analysis required to implement this ToR may need asubstantial commitment of EGAT’s human and computer resources over a relativelyshort period of time, the Bank is prepared to help the Consultant and EGATaccommodate operational constraints in this respect.

[B] Study Outcome

The study outcome will be determined by means of the results profile shown in Annex1: “Cost-Risk Framework”. This profile provides for calculating the probability-weighted present value (PV) costs of either implementing or not implementing NT2for 2009, given the interplay of several major uncertain factors – project cost, long-term demand for electricity and long-term economic value of natural gas as well as thesuggested probabilities of occurrence for Base Case, Lower and Higher estimates ofthese variables. The difference between the probability weighted PV cost of 49 “Thailand Power Scenario Study”, by Robert Vernstrom, consulting economist, Bangkok, March2003. The World Bank financed and supervised this study.

50 World Bank guidelines for the economic evaluation of investment operations, including electricpower projects: OP 10.04 and GP 4.45.

51 “Regional” means Laos and Thailand in this Terms of Reference.


implementing the project in 2009 versus that of not implementing it is the decisioncriteria for this analysis by showing whether the project is an acceptable economicinvestment for the regional power market.

The following sections describe the Bank’s requirements for this stage of its economicdue diligence. Because the Bank is specifying these requirements for the purpose of areal resource cost-based analysis, neither the Consultant nor EGAT would be heldaccountable for specific assumptions and values that the Bank requires or to whichthe Bank agrees. The Bank acknowledges that the methods and values used in thisstudy for its purposes are completely without prejudice to different ones that EGATmay consider as more appropriate for its own operating context and requirements.

[C] Basic Parameters

1. All values will be expressed in terms of real US dollars of 2003.2. The discount rate will be 10% real.3. The power system reliability criterion for generation capacity expansion is

EGAT’s standard of 15% reserve margin over forecast peak load.4. All costs will exclude internal fiscal transfers (e.g. taxes and subsidies).5. NT2 is commissioned in 2009 in the “with project” case, or not at all in the

“without project’ case.6. The expected values of NT2 production for primary energy and secondary

energy are as stated in the TPSS. The study will check whether it is reliable toassume that the probability of under-achieving these values is negligible, andshall document evidence to support this assumption.

7. The scenarios with NT2 should include a carbon credit of $x per ton ofcarbon displaced by NT2 to be credited against the operating costs of NT2.The Bank will confirm the acceptable unit value per ton carbon.

8. The system expansion period will end in the year that the NT2 projectoutput would be fully absorbed under the low demand forecast. The durationof the run-out period for end effects will be till the year at which the residualvalue in that year would discount to an insignificant present value. The Bankwill discuss with the consultant how the power system model neutralizes endeffects before the model runs are undertaken.

9 . The EGAT plant retirement schedule is adopted, subject to reportingrequirements described in Section [F].

[D] Variables

[D.1] Demand Forecast:

1. The Base Case Demand Forecast used in the Thailand Power Scenario Studyis acceptable for the Thai load. For Laotian demand, the Bank recommends aBase Case in which Laos fully absorbs 200GWh of energy in the year theproject is commissioned.

2. For both countries the Low Case demand forecast will be keyed off the BaseCase forecast using the following equation, reflecting the percentage gap


between these forecasts the Bank considers appropriate by year 10 into theforecast period (based on forecasting experience in Thailand and elsewhere):

(1+grL)^10 = 0.75*(1+grB)^10

where grL means Low Case growth rate of demand and grB means Base Casegrowth rate of demand.

3. The High Case load forecast will be symmetrical to that of the Low Case. Thegrowth rate for the High Case (“grH”) will therefore be determined accordingto the following formula:

(1+grH)^10 = 1.25*(1+grB)^10

[D.2] NT2 Project

1. The Bank will provide the real cash flows for the Base Case economicinvestment and operating costs of the NT2 project based on data from theproject lenders’ financial model. This cash flow series will exclude transfers andsunk costs, but include incremental sponsor development costs that reflectuse of real resources.

2. The High Case for the construction cost of NT2 will be 30% above of theexpected construction cost used for the Base Case. The Low Case for theconstruction cost of NT2 will be 30% below that of the Base Case.

[D.3] Other Power Generation Technologies

1. The screening curve analysis of the type used in the TPSS will be deployedusing real economic costs to determine the least-cost alternative options,using the same technologies as in the TPSS. It is expected that as in the TPSS,natural gas will emerge as the primary alternative to NT2. In case it does not,several aspects of this ToR related to fuel value and fuel value risk will need tobe revised accordingly.

2. The real economic costs of alternative generation capacity will also includeprivate sector incremental development costs appropriate to thosetechnologies.

3. The Bank recommends that there be a spread of about USD200/kW toappropriately reflect the EPC cost difference between GT and CCGT plant.

4 . The Bank will confirm with the consultant the actual EPC costs anddevelopment cost margins to be used for GT and CCGT capacity.

5. The Consultant will assume that Laos’ alternative to NT2 for meeting thatportion of its demand would be import of electricity from Thailand.

[D.4] Oil Products and Natural Gas

1 . The Bank will confirm with the consultant the real values it considersacceptable for oil product prices in the screening curve analysis, as well as theBase, Low and High natural gas price trajectories.


2. The coal prices in the TPSS may be adopted, unless it seems appropriate tomake some adjustment in relation to the assumptions for natural gas and oilproduct prices to be used in this study.

[D.5] Transmission

1. The project-associated transmission works in Laos are included in the projectcost.

2. The project-associated incremental transmission costs for Thailand need to bedetermined in co-operation with EGAT on a basis that does not include anyother future hydro exports from Laos to Thailand, because of theiruncertainty, notwithstanding the higher level of potential exports containedin the MoU between the two countries on power exports from Laos toThailand.

3. If EGAT and the consultant believe that the non-NT2 options also requireincremental generation-associated transmission works, the economic costs ofthese should be determined and included.

[E] Modeling

1. The Consultant will use EGAT’s Proscreen Model as in the TPSS, subject tothe custom parameter and variable assumptions made for this study.

2 . Before the modeling begins, Bank staff will obtain from EGAT and theconsultant, by verbal and documentary communication, a clear understandingof how this model works, especially but not limited to the following factors: (i)optimization and simulation characteristics, (ii) treatment of mixed hydro-thermal capacity (valuation of stored water, optimization of hydro-electricreservoir management), (iii) dispatching optimization (stacking merit order anddispatching algorithm), and (iv) calculation of end effects.

3. In these model runs, NT2 and all other generation capacity on the regionalpower system – including existing capacity owned and operated by IPPs - willbe subject to economic dispatch for meeting incremental demand and thespecified amount of Laotian demand, without consideration of contractualtake-or-pay constraints.

4. Before proceeding with paragraph E5 below, two sensitivity tests are required:(i) for the MMM case (ref. Annex 1) a “with” and “without” NT2 comparisonin a situation where the commissioning of NT2 is delayed for 24 months, theinvestment cash flow being extended over the additional time period, and (ii)the same test but with a 30% cost over-run of NT2 (the HMM case of Annex1). The results of these tests should be reported to the Bank beforecommencing the model runs described below, to determine whether it wouldbe appropriate to amend the cost-risk analysis framework (Annex 1).

5. To complete the Cost-Risk Framework (Annex 1), a total of 18 scenario runswill be required, 9 with NT2 and 9 without NT2 as described in the Annex.The scenarios are formed from combinations of two planning variables –power demand and natural gas price. Three cases– high, base, low – are usedfor each of these variables.


6. The 9 scenarios run with NT2 will be expanded to 27 scenarios by combiningmanually the three cases for the construction cost of NT2 with the results ofthese scenarios.

7. The probabilities associated with the High, Medium and Low assumptions arestated in Annex 1.

8. A second set of model runs for these scenarios will be carried out underwhich the economic values are converted to commercial values, but expressedin real US dollars of 2003, using the same framework as in Annex 1, in orderto assess the commercial sustainability of the NT2 Power Purchase Agreementagainst the underlying economic trends in the regional power market.

[F] Reporting

This study will serve a number of purposes eventually involving a considerable range ofaudiences within and outside of the World Bank. For this reason, it is essential thatthe reporting of this work be thorough and self-standing, so that the assumptions,methods and corresponding results are detailed, transparent and easilyunderstandable.

Without limitation to the generality of this requirement, the Bank stresses theimportance of comprehensive documentation, in Annexes as appropriate, for certainkey aspects:

1. The economic characteristics of the NT2 project.2. The Base Case demand forecast (forecasting methods, key input assumptions,

benchmark data and main results per consumer category);3. Justification for NT2 hydrological performance assumption;4. Explanation for assuming in respect of NT2 that there is no systemic bias in

the estimated construction cost for NT2, namely that no difference should beassumed between Base Case estimated and Base Case expected project cost;

5. The valuation of oil products and natural gas;6. The status of the individual power plants included in the EGAT retirement

schedule adopted for this study;7. Model characteristics and modeling implementation;8. Description of the logic underlying the cost-risk decision framework;9. Explanation of results, and enhanced explanation of any counter-intuitive

results;10. Explanation of differences in values and results between the economic and

commercial model runs; and11. For the commercial runs, how the PPA revenues are composed and converted

to US dollar terms.12. For data output, the Bank requires the present values of each of the major

components contributing to the total PV cost of each scenario, in order tofacilitate a clear understanding of the reasons for differences in total PV costbetween scenarios. The Bank also requires production and value data for thedispatch of each plant at five year intervals in the MMM case, to betterunderstand how the model handles the merit order, and the contribution inenergy and cost of each operating facility.


Annex 1: Cost-Risk Framework

1234567891011121314151617181920212223242526272829303132333435363738394041424344454647

A B C D E F G H

Value Probability Value Probability Value Probability Value Probabilityh 0.25 h 0.25 h 0.25 hhh 0.01563h 0.25 h 0.25 m 0.50 hhm 0.03125h 0.25 h 0.25 l 0.25 hhl 0.01563h 0.25 m 0.50 h 0.25 hmh 0.03125h 0.25 m 0.50 m 0.50 hmm 0.06250h 0.25 m 0.50 l 0.25 hml 0.03125h 0.25 l 0.25 h 0.25 hlh 0.01563h 0.25 l 0.25 m 0.50 hlm 0.03125h 0.25 l 0.25 l 0.25 hll 0.01563m 0.50 h 0.25 h 0.25 mhh 0.03125m 0.50 h 0.25 m 0.50 mhl 0.06250m 0.50 h 0.25 l 0.25 mhi 0.03125m 0.50 m 0.50 h 0.25 mmh 0.06250m 0.50 m 0.50 m 0.50 mmm 0.12500m 0.50 m 0.50 l 0.25 mml 0.06250m 0.50 l 0.25 h 0.25 mlh 0.03125m 0.50 l 0.25 m 0.50 mlm 0.06250m 0.50 l 0.25 l 0.25 mll 0.03125l 0.25 h 0.25 h 0.25 lhh 0.01563l 0.25 h 0.25 m 0.50 lhm 0.03125l 0.25 h 0.25 l 0.25 lhl 0.01563l 0.25 m 0.50 h 0.25 lmh 0.03125l 0.25 m 0.50 m 0.50 lmm 0.06250l 0.25 m 0.50 l 0.25 lml 0.03125l 0.25 l 0.25 h 0.25 llh 0.01563l 0.25 l 0.25 m 0.50 llm 0.03125l 0.25 l 0.25 l 0.25 lll 0.01563

WGTD PV 1.00000[B] Present Values Without NT2

Value Probability Value Probability Value Probabilityh 0.25 h 0.25 hhh 0.06250h 0.25 m 0.50 hhm 0.12500h 0.25 l 0.25 hhl 0.06250m 0.50 h 0.25 hmh 0.12500m 0.50 m 0.50 hmm 0.25000m 0.50 l 0.25 hml 0.12500l 0.25 h 0.25 hlh 0.06250l 0.25 m 0.50 hlm 0.12500l 0.25 l 0.25 hll 0.06250

WGTD PV 1.00000

0.00000Net PV with NT2

Power Demand Gas Price Scenario

Cost-Risk Analysis Matrix[A] Present Values with NT2

Construction Cost Power Demand Gas Price Scenario

Thailand Demand Forecast 7 7

A2 Thailand Demand Forecast

This appendix provides details of Thailand’s official Aug-02 load forecast. Thisforecast, supplemented by Lao PDR domestic load to be served by NT2 (75 MWcapacity and 300 GWh generation), is the Base Case load forecast for our regionalstudy. Table A2-5 provides a comparison of the Aug-02 forecast with the moreoptimistic Jan-04 forecast adopted for EGAT’s 2004 Power Development Plan.

This appendix includes the following tables:

Table A2-1. EGAT Total Generation Requirement Forecast

Table A2-2. EGAT Total Sales Forecast

Table A2-3. MEA Purchases and Sales Forecast by Customer Class

Table A2-4. PEA Purchases and Sales Forecast by Customer Class

Table A2-5. Comparison of the Aug-02 and Jan-04 Forecasts


Table A2-1. EGAT Total Generation Requirement Forecast

Base Case_August 2002

Fiscal Peak Energy Load

Year Increase Increase Factor

MW % GWh % %Actual

1991 8,045.00 951.30 13.41 49,225.03 6,036.24 13.98 69.85

1992 8,876.90 831.90 10.34 56,006.44 6,781.41 13.78 72.02

1993 9,730.00 853.10 9.61 62,179.73 6,173.29 11.02 72.95

1994 10,708.80 978.80 10.06 69,651.14 7,471.41 12.02 74.25

1995 12,267.90 1,559.10 14.56 78,880.37 9,229.23 13.25 73.40

1996 13,310.90 1,043.00 8.50 85,924.14 7,043.77 8.93 73.69

1997 14,506.30 1,195.40 8.98 92,724.66 6,800.52 7.91 72.97

1998 14,179.90 -326.40 -2.25 92,134.44 -590.22 -0.64 74.17

1999 13,712.40 -467.50 -3.30 90,414.15 -1,720.29 -1.87 75.27

2000 14,918.30 1,205.90 8.79 96,780.72 6,366.57 7.04 74.06

2001 16,126.40 1,208.10 8.10 103,165.20 6,384.48 6.60 73.03

Average Growth1991-2001 - 821.15 7.20 - 5,452.40 7.68 -

Forecast2002 16,700.00 573.60 3.56 108,036.00 4,870.80 4.72 73.85

2003 17,843.00 1,143.00 6.84 114,754.00 6,718.00 6.22 73.42

2004 19,029.00 1,186.00 6.65 122,024.00 7,270.00 6.34 73.20

2005 20,295.00 1,266.00 6.65 130,232.00 8,208.00 6.73 73.25

2006 21,648.00 1,353.00 6.67 139,000.00 8,768.00 6.73 73.30

2007 23,020.00 1,372.00 6.34 147,835.00 8,835.00 6.36 73.31

2008 24,450.00 1,430.00 6.21 157,064.00 9,229.00 6.24 73.33

2009 26,143.00 1,693.00 6.92 168,004.00 10,940.00 6.97 73.36

2010 27,711.00 1,568.00 6.00 178,079.00 10,075.00 6.00 73.36

2011 29,321.00 1,610.00 5.81 188,446.00 10,367.00 5.82 73.37

2012 31,014.00 1,693.00 5.77 199,378.00 10,932.00 5.80 73.39

2013 32,842.00 1,828.00 5.89 211,146.00 11,768.00 5.90 73.39

2014 34,743.00 1,901.00 5.79 223,437.00 12,291.00 5.82 73.41

2015 36,754.00 2,011.00 5.79 236,364.00 12,927.00 5.79 73.41

2016 38,851.00 2,097.00 5.71 249,878.00 13,514.00 5.72 73.42

Average Growth1992-1996 - 1,053.18 10.60 - 7,339.82 11.79 -

1997-2001 - 563.10 3.91 - 3,448.21 3.73 -

2002-2006 - 1,104.32 6.07 - 7,166.96 6.14 -

2007-2011 - 1,534.60 6.26 - 9,889.20 6.28 -

2012-2016 - 1,906.00 5.79 - 12,286.40 5.81 -

Thailand Load Forecast Subcommittee

August 2002

MW GWh


Table A2-2. EGAT Total Sales Forecast


Fiscal Peak Energy Load

Year Increase Increase Factor

MW % GWh % %Actual

1991 8,000.92 926.17 13.09 44,773.24 5,404.46 13.73 63.88

1992 9,243.13 1,242.21 15.53 50,770.86 5,997.62 13.40 62.70

1993 10,336.68 1,093.55 11.83 56,558.43 5,787.57 11.40 62.46

1994 11,424.52 1,087.84 10.52 63,642.85 7,084.42 12.53 63.59

1995 12,990.34 1,565.82 13.71 72,779.57 9,136.72 14.36 63.96

1996 14,263.97 1,273.63 9.80 79,450.96 6,671.39 9.17 63.59

1997 15,475.54 1,211.57 8.49 85,896.66 6,445.70 8.11 63.36

1998 1 / 13,724.01 -1,751.53 -11.32 85,597.60 -299.06 -0.35 71.20

1999 13,596.30 -127.70 -0.93 84,512.03 -1,085.57 -1.27 70.96

2000 14,815.02 1,218.72 8.96 90,725.42 6,213.39 7.35 69.91

2001 16,005.76 1,190.74 8.04 97,412.45 6,687.03 7.37 69.48

Forecast

2002 16,643.00 637.24 3.98 102,260.00 4,847.55 4.98 70.14

2003 17,615.00 972.00 5.84 108,437.00 6,177.00 6.04 70.27

2004 18,724.00 1,109.00 6.30 115,447.00 7,010.00 6.46 70.38

2005 19,951.00 1,227.00 6.55 123,249.00 7,802.00 6.76 70.52

2006 21,270.00 1,319.00 6.61 131,553.00 8,304.00 6.74 70.60

2007 22,630.00 1,360.00 6.39 140,134.00 8,581.00 6.52 70.69

2008 24,062.00 1,432.00 6.33 149,258.00 9,124.00 6.51 70.81

2009 25,679.00 1,617.00 6.72 159,965.00 10,707.00 7.17 71.11

2010 27,238.00 1,559.00 6.07 169,885.00 9,920.00 6.20 71.20

2011 28,842.00 1,604.00 5.89 180,070.00 10,185.00 6.00 71.27

2012 30,514.00 1,672.00 5.80 190,798.00 10,728.00 5.96 71.38

2013 32,295.00 1,781.00 5.84 202,344.00 11,546.00 6.05 71.52

2014 34,159.00 1,864.00 5.77 214,391.00 12,047.00 5.95 71.65

2015 36,145.00 1,986.00 5.81 227,324.00 12,933.00 6.03 71.79

2016 38,223.00 2,078.00 5.75 240,786.00 13,462.00 5.92 71.91

Average Growth1992-1996 - 1,252.61 12.26 - 6,935.54 12.15 -

1997-2001 - 348.36 2.33 - 3,592.30 4.16 -

2002-2006 - 1,052.85 5.85 - 6,828.11 6.19 -

2007-2011 - 1,514.40 6.28 - 9,703.40 6.48 -

2012-2016 - 1,876.20 5.79 - 12,143.20 5.98 -

Note : 1/ 1991 - 1997 are non-coincident peak, while 1998 onwards are coincident peak of each electricity authority and direct customers.

Thailand Load Forecast SubcommitteeAugust 2002

MW GWh


Table A2-3. MEA Purchases and Sales Forecast by Customer Class

Base Case_August 2002 Unit : GWh

Historical Forecast

DESCRIPTION 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

2543 2544 2545 2546 2547 2548 2549 2550 2551 2552 2553 2554 2555 2556 2557 2558 2559

Residential (Total) 6,669 7,355 7,381 7,678 8,057 8,461 8,885 9,353 9,836 10,340 10,851 11,375 11,903 12,443 13,000 13,567 14,148

%increase 3.43 10.29 0.35 4.02 4.94 5.01 5.01 5.27 5.16 5.12 4.94 4.83 4.64 4.54 4.48 4.36 4.28

< 150 kWh per month 435 425 425 431 440 450 460 469 478 486 494 502 510 518 526 533 541

%increase 4.07 -2.30 0.00 1.41 2.09 2.27 2.22 1.96 1.92 1.67 1.65 1.62 1.59 1.57 1.54 1.33 1.50

> 150 kWh per month 6,234 6,930 6,956 7,247 7,617 8,011 8,425 8,884 9,358 9,854 10,357 10,873 11,393 11,925 12,474 13,034 13,607

%increase 3.38 11.16 0.38 4.18 5.11 5.17 5.17 5.45 5.34 5.30 5.10 4.98 4.78 4.67 4.60 4.49 4.40

Small General Service 4,334 4,749 4,848 5,029 5,275 5,529 5,816 6,107 6,408 6,722 7,041 7,367 7,643 7,926 8,217 8,516 8,824

%increase 5.32 9.58 2.08 3.73 4.89 4.82 5.19 5.00 4.93 4.90 4.75 4.63 3.75 3.70 3.67 3.64 3.62

Medium General Service 7,494 7,817 8,024 8,343 8,731 9,147 9,598 10,026 10,450 10,919 11,384 11,852 12,269 12,697 13,135 13,583 14,042

%increase 4.96 4.31 2.65 3.98 4.65 4.76 4.93 4.46 4.23 4.49 4.26 4.11 3.52 3.49 3.45 3.41 3.38

Large General Service 10,247 11,122 11,682 12,296 12,951 13,629 14,309 14,979 15,614 16,337 17,054 17,759 18,376 18,995 19,617 20,241 20,865

%increase 13.00 8.54 5.04 5.26 5.33 5.24 4.99 4.68 4.24 4.63 4.39 4.13 3.47 3.37 3.27 3.18 3.08

Specific Business 1,442 1,517 1,559 1,623 1,705 1,756 1,814 1,869 1,936 1,997 2,058 2,132 2,207 2,284 2,363 2,443 2,524

%increase 5.80 5.20 2.77 4.11 5.05 2.99 3.30 3.03 3.58 3.15 3.05 3.60 3.52 3.49 3.46 3.39 3.32

Government Offices & NPO 1,141 1,134 1,179 1,225 1,279 1,330 1,384 1,440 1,489 1,531 1,574 1,614 1,655 1,697 1,740 1,783 1,826

%increase -16.53 -0.61 3.97 3.90 4.41 3.99 4.06 4.05 3.40 2.82 2.81 2.54 2.54 2.54 2.53 2.47 2.41

Street Lighting 148 153 178 186 195 204 210 215 220 225 229 232 236 240 243 246 250

%increase 4.96 3.38 16.34 4.49 4.84 4.62 2.94 2.38 2.33 2.27 1.78 1.31 1.72 1.69 1.25 1.23 1.63

TOTAL ENERGY SALES 31,475 33,847 34,851 36,380 38,193 40,056 42,016 43,989 45,953 48,071 50,191 52,331 54,289 56,282 58,315 60,379 62,479

%increase 6.18 7.54 2.97 4.39 4.98 4.88 4.89 4.70 4.46 4.61 4.41 4.26 3.74 3.67 3.61 3.54 3.48

ENERGY RECEIVED FROM EGAT 32,889 35,327 36,378 38,015 39,909 41,855 43,904 45,965 48,018 50,231 52,446 54,682 56,729 58,811 60,935 63,092 65,287

%increase 6.32 7.41 2.98 4.50 4.98 4.88 4.90 4.69 4.47 4.61 4.41 4.26 3.74 3.67 3.61 3.54 3.48

PEAK DEMAND (MW) 5,800 6,229 6,418 6,706 7,041 7,385 7,748 8,112 8,475 8,865 9,256 9,652 10,014 10,381 10,757 11,138 11,528

%increase 8.27 7.40 3.03 4.49 5.00 4.89 4.92 4.70 4.47 4.60 4.41 4.28 3.75 3.66 3.62 3.54 3.50

% LOAD FACTOR 64.73 64.74 64.70 64.71 64.70 64.70 64.69 64.68 64.68 64.68 64.68 64.67 64.67 64.67 64.67 64.66 64.65

% LOSS 4.30 4.19 4.20 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30 4.30

0

1

2

2000

0

1

2

1


Table A2-4. PEA Purchases and Sales Forecast by Customer Class

Unit: GWh

Historical FORECAST

DESCRIPTION 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

2543 2544 2545 2546 2547 2548 2549 2550 2551 2552 2553 2554 2555 2556 2557 2558 2559

Residential 12,190 13,602 14,270 15,206 16,257 17,432 18,722 20,092 21,532 23,044 24,633 26,303 28,071 29,946 31,941 34,065 36,327

%increase 4.66 11.59 4.91 6.56 6.91 7.23 7.40 7.32 7.17 7.02 6.90 6.78 6.72 6.68 6.66 6.65 6.64

Small General Service 4,112 4,467 4,662 4,965 5,317 5,711 6,145 6,598 7,072 7,568 8,087 8,632 9,207 9,814 10,458 11,141 11,867

%increase 3.85 8.62 4.37 6.51 7.09 7.41 7.60 7.37 7.18 7.01 6.87 6.74 6.65 6.60 6.56 6.53 6.51

Medium General Service 9,820 10,430 10,737 11,399 12,154 13,028 14,051 15,139 16,276 17,464 18,704 20,000 21,362 22,794 24,307 25,906 27,598

%increase 7.58 6.21 2.94 6.16 6.63 7.19 7.86 7.74 7.51 7.30 7.10 6.93 6.81 6.71 6.64 6.58 6.53

Large General Service * 22,350 23,688 25,595 27,511 29,732 32,171 34,789 37,507 40,529 44,907 48,295 51,589 55,408 59,739 64,215 69,209 74,334

%increase 11.46 5.99 8.05 7.48 8.07 8.20 8.14 7.81 8.06 10.80 7.54 6.82 7.40 7.82 7.49 7.78 7.40

Specific Business 1,311 1,431 1,509 1,614 1,725 1,843 1,973 2,112 2,258 2,412 2,574 2,747 2,929 3,123 3,329 3,547 3,779

%increase 4.91 9.15 5.46 6.98 6.86 6.87 7.07 7.02 6.91 6.82 6.75 6.70 6.65 6.62 6.58 6.56 6.53

Government Offices & NPO 1,970 2,264 2,365 2,547 2,747 2,957 3,179 3,413 3,659 3,917 4,189 4,475 4,777 5,097 5,436 5,796 6,178

%increase 8.79 14.95 4.47 7.70 7.84 7.67 7.50 7.34 7.20 7.06 6.94 6.83 6.75 6.70 6.65 6.62 6.60

Agricultural Pumping 145 179 188 202 216 229 241 254 267 280 294 309 324 339 356 373 391

%increase -22.00 23.48 5.47 7.44 6.60 6.00 5.55 5.22 5.09 5.01 4.95 4.91 4.88 4.86 4.84 4.82 4.80

Temporary 473 414 382 396 413 435 463 498 535 574 615 658 704 753 805 859 916

%increase -5.53 -12.57 -7.72 3.60 4.38 5.30 6.41 7.59 7.41 7.27 7.16 7.08 6.99 6.91 6.82 6.74 6.66

TOTAL SALES 52,370 56,473 59,709 63,840 68,560 73,806 79,564 85,613 92,127 100,165 107,392 114,713 122,783 131,607 140,846 150,896 161,391

%increase 7.91 7.83 5.73 6.92 7.39 7.65 7.80 7.60 7.61 8.73 7.21 6.82 7.03 7.19 7.02 7.14 6.96

Free of Charge 665 643 747 813 880 950 1,023 1,099 1,180 1,266 1,357 1,454 1,557 1,668 1,785 1,909 2,041

%increase 37.23 -3.19 16.14 8.82 8.28 7.91 7.65 7.47 7.35 7.26 7.20 7.16 7.11 7.07 7.02 6.97 6.93

TOTAL CONSUMPTIONS 53,035 57,117 60,456 64,654 69,441 74,756 80,587 86,713 93,307 101,431 108,749 116,167 124,340 133,274 142,631 152,805 163,432

%increase 8.20 7.70 5.85 6.94 7.40 7.65 7.80 7.60 7.60 8.71 7.21 6.82 7.04 7.19 7.02 7.13 6.95

* included standby rate



Table A2-5. Comparison of The August 2002 and January 2004 Forecasts

Year Aug-02 Jan-04 1/ Difference Aug-02 Jan-04 2/ Difference

2004 122,024 126,811 4,787 19,029 19,600 571 2005 130,232 136,784 6,552 20,295 21,143 848 2006 139,000 147,658 8,658 21,648 22,238 590 2007 147,835 158,212 10,377 23,020 23,844 824 2008 157,064 169,280 12,216 24,450 25,548 1,098 2009 168,004 180,942 12,938 26,143 27,352 1,209 2010 178,079 193,530 15,451 27,711 29,308 1,597 2011 188,446 206,674 18,228 29,321 31,344 2,023 2012 199,378 220,253 20,875 31,014 33,445 2,431 2013 211,146 234,672 23,526 32,842 35,673 2,831 2014 223,437 249,843 26,406 34,743 38,015 3,272 2015 236,364 265,788 29,424 36,754 40,478 3,724

Average Annual Growth (%)2004-10 6.5% 7.3% 6.5% 6.9%2010-15 5.8% 6.6% 5.8% 6.7%2004-15 6.2% 7.0% 6.2% 6.8%

1/ Base case assuming medium economic growth (MEG) scenario.2/ Includes "Peak Cut" of 500 MW per year from 2006 (GOT policy).

Emergy Requirement (GWh) Peak Demand (MW)

Fuel Price Assumptions 8 3

A3 Fuel Price Assumptions


Table A3-1. Economic Fuel Prices Adopted for the Study (constant US$2003)

Table A3-2. Commercial Fuel Prices Adopted for the Study (current US$)

Following the tables is an appendix from the World Bank’s Project Apprasal Documentfor NT2 (January 2005) which outlines the methodology employed to develop thenatural gas price projections adopted for the current study.


Table A3-1. Economic Fuel Price Projections (constant US$2003)

Real Economic Prices - Base CaseFiscal Hvy Oil 3.5% Diesel Lignite Import CoalYear Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.55 2.55 2.55 3.39 6.10 1.21 1.54 2004 2.56 2.65 2.55 4.48 8.68 1.20 2.33 2005 2.51 2.60 2.49 4.06 7.88 1.19 2.22 2006 2.41 2.50 2.40 3.58 6.93 1.17 2.00 2007 2.37 2.46 2.36 3.43 6.65 1.15 1.77 2008 2.33 2.42 2.32 3.28 6.37 1.14 1.66 2009 2.31 2.41 2.30 3.26 6.33 1.12 1.54 2010 2.30 2.39 2.29 3.25 6.29 1.11 1.54 2011 2.29 2.38 2.28 3.23 6.26 1.10 1.55 2012 2.28 2.37 2.27 3.24 6.28 1.08 1.56 2013 2.27 2.37 2.27 3.25 6.30 1.06 1.57 2014 2.27 2.36 2.27 3.26 6.32 1.05 1.58

Average Annual Growth (%)2003-2014 -1.1% -0.7% -1.1% -0.4% 0.3% -1.3% 0.2%

Real Economic Prices - Low CaseFiscal Hvy Oil 3.5% Diesel Lignite Import CoalYear Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.32 2.32 2.32 3.00 5.40 1.21 1.24 2004 2.21 2.31 2.20 3.80 7.36 1.20 2.03 2005 2.18 2.27 2.17 3.45 6.68 1.19 1.93 2006 2.11 2.20 2.10 3.03 5.89 1.17 1.75 2007 2.08 2.17 2.06 2.91 5.65 1.15 1.56 2008 2.04 2.14 2.03 2.79 5.41 1.14 1.46 2009 2.03 2.13 2.02 2.77 5.38 1.12 1.36 2010 2.02 2.11 2.01 2.76 5.35 1.11 1.36 2011 2.01 2.10 2.00 2.74 5.32 1.10 1.37 2012 2.00 2.10 1.99 2.75 5.34 1.08 1.38 2013 1.99 2.09 1.99 2.76 5.35 1.06 1.38 2014 1.99 2.08 1.99 2.77 5.37 1.05 1.39

Average Annual Growth (%)2003-2014 -1.4% -1.0% -1.4% -0.7% -0.1% -1.3% 1.1%

Real Economic Prices - High CaseFiscal Hvy Oil 3.5% Diesel Lignite Import CoalYear Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.81 2.81 2.81 3.92 7.04 1.21 1.85 2004 2.95 3.04 2.94 5.17 10.01 1.20 2.63 2005 2.87 2.96 2.86 4.68 9.07 1.19 2.50 2006 2.74 2.84 2.73 4.12 7.98 1.17 2.25 2007 2.69 2.78 2.68 3.95 7.65 1.15 1.99 2008 2.64 2.73 2.63 3.78 7.32 1.14 1.85 2009 2.62 2.72 2.61 3.76 7.28 1.12 1.72 2010 2.61 2.70 2.60 3.73 7.24 1.11 1.71 2011 2.59 2.69 2.58 3.71 7.20 1.10 1.73 2012 2.59 2.68 2.58 3.73 7.22 1.08 1.74 2013 2.58 2.67 2.58 3.74 7.25 1.06 1.75 2014 2.57 2.67 2.57 3.75 7.27 1.05 1.76

Average Annual Growth (%)2003-2014 -0.8% -0.5% -0.8% -0.4% 0.3% -1.3% -0.5%

1/ Assumed fuel heat content: - Natural Gas: 1,000 Mbtu/MCuF - Heavy Oil 3.5%: 38,886 Mbtu/MLtr - Diesel: 36,307 Mbtu/MLtr - Lignite: 10,912 Mbtu/kTon - Imported Coal: 26,467 Mbtu/kTon





Table A3-2. Commercial Fuel Price Projections (current US$)

Nominal Commercial Prices - Base CaseFiscal Hvy Oil 3.5% Diesel Lignite Import CoalYear Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.95 2.95 2.95 3.56 8.54 1.21 1.56 2004 3.63 3.63 3.63 5.11 11.43 1.20 2.49 2005 3.48 3.48 3.48 4.57 10.46 1.20 2.34 2006 3.34 3.34 3.34 4.02 9.48 1.19 2.11 2007 3.32 3.30 3.32 3.89 9.25 1.19 1.89 2008 3.30 3.30 3.30 3.76 9.01 1.19 1.78 2009 3.32 3.34 3.32 3.77 9.02 1.18 1.67 2010 3.34 3.37 3.33 3.77 9.04 1.19 1.67 2011 3.36 3.38 3.34 3.78 9.05 1.19 1.69 2012 3.38 3.42 3.37 3.82 9.12 1.18 1.72 2013 3.40 3.46 3.39 3.86 9.20 1.18 1.74 2014 3.42 3.50 3.41 3.90 9.27 1.18 1.76


Nominal Commercial Prices - Low CaseFiscal Hvy Oil 3.5% Diesel Lignite Import CoalYear Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 2.75 2.75 2.75 3.15 7.55 1.21 1.25 2004 3.29 3.29 3.29 4.33 10.02 1.20 2.17 2005 3.18 3.18 3.18 3.87 9.21 1.20 2.03 2006 3.07 3.07 3.07 3.41 8.39 1.19 1.84 2007 3.05 3.03 3.05 3.30 8.19 1.19 1.66 2008 3.04 3.04 3.04 3.19 8.00 1.19 1.56 2009 3.06 3.07 3.06 3.20 8.01 1.18 1.47 2010 3.08 3.11 3.07 3.20 8.02 1.19 1.48 2011 3.10 3.12 3.08 3.21 8.03 1.19 1.50 2012 3.12 3.16 3.10 3.25 8.10 1.18 1.52 2013 3.14 3.20 3.12 3.28 8.16 1.18 1.54 2014 3.16 3.24 3.14 3.32 8.23 1.18 1.56


Nominal Commercial Prices - High CaseFiscal Hvy Oil 3.5% Diesel Lignite Import CoalYear Base Demand Low Demand High Demand USD/mmBtu USD/mmBtu USD/mmBtu USD/mmBtu2003 3.19 3.19 3.19 4.11 9.85 1.21 1.87 2004 3.97 3.97 3.97 5.90 12.83 1.20 2.82 2005 3.80 3.80 3.80 5.27 11.70 1.20 2.64 2006 3.63 3.63 3.63 4.63 10.58 1.19 2.37 2007 3.60 3.58 3.60 4.48 10.30 1.19 2.11 2008 3.58 3.57 3.57 4.33 10.03 1.19 1.99 2009 3.60 3.61 3.59 4.33 10.04 1.18 1.86 2010 3.62 3.64 3.61 4.34 10.05 1.19 1.86 2011 3.63 3.65 3.62 4.34 10.06 1.19 1.89 2012 3.66 3.70 3.64 4.39 10.15 1.18 1.91 2013 3.68 3.74 3.67 4.44 10.23 1.18 1.94 2014 3.70 3.78 3.69 4.48 10.32 1.18 1.97






Natural Gas Valuation

An important component of the economic due diligence on the NT2 project is todetermine whether NT2 is cost-effective for the Thai power system, as the project’sprimary purpose and underlying bankability relates to the Thai power market. Thiscost-effectiveness is assessed by evaluating whether the project is least-cost for theduty-service envisaged. One of the most important determining factors is the value ofnatural gas that would be used in combined cycle gas turbines, as these are the mostlikely economic alternative to NT2.

The long-term supply and demand outlook for natural gas, and its opportunity costwhether as an export or import commodity are key factors determining theappropriate principles for calculating its economic value. The industry has grownconsiderably and the long-term supply: demand picture has evolved over the pastseveral decades. As well, because of the commercial interests at stake between buyersand sellers, competition for the market between sellers, the real uncertainty aboutfuture demand and supply conditions and the complexity of the contractingarrangements, this is an industry that doles out information very cautiously. Theinsights leading to the valuations presented in this note rely for the most part onverbally communicated confidential information from players active in the industry,some power sector documentation and some relevant oil price projections providedby the World Bank. While this is not the optimal basis for the purpose at hand, it wassufficient for developing reasonable valuations.

This note develops the value series in the following steps:

1. Principles of commodity valuation;2. Evidence of long term supply and demand for natural gas in Thailand;3. Comments on the market structure;4. Implications of (2) and (3) for the approach to valuation;5. Insights about economic value from contracting principles (GPAs) in Thailand;6. Calculations and projections (Base, low and high gas value cases).

Natural gas may be valued at its economic resource costs of finding, developing,producing (EDP) and transporting the commodity (supply cost basis), or at itsopportunity value as an export commodity or import requirement (border pricebasis). It may also be appropriate to include a depletion premium (also called a “usercost”). This reflects the possibility that an increased current use of the resourceaccelerates the time path to depletion, at which point a “backstop” price would bepaid for the commodity that replaces it.

The supply cost basis is appropriate where the potential supply of natural gas is verylarge relative to the market, with little likelihood over an economically meaningful timeperiod that foregone economic export potential or heavy domestic use would triggerborder prices as the key determinant of economic value. Save for these circumstances,border prices, or a combination of supply cost and depletion premium based onexpected border prices should be the valuation basis. Which to use is informed by thedata.


Economic supply costs are the real costs incurred over time of finding, developing,producing and transporting the commodity, net of taxes and royalties. Border pricesare projected real f.o.b netbacks to the wellhead in respect of forgone exports, or c.i.fimport values in respect of imported gas, net of taxes and royalties. The user cost is aprice signal that tells consumers the present value consequences of an increase in theiruse of an exhaustible resource. It compensates the resource owner who may choosewhether to leave the resource in the ground for future appreciation or produce itsooner. The calculation of a user cost requires knowing the time path to depletion,the shape of the marginal cost curves with and without the incremental consumptionover that time and the likely cost of the backstop at depletion time. The moreuncertain the basis of the supply, demand and cost projections, the lower theexpected backstop value, the further off the expected depletion time and the flatterthe marginal cost curves, the less the attention that should be focused on user costs.All of these factors indicate that user costs would be very difficult to compute withconfidence for Thailand.

On the whole, the industry is optimistic about both the resource base and demandgrowth. Evidence of this optimism is these companies’ continued commitment ofresources to exploration and development as needed, the creation of long term jointarrangements between countries sharing resources in the Gulf of Thailand52, and a 2.4billion dollar pipeline from the Gulf to the mainland (target of 2006). Existingtransportation capacity is nearing saturation. The new line will almost double existingtransportation capacity. This capacity should be fully utilized by 2015, based onprojected demand growth of about 6% per year.

The R/P ratio is now about 20. This is higher than the industry typically considersideal, and is partly the result of conservatively regulated reservoir depletion rates, aswell as strenuous effort to expand the industry over the past two decades. Given thiscomfortable supply position, the market will pace reserves additions; however therewill be a rush between companies to reserve capacity in the new pipeline. This meansdeveloping new GPAs over the next few years and proving-up the necessary reservesas required.

The industry views demand as driving new contracts. Producers use demand forecastsfrom PTT and EGAT to do their E&P planning. Hence supply will evolve to meetgrowing demand.

Several sources say that supply costs have declined dramatically over the past twentyyears with major advances in exploration and drilling technology. The latter isespecially important for the Gulf of Thailand, which is geologically fractured. Theysuggest that future E&P costs should decrease very gradually in well-known areas, butcosts could increase due to more difficult production conditions and higher CO2

content of the gas in certain other off shore areas. It is not clear whether to believethat aggregate supply costs in the future will remain about the same, increasemoderately or decrease moderately. The supply from Myanmar is priced about 50%higher than that from Thailand, and has a 30% share in the market. This share varies

52 These include the Myanmar Thailand joint area and the Thai Kampuchea overlap – there is adispute about resource sharing between the latter.


from period to period, its value being uncertain over the long term it could decrease,increase or remain about the same, depending upon negotiations.

Regarding demand, the power sector absorbs about 80% of consumption and theindustrial sector the other 20%. The electricity vs. other industry share is likely to besustained in a range of 70% to 80%. Assuming that power sector and industrialdemand continue to grow at 6% per year over the long term, gas supply will beproduced from known areas for many years to come, providing a reference point forpricing; but beyond 2014/2015, imported gas or as-yet undiscovered Thai gas will berelied upon increasingly to complement the supply requirement at marginal costs thatare not now known.

The basic market structure is one of monopoly buyer and competition betweensellers. The majors are UNOCAL, TotalElfFina, PTT (now privatized) and Mitsui, withAmarada Hess and Chevron growing quickly. There are several other companies witha smaller presence in the E&P business. Stiff downward pressure on prices is exercisedby a vigilant public, vigilant government and the monopoly buyer (PTT) having awindow on the producing industry through its own E&P subsidiary. Several industryplayers assert that the producers do not cohere, they are not coordinated, and theyare vying with each other for market share.

The predominant transaction form is long-term contracts covering the life of aconcession, with regulated depletion rates (1 in 6000) to prevent reserves lossthrough accelerated depletion. Each concession has its own particular cost structureand gas quality; hence the detailed contract terms vary from contract to contract.However, there is a general pricing structure common to most contracts.

The following factors distilled from the foregoing discussion seem most pertinent tothe choice of valuation approach:

i. there is apparent comfort in respect of long-term supply from domestic reservesand the MTJDA, with no issue of export opportunity cost;

ii. a minority share of gas comes from Myanmar, it being expected that this sharewill vary moderately over time; the time period to depletion – if it ever happens– is far off; backstop values could be determined by imported LNG, more as yetundiscovered Thai gas or imports from neighboring countries – all at costs thatare not now known;

iii. there are competitive pressures characterizing the contracting process, suchthat the terms of the contracts can be said to reflect a market-based valuationof the cost recovery and remuneration levels needed to keep the producers inoperation;

iv. in general, there is uncertainty about the size of future reserves additions andtheir incremental costs, the predominant view in the industry being optimistic onsupply and rather unclear about whether marginal cost will increase moderatelyor decrease moderately.

Under these conditions, it seems most appropriate to base the economic value ofnatural gas on:


i. the cost of discovery, development and production for local supply as evidencedin current pool pricing;

ii. border price for the Myanmar supply, iii. removal of taxes and royalties from domestic production, iv. addition of the PTT marketing margin and v. valuation of gas transmission on a postage stamp basis including only the

estimated recurrent operating costs of the transmission network, insofar as thecapital costs of the existing infrastructure and the third line now underconstruction are sunk costs).

Because each GPA differs and we do not have access to the individual contracts, itwas necessary to create a “typical contract” the key elements of which industryinterviewees claimed to be representative of the average.

The basic pricing structure, valid for the duration of the contract, is as follows. In thecontracts, the current gas price payable to producers is specified in THB. It is theresult of applying a series of indices (contained in one formula) to a base price.

The indexation formula applied to the Base Price reflects changes in: (i) the fob priceof 3.5%S HFO Singapore, (ii) a petroleum industry machinery inflation index reflectingUSD inflation, (iii) the Thai CPI reflecting Thai domestic inflation, (iv) an exchangerate adjuster and (v) a constant. Given that our numeraire in this project analysis isUSD, the machinery index, the Thai CPI index and the exchange rate adjuster wouldbe offsetting in future price projections using the PPP method of exchange rateprojection. When working in USD prices rather than THB prices, the only necessaryelement of the index is the HFO adjuster, having a weight of about 30% in the index.PTT charges EGAT and IPPs a marketing margin of 1.75%. In the economic valuationPTT's tolls are replaced with an estimated incremental recurrent operating cost oftransmission services.

The pen-ultimate step for moving from commercial value to economic value is toremove transfers from the commercial price, these being royalties and taxes. Theroyalty rate for new reserves is 12.5% of the producers’ selling price. The actualamount of income tax producers pay in total or per mmbtu of gas sold cannot beknown without access to company accounts, and we have no such access. Anapproximation of the income tax load is made by taking the difference between theprojected producer selling price net of royalties from the foregoing steps, deducting anadvised producer EDP cost, the residual being gross profit, of which 50% is deductedin taxes. These deductions of income taxes and royalties are made only for the Thaiportion of gas supply, because Myanmar is beyond the welfare boundary of theanalysis. At the welfare boundary Thailand faces a border price, and any embeddedtaxes and royalties going to the Government of Myanmar are included in economiccosts facing Thailand, therefore not deducted.

The final calculation is to convert the nominal economic natural gas values into realvalues by deflating the nominal series with the MUV index. This is the index theWorld Bank uses for converting hydrocarbon prices between real and nominal values.


Low and High Value Projections: The gas value projections for the low andhigh cases consist of two changes to the base case presented above:

Firstly, the values of HFO to be used in the price adjustment index are recalculatedusing high and low price projections for the World Bank Crude Mix. The high and lowprice projections are calculated on the basis of one standard deviation from the baseprice projection.

Secondly, the Myanmar share is decreased or increased moderately in the low andhigh price projections respectively, according to the range of conceivable Myanmarshare mentioned by industry participants.

Thus, the low price trajectory reflects the combined impact of a lower valuedinternational hydrocarbon market along with a more plentiful outlook for Thai supplyat no increase in marginal cost, hence less involvement of costlier Myanmar bordervalues, while the high trajectory reflects the reverse. We believe that the range socreated accounts for the two key uncertainties going forward: (i) the future value ofworld oil, and (ii) the degree of future Thai exposure to (costlier) imported naturalgas.

The valuation methodology described above was calibrated to 2004 actualcommercial values (i.e. excluding adjustments from commercial to economic value), inorder to have an accurate basis upon which to project both commercial andeconomic values based on the assumptions discussed above.

The commercial values of natural gas for the commercial analysis includes taxes androyalties and they include actual or anticipated pipeline tolls with capital charges.

There is some sensitivity of the gas prices to the electricity demand forecast, mainlybecause changes in volumes affect unit transmission costs.

The natural gas price projections extend from 2004 to 2014, being the final year ofelectric power system expansion modeled in the least-cost analysis. For the end effectsperiod 2014-2034, in the economic analysis the value achieved by 2014 is sustained inreal terms; for the commercial analysis, which is conducted in nominal values, from2014 the price of natural gas is inflated by 1.23 percent per year. This reflects ajudgment that international background inflation will be no less than this value, and itmaintains the inflation of the natural gas price in step with the inflation of NT2's tariffin the PPA. Of course, if the commercial value of natural gas were to increase at higherrates, this would make NT2 more advantageous. The assumptions used in theseprojections are modest.

The year to year projected natural gas prices used in the cost risk analysis are asfollows:


Table 7.3 Economic values of Natural Gas – Thailand

Year Base Val Low Val High Val Base Val Low Val High Val Base Val Low Val High Val2003 2.39 2.27 2.63 2.49 2.16 2.73 2.38 2.05 2.622004 2.42 2.09 2.79 2.52 2.19 2.88 2.41 2.08 2.782005 2.37 2.06 2.71 2.46 2.15 2.81 2.36 2.05 2.702006 2.28 1.99 2.59 2.37 2.09 2.69 2.27 1.98 2.582007 2.24 1.96 2.54 2.33 2.06 2.64 2.23 1.95 2.532008 2.20 1.93 2.49 2.30 2.03 2.59 2.19 1.92 2.482009 2.19 1.92 2.48 2.28 2.02 2.57 2.18 1.91 2.472010 2.18 1.91 2.47 2.27 2.01 2.56 2.17 1.90 2.462011 2.16 1.90 2.45 2.26 2.00 2.55 2.15 1.89 2.442012 2.16 1.89 2.45 2.25 1.99 2.54 2.15 1.88 2.432013 2.15 1.89 2.44 2.24 1.98 2.53 2.15 1.89 2.442014 2.14 1.88 2.43 2.24 1.97 2.53 2.14 1.88 2.43

ECONOMIC VALUESBase Demand Low Demand High Demand

Base Pr Low Pr High Pr Base Pr Low Pr High Pr Base Pr Low Pr High Pr3.37 3.25 3.54 3.37 3.05 3.54 3.37 3.05 3.543.63 3.29 3.97 3.63 3.29 3.97 3.63 3.29 3.973.48 3.18 3.80 3.48 3.18 3.80 3.48 3.18 3.803.34 3.07 3.63 3.34 3.07 3.63 3.34 3.07 3.633.32 3.05 3.60 3.30 3.03 3.58 3.32 3.05 3.603.33 3.07 3.60 3.33 3.07 3.60 3.32 3.06 3.603.35 3.09 3.62 3.36 3.10 3.64 3.34 3.08 3.613.36 3.10 3.64 3.40 3.13 3.67 3.35 3.09 3.633.38 3.12 3.65 3.41 3.14 3.68 3.36 3.10 3.643.40 3.14 3.67 3.45 3.18 3.72 3.38 3.12 3.663.42 3.16 3.70 3.49 3.22 3.76 3.41 3.14 3.683.44 3.17 3.72 3.53 3.26 3.81 3.42 3.16 3.70

COMMERCIAL PRICESBase Demand Low Demand High Demand

Year200320042005200620072008200920102011201220132014

Detailed Plant Data (Existing System) 9 3

A4 Detailed Plant Data (Existing System)


Table A4-1. Existing Installed Generating Capacity (as of Sep-03)

Table A4-2. Existing Hydro Power Plant Data

Table A4-3. Existing and Committed Small Power Producers (as of Sep-03)

Table A4-4. Schedule of Planned Power Plant Retirements


Table A4-1. Existing Installed Generating Capacity (as of Sep-03)

Plant Type Fuel Installed Capacity Total CapacityType (MW) (MW)

A. Hydroelectric Plant -Bhumibol - (6x82.2)+115+171 779.2Sirikit - 4x125 500.0Ubolratana - 3x8.4 25.2Sirindhorn - 3x12 36.0Chulabhorn - 2x20 40.0Kaeng Krachan - 1x17.5 17.5Nam Pung - 2x3 6.0Srinagarind - (3x120)+(2x180) 720.0Bang Lang - 3x24 72.0Tha Thung Na - 2x19 38.0Vajiralongkorn - 3x100 300.0Pak Mun - 4x34 136.0Huai Kum - 1x1.06 1.1Ban Santi - 1x1.275 1.3Mae Ngat - 2x4.5 9.0Rajjaprabha - 3x80 240.0Miscellaneous - 0.429 0.4

Total 2,921.7B. Thermal Power Plant

South Bangkok Oil/Gas (2x200)+(3x310) 1,330.0Mae Moh Lignite (3x75)+(4x150)+(6x300) 2,625.0Bang Pakong Oil/Gas (2x550)+(2x600) 2,300.0

Total 6,255.0C. Combined Cycle Power Plant

Bang Pakong Block 1-2 Gas 2x[(4x60.7)+(137.5)] 760.6Block 3-4 Gas 2x[(2x104)+(1x99)] 614.0

Nam Phong Block 1-2 Gas 2x[(2x121)+(1x113)] 710.0South Bangkok Block 1 Gas (2x110)+(1x115) 335.0

Block 2 Gas (2x202)+(1x220) 624.0Wang Noi Block 1-2 Gas 2x[(2x223)+(1x205)] 1,302.0

Block 3 Gas (2x236)+(1x257) 729.0Total 5,074.6

D. Gas Turbine Power PlantLan Krabu Gas (4x14)+(2x16)+(4x20) 168.0Nong Chok 1-2 Diesel 3x122 366.0Surat Thani Gas 2x122 244.0

Total 778.0E. Diesel

Mae Hong Son Diesel 1x6 6.0Total 6.0

F. Renewable Energy SourceTotal 0.534 0.5

G. Purchased PowerKhanom Thermal Oil/Gas 2x75 150.0Khanom CC Gas (4x112)+(1x226) 674.0Rayong CC Block 1-4 Gas 4x[(2x103)+(1x102)] 1,232.0Ratchaburi Thermal Gas 2x720 1,440.0Ratchaburi CC Block 1-3 Gas 3x[(2x230)+(1x265)] 2,175.0Tri Energy Gas (2x224)+(1x252) 700.0Independent Power Gas (2x230)+(1x240) 700.0Bo Win Power Gas (2x356.5) 713.0Eastern Power&Electric Gas 350 350.0SPP - 1837.2 1,837.2Theun Hinboun Hydro - 2x115 214.0Houay Ho Hydro - 2x75 126.0EGAT-TNB Tie Line - 300 300.0

Total 10,611.2Grand Total 25,647.0

Note: FY2003 installed capacity reported in the Study is based on mid-year estimates, and therefore varies slightly from the actual end-year data reported above; differences generally relate to SPP scheduling.


Table A4-2. Existing Hydro Power Plant Data

Power Plant Est. Life Commission(years) Date Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Total

I Bang Lang #1-3 50 Jul-81 MW 57.0 60.4 66.0 66.8 63.7 60.3 60.7 60.6 61.3 60.5 58.0 57.0 MWh 8,930 8,640 8,930 15,490 12,260 12,240 8,640 8,930 8,640 8,930 8,640 8,930 119,200 monthly share 0.075 0.072 0.075 0.130 0.103 0.103 0.072 0.075 0.072 0.075 0.072 0.075

2 Rajjaprabha #1-3 50 May-87 MW 196.9 198.1 196.2 190.2 182.1 173.2 179.6 170.9 163.3 165.9 178.3 190.9 MWh 29,800 28,800 29,800 29,800 26,900 29,800 28,800 29,800 28,800 29,800 29,800 28,800 350,700 monthly share 0.085 0.082 0.085 0.085 0.077 0.085 0.082 0.085 0.082 0.085 0.085 0.082

3 Bhumibol #1-8 50 May-64 MW 557.1 508.4 512.6 492.0 487.3 418.7 470.9 561.6 553.3 510.3 562.5 559.6 MWh 62,540 55,500 59,540 95,440 123,930 140,060 181,320 70,400 67,480 72,150 69,930 63,630 1,061,920 monthly share 0.059 0.052 0.056 0.090 0.117 0.132 0.171 0.066 0.064 0.068 0.066 0.060

4 SirJkit #1-4 50 Mar-74 MW 436.4 394.1 400.6 383.6 361.0 314.5 340.5 339.2 351.5 346.7 389.3 424.6 MWh 37,200 36,000 37,200 68,200 93,600 117,600 88,600 37,000 35,900 45,000 37,200 36,000 669,500 monthly share 0.056 0.054 0.056 0.102 0.140 0.176 0.132 0.055 0.054 0.067 0.056 0.054

5 Ubolratana #1-3 50 Mar-66 MW 20.4 21.2 21.0 20.7 19.8 18.3 17.0 16.9 16.7 16.6 16.2 18.5 MWh 4,290 1,130 10 860 3,180 4,410 3,860 970 10 1,610 2,960 3,130 26,420 monthly share 0.162 0.043 0.000 0.033 0.120 0.167 0.146 0.037 0.000 0.061 0.112 0.118

6 Chulabhorn #1-2 50 Oct-72 MW 40.0 40.0 40.0 39.9 40.0 40.0 40.0 40.0 39.6 39.9 40.0 40.0 MWh 4,980 4,820 4,980 4,980 4,500 4,980 4,820 4,980 4,820 4,980 4,980 4,820 58,640 monthly share 0.085 0.082 0.085 0.085 0.077 0.085 0.082 0.085 0.082 0.085 0.085 0.082

7 Sirindhorn #1-3 50 Nov-72 MW 36.0 36.0 36.0 35.6 34.7 33.6 32.7 32.1 32.2 32.4 33.4 35.6 MWh 4,460 4,320 4,460 4,460 4,030 4,460 4,320 4,460 4,320 4,460 4,460 4,300 52,510 monthly share 0.085 0.082 0.085 0.085 0.077 0.085 0.082 0.085 0.082 0.085 0.085 0.082

8 Kang Krachan #1 60 Aug-74 MW 13.9 13.9 14.7 14.5 14.3 13.6 13.2 13.0 12.6 12.0 11.0 11.3 MWh 2,600 4,890 2,600 3,000 3,750 2,650 2,520 3,050 8,640 8,260 8,340 6,330 56,630 monthly share 0.046 0.086 0.046 0.053 0.066 0.047 0.044 0.054 0.153 0.146 0.147 0.112

9 Nam Pung #1-3 50 Oct-65 MW 5.8 5.8 5.8 5.7 5.7 5.6 5.6 5.5 5.5 5.6 5.6 5.7 MWh 1,190 1,150 740 740 670 740 720 740 720 740 1,190 720 10,060 monthly share 0.118 0.114 0.074 0.074 0.067 0.074 0.072 0.074 0.072 0.074 0.118 0.072

10 Vachiralongkorn #1-3 50 Feb-85 MW 230.3 234.3 232.5 229.0 222.7 213.0 203.6 195.3 190.7 192.2 201.4 217.6 (Khao Laem) MWh 29,800 28,800 29,800 29,800 59,200 58,900 37,100 36,000 39,300 38,100 44,600 28,800 460,200

monthly share 0.065 0.063 0.065 0.065 0.129 0.128 0.081 0.078 0.085 0.083 0.097 0.063 11 Srinagarind #1-5 50 Feb-80 MW 675.0 682.2 683.4 681.3 677.9 359.1 358.2 351.3 347.2 346.0 346.5 352.4

MWh 74,000 72,200 74,600 75,100 66,800 98,500 97,600 101,400 71,600 74,500 74,400 72,700 953,400 monthly share 0.078 0.076 0.078 0.079 0.070 0.103 0.102 0.106 0.075 0.078 0.078 0.076

12 Tha Thung Na #1-2 50 Dec-82 MW 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 38.0 MWh 4,700 4,530 6,420 10,670 11,280 14,790 17,000 4,700 4,500 6,600 4,800 4,500 94,490 monthly share 0.050 0.048 0.068 0.113 0.119 0.157 0.180 0.050 0.048 0.070 0.051 0.048

13 Mae Ngat #1-2 50 Oct-85 MW 1.6 1.1 2.7 7.6 7.3 3.9 1.0 - - - - 2.7 MWh 1,100 540 1,810 5,530 5,530 2,490 540 - - - - 1,810 19,350 monthly share 0.057 0.028 0.094 0.286 0.286 0.129 0.028 - - - - 0.094

14 Pak Mun #1-4 50 Oct-94 MW 100.0 108.0 93.2 59.6 56.8 60.0 67.2 97.6 89.6 112.4 97.2 66.4 MWh 49,200 32,000 14,000 7,600 6,400 7,600 8,400 11,600 21,200 32,000 26,800 34,400 251,200 monthly share 0.196 0.127 0.056 0.030 0.025 0.030 0.033 0.046 0.084 0.127 0.107 0.137

15 Ban Yang+Huai Kum+ 50 Feb-74 MW 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 2.9 Ban Khun Klang MWh 1,299 1027 977 1064 891 829 718 779 928 1225 1188 1448 12,373

monthly share 0.105 0.083 0.079 0.086 0.072 0.067 0.058 0.063 0.075 0.099 0.096 0.117 16 Khirtharn #1-2 50 Oct-86 MW 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2 12.2

MWh 2,020 1910 1920 1940 1780 1930 1850 1890 1880 1960 2000 1940 23,020 monthly share 0.088 0.083 0.083 0.084 0.077 0.084 0.080 0.082 0.082 0.085 0.087 0.084

Total Dependable Capacity 1/ MW 2,411 2,344 2,346 2,267 2,214 1,755 1,831 1,925 1,904 1,881 1,980 2,023 Total Generation 1/ MWh 316,089 284,347 275,867 352,734 422,921 500,049 484,958 314,809 296,858 328,355 319,288 300,318 4,219,613

monthly share 0.075 0.067 0.065 0.084 0.100 0.119 0.115 0.075 0.070 0.078 0.076 0.071

1/ Excluding Khiritharn, which is non-firm (under Irrigation Department control).

Monthly Dependable Hydro Capacity (MW) and Energy (MWh)


Table A4-3. Existing and Committed Small Power Producers (as of Sep-03)

Power Plant Location

Type of Fuel

Date of Purchase 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006

1 Glow SPP Public Co.,Ltd (1) Rayong Gas 1 Apr. 96 902 Glow SPP Public Co.,Ltd (2) Rayong Gas 1 Oct. 96 903 TPT Utility Co.,Ltd Rayong Coal 1 Feb. 97 104 National Petrochemical Public Co.,Ltd Rayong Gas 1 Apr. 97 325 Glow SPP 1 Co.,Ltd (1) Rayong Gas 3 Feb. 98 556 Thai Oil Power Co.,Ltd. Chon Buri Gas 1 Apr. 98 417 Defence Energy Chiang Mai Heavy Oil 26 Jun. 98 98 Gulf Cogeneration Co.,Ltd Sara Buri Gas 3 Sep. 98 909 Amata-EGCO Power Co.,Ltd Chon Buri Gas 17 Sep. 98 90

10 Glow SPP 1 Co.,Ltd (2) Rayong Gas 18 Sep. 98 5511 Bangkok Cogeneration Co.,Ltd Rayong Gas 4 Feb. 99 9012 National Power Supply Co.,Ltd (1) Pra Chin Buri Coal 12 Mar. 99 9013 Glow SPP 2 Co.,Ltd (1) Rayong Gas 29 Mar. 99 6014 Saha Cogen (Chon Buri) Co.,Ltd Chon Buri Gas 19 Apr. 99 9015 Thai Power Supply Co.,Ltd (1) Cha Choeng Sao Rice Husk 21 Apr. 99 2516 Glow SPP 2 Co.,Ltd (2) Rayong Gas 26 Apr. 99 6017 Thai Power Supply Co.,Ltd (2) Cha Choeng Sao Rice Husk 7 May. 99 6.418 Rojana Power Co.,Ltd Ayutthaya Gas 26 May. 99 9019 National Power Supply Co.,Ltd (2) Pra Chin Buri Coal 12 Jul. 99 9020 Samutprakarn Cogeneration Co.,Lld Samut Prakarn Gas 23 Aug. 99 9021 Glow SPP 3 Co.,Ltd (1) Rayong Coal 1 Sep. 99 9022 Glow SPP 3 Co.,Ltd (2) Rayong Coal 20 Mar. 00 9023 Thai National Power Co.,Ltd Rayong Gas 4 Oct. 00 9024 Nong Khae Cogeneration Co.,Ltd Sara Buri Gas 12 Oct. 00 9025 Laem Chabang Power Co.,Ltd Chon Buri Gas 16 Jul. 01 6026 Bio-Mass Power Co.,Ltd Chainat Rice Husk 9 Sep. 01 527 Amata Power Co.,Ltd Chon Buri Gas 28 Sep. 01 9028 T.L.P. Cogeneration Co.,Ltd Rayong Gas 28 Jan. 03 6029 Roi Et Green Co.,Ltd Roiet Rice Husk 29 May. 03 8.830 Siam Power Co.,Ltd Rayong Gas 1 Jan 06 6031 Gulf Electric Public Co.,Ltd (Yala) Yala Wood Chip 1 Jun 04 20.232 Country Electric Co.,Ltd Lopburi Rice Husk - 1533 Mitr Phol Sugar Corp.,Ltd Suphan Buri Bagasse/Wood - 2534 Gulf Electric Public Co.,Ltd (Trang) Trang Wd Chp Plm Shll - 20.235 A.A. Pulp Mill (2) Co.,Ltd Pra Chin Buri Black Liquor - 2536 Advance Agro Public Co.,Ltd Chon Buri Rice Hsk Wd Chp - 5037 Korach Industry Co.,Ltd Nakhon Ratchasima Bagasse - 838 United Farmer& Industry Co.,Ltd Chaiyaphum Bagasse/wood - 2939 A.T. Bio Power Co.,Ltd Phichit Rice Husk - 2040 Mitr Kalasin Sugar Co.,Ltd Kalasin Bagasse - 841 Thai Power Supply Co.,Ltd (3) Cha Choeng Sao Rice Hsk Wd Chp - 2

Total -Gas 90 212 543 1,023 1,023 1,353 1,353 1,413 1,413 1,473 1,473

-Coal 0 10 10 280 370 370 370 370 370 370 370

-Heavy Oil 0 0 9 9 9 9 9 9 9 9 90 0 0 31 31 36 36 45 45 45 268

Grand Total 90 222 562 1,343 1,433 1,768 1,768 1,837 1,837 1,897 2,120

Note: The Study, based on mid-year estimates, assumes somewhat different SPP additions than the most recent assumptions reported above: 128.9 MW in FY2003, 60 MW in FY2004, 80 MW in FY2005, and none thereafter.

-Renewable energy

Small Producers Project


Table A4-4. Schedule of Planned Plant Retirements

Power Plant Rating Year(s) of Year of Planned Life(MW) Commissioning Retirement (Years)

Thermal PlantSouth Bangkok #1 200 1970 2006 36

#2 200 1971 2007 36#3 310 1974 2009 35 1/#4 310 1975 2010 35 1/#5 310 1977 2012 35 1/

Mae Moh #4-5 2x150 1984 2014 30 1/#6-7 2x150 1985 2015 30 1/#8 300 1989 2018 30#9 300 1990 2019 30#10-11 2x300 1991 2021 30#12 300 1995 2024 30#13 300 1995 2025 30

Khanom PPB #1 75 1981 2007 26 2/#2 75 1989 2007 18 2/

Bang Pakong #1 550 1983 2013 30 1/#2 550 1984 2014 30 1/#3-4 2x600 1992 2021 30

Ratchaburi TH #1-2 2x720 2000 2025 25Krabi #1 300 2003 2033 30

Combined Cycle PlantBang Pakong Block #1 380 1980-82 2008 26

#2 380 1981-83 2009 26#3 307 1990-92 2015 25#4 307 1990-92 2016 25

Rayong Block #1-2 308 1990-92 2011 20 1/#3 308 1991-92 2012 20 1/#4 308 1992-93 2013 20 1/

Nam Pong Block #1 355 1990-92 2017 25#2 355 1993-94 2019 25

South Bangkok #1 335 1993-94 2014 25#2 623 1996-97 2017 25

Wang Noi #1 651 1996-97 2023 25#2 651 1996-97 2023 25#3 729 1997-98 2023 25

Ratchaburi CC #1-2 2x725 2002 2022 25#3 725 2002 2023 25

Gas Turbine PlantLan Krabu 2x16+2x14 1969-70 Depending on gas availabilityLan Krabu 4x20 1981 Depending on gas availabilityNong Chok 3x122 1995 2016 21Surat 2x122 2001 2016 15

1/ Candidates for reconditioning. 2/ Retirement advanced due to planned availability of lower cost resources in South.

How PROSCREEN Works 9 9

A5 How PROSCREEN Works

PROSCREEN selects the least-cost plan by identifying the expansion scenario withthe lowest present value over a user-specified period (the “objective function”). Toachieve this objective requires a user manual over a foot thick and model inputspecification of several hundred pages. While it is beyond the scope of the currentstudy to explain these details, the following paragraphs attempt to describe themethodology in layman’s terms.

PROSCREEN divides the “Study Period” into two parts:

the “Planning Period”, defined for the current study as FY2003-14, inwhich decisions regarding system operation and expansion are analyzedannually and sub-annually (i.e., for user-defined seasons). The duration ofthe Planning Period has been selected based on preliminary model runsindicating (i) that NT2 is a least-cost addition to the Base Case expansionplan as of October 2009 (FY2010), and (ii) that NT2 would be fullyabsorbed into the regional power system by that date under the Lowdemand forecast (see Chapter 2).

The “End Effects Period” in which sophisticated programming techniquesanalyze differences between alternatives (e.g., due to different lives andoperating characteristics) beyond the Planning Period horizon. Withoutend effects analysis, results would be biased against commissioning capital-intensive units near the end of the planning period.

The objective function for our analysis is based on the Study Period, which representsthe sum of both the Planning Period and End-Effects Period results.

Production Costing and System Dispatch

The production costing procedure used by PROSCREEN has two stages. In the firststage, operation of hydro generation, transactions (i.e., IPP purchases), and economicoperation of pumped storage is simulated. The result of this first stage is the seasonalthermal load duration curve. In the second stage, the expected operation of thethermal units within the year is simulated based on a probabilistic technique. Theresults are production costs and the associated level of reliability.

Dispatch of non-thermal resources. Resources are dispatched to meet systemload (modeled as typical weekly load shapes) without regard to cost in thefollowing order:

Transactions (e.g. contract purchases) are dispatched eitheraccording to an hourly profile or designated shape (e.g., peak-

How PROSCREEN Works 1 0 0

shaving, valley-filling, etc.). Although many SPPs are thermal, they areall treated as must-run transactions.

Hydro generation is dispatched simply as monthly generation whichcontributes to meeting system load, peak-shaving where possible.Available monthly hydro generation is exogenously determined byEGAT. (While PROSCREEN permits more complex modeling ofhydro resources, these capabilities are not used by EGAT, sincehydro makes up a relatively small portion of the total system.)

Pumped Storage is dispatched when (and if) off-peak pumping foron-peak generation is economically justified.

Dispatch of thermal resources. Each in-service thermal unit is dispatchedaccording to standard probabilistic production costing procedures. Any“must-run” units are dispatched first, followed by enough other units ineconomic order53 to meet system load and resource requirements.

Evaluating Expansion Alternatives

PROSCREEN uses a mathematical approach called “dynamic programming” todetermine the combination of sequential, interrelated decisions which produce thedesired least-cost result. Specifically, for each year of the Planning Period, allcombinations of expansion alternatives are evaluated; each combination (known as a“state”) that meets user-defined goals (i.e., to provide required capacity and targetreserve margin) is defined as a feasible state. A feasible state includes:

Capital costs expressed as the economic carrying cost associated with eachcandidate in the state; and

Production costs derived from a complete probabilistic dispatch of the totalsystem including both existing and candidate units.

The present value of capital and production costs determines the accumulated cost ofeach feasible state.

For the next year, each of these “origin states” becomes a starting point forgenerating additional states which are feasible in the current year. Again, all possiblecombinations of the initial state and alternative resource additions are considered.Each feasible state for the year is defined by the required additions, the origin state,and the cumulative objective function value to date. This process continues throughthe Planning Period, with the objective function value for each year equal to theobjective function value for the “origin state” plus the present value of productionand capital cost from the current state.

After the last year of the Planning Period is analyzed, end-effects are considered toaccount for differences in operating characteristics, fuel costs, O&M costs, and the

53 As modified to reflect fuel contract and availability constraints.

How PROSCREEN Works 1 0 1

lives of the alternatives resources beyond the Planning Period. The End Effects Periodtotal costs are equal to the present value of capital costs plus production costs.Capital costs equal the economic carrying costs associated with each year of thespecified End Effects Period. (Since EGAT adopts the model option of an infinite EndEffects Period, this calculation is analogous to a perpetuity.) Production costs equalthe total system cost from a single-period simulation representing this same end-effects period; the dispatch is based on a constant load (the load from the last year ofthe Planning Period) and time-weighted inputs for fuel and operating costs.

Economic Base Case with NT2 – Detail 1 0 3

A6 Economic Base Case with NT2 – Detail


Table A6-1. Demand and Supply Balance

Table A6-2. System Costs by Plant Group

Table A6-3. Fuel Use by Type

Table A6-4. Fuel Type by Individual Plant


Table A6-1. Demand and Supply Balance – Economic Base Case with NT2

2003 2004 2005 2006 2007 2008LOADS - MW SYSTEM PEAK LOAD 17,350 18,520 19,749 21,057 22,440 23,896

RESOURCES - MW HYDRO 1,831 1,831 1,831 1,831 1,831 1,831

PUMPED STORAGE - 490 490 490 490 490

TRANSACTIONS 2,155 2,263 2,323 2,343 2,343 2,343 TOTAL SPP 1,837 1,945 2,005 2,025 2,025 2,025 THEUN HINBOUN HYDRO 192 192 192 192 192 192 HOUAYHO HYDRO 126 126 126 126 126 126 NAM THEUN 2 - - - - - -

THERMAL (by fuel type) 19,844 20,131 20,131 19,940 21,332 23,059 GAS - Combined Cycle 11,691 11,691 11,691 11,691 12,071 13,798 GAS - Thermal 5,048 5,048 5,048 4,856 4,521 4,521 HFO (Heavy Fuel Oil) - 287 287 287 287 287 DIESEL 597 597 597 597 597 597 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported - - - - 1,347 1,347 TNB (tie line) 300 300 300 300 300 300

INSTALLED CAPACITY 23,830 24,715 24,775 24,604 25,996 27,723 CAPACITY RESERVE 6,480 6,195 5,026 3,547 3,556 3,827

ENERGY - GWh ENERGY REQUIRED 111,310 118,506 126,516 135,039 143,847 153,214

GENERATION HYDRO 4,054 4,054 4,054 4,054 4,054 4,054 PUMPED GENERATION - - - 145 243 228 PUMPING ENERGY - - - (207) (348) (325) NET TRANSACTIONS 15,820 16,430 16,856 16,992 16,942 16,892 THERMAL 91,436 98,021 105,606 114,054 122,952 132,360 EMERGENCY ENERGY - - - - 2 4 SYSTEM LOAD FACTOR 0.73 0.73 0.73 0.73 0.73 0.73


2009 2010 2011 2012 2013 2014LOADS - MW SYSTEM PEAK LOAD 25,599 27,263 28,889 30,598 32,442 34,358

RESOURCES - MW HYDRO 1,831 1,831 1,831 1,831 1,831 1,831

PUMPED STORAGE 490 490 490 490 490 490

TRANSACTIONS 2,343 3,338 3,338 3,338 3,338 3,338 TOTAL SPP 2,025 2,025 2,025 2,025 2,025 2,025 THEUN HINBOUN HYDRO 192 192 192 192 192 192 HOUAYHO HYDRO 126 126 126 126 126 126 NAM THEUN 2 - 995 995 995 995 995

THERMAL (by fuel type) 24,786 25,716 27,576 29,676 31,776 33,876 GAS - Combined Cycle 15,526 16,752 18,909 21,009 23,405 26,029 GAS - Thermal 4,521 4,225 3,929 3,929 3,632 3,108 HFO (Heavy Fuel Oil) 287 287 287 287 287 287 DIESEL 597 597 597 597 597 597 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported 1,347 1,347 1,347 1,347 1,347 1,347 TNB (tie line) 300 300 300 300 300 300

INSTALLED CAPACITY 29,451 31,376 33,236 35,336 37,436 39,536 CAPACITY RESERVE 3,852 4,113 4,347 4,738 4,994 5,178

ENERGY - GWh ENERGY REQUIRED 164,204 174,688 185,141 196,153 208,007 220,372

GENERATION HYDRO 4,054 4,054 4,054 4,054 4,054 4,054 PUMPED GENERATION 278 100 86 51 40 69 PUMPING ENERGY (397) (143) (123) (74) (57) (98) NET TRANSACTIONS 16,842 22,171 22,109 22,071 22,021 21,971 THERMAL 143,423 148,504 159,014 170,049 181,948 194,375 EMERGENCY ENERGY 3 1 1 - - - SYSTEM LOAD FACTOR 0.73 0.73 0.73 0.73 0.73 0.73


Table A6-2. System Costs by Plant Group – Economic Base Case with NT2

(US$ 000) 2003 2004 2005 2006 2007 2008

OPERATING COSTSTHERMAL COST - TOTAL TOTAL FUEL COST 1/ 1,601,057 1,771,588 1,901,271 2,027,558 2,149,007 2,249,831 VAR. O&M COST 55,007 58,049 62,536 71,634 81,144 97,019 FIXED 0&M COST 368,831 381,972 381,971 376,866 400,463 417,695 THERMAL COST ($/MWh) 22 23 22 22 21 21

HYDRO COST - TOTAL TOTAL VAR COST 6,933 6,933 6,933 7,609 8,068 7,995 TOTAL FIXED COST 49,845 57,472 57,472 57,472 57,472 57,472

TRANSACTION PURCHASES 513,864 535,738 551,482 557,671 557,671 557,671

EMERGENCY ENERGY COST - - - 559 3,279 5,911

TOTAL SYSTEM COST 2,595,538 2,811,751 2,961,667 3,099,370 3,257,106 3,393,595 SYSTEM COST ($/MWh) 23 24 23 23 23 22 AVG. MARGINAL COST ($/MWh) 22 22 23 30 39 43

FIXED COSTSTOTAL CAPITAL COST 2/ - - - - - 45,808

TOTAL COSTTOTAL UTILITY COST 2,595,538 2,811,751 2,961,667 3,099,370 3,257,106 3,439,403 PRESENT VALUE OF COST 2,595,538 2,556,138 2,447,658 2,328,602 2,224,647 2,135,598 ACCUM. PRESENT VALUE 2,595,538 5,151,675 7,599,334 9,927,937 12,152,584 14,288,183

1/ See attached table of fuel usage by type. 2/ Capital costs for each addition discounted to the year of commissioning.


(US$ 000) 2009 2010 2011 2012 2013 2014

OPERATING COSTSTHERMAL COST - TOTAL TOTAL FUEL COST 1/ 2,395,015 2,474,167 2,647,856 2,819,880 3,004,989 3,183,045 VAR. O&M COST 125,022 132,516 173,563 233,052 297,620 376,656 FIXED 0&M COST 458,520 478,517 508,781 546,959 585,137 623,315 THERMAL COST ($/MWh) 21 21 21 21 21 22

HYDRO COST - TOTAL TOTAL VAR COST 8,229 7,399 7,335 7,173 7,119 7,255 TOTAL FIXED COST 57,472 57,472 57,472 57,472 57,472 57,472

TRANSACTION PURCHASES 557,671 566,509 566,509 566,562 566,509 566,509

EMERGENCY ENERGY COST 4,264 856 741 368 306 315

TOTAL SYSTEM COST 3,606,194 3,717,438 3,962,257 4,231,467 4,519,152 4,814,567 SYSTEM COST ($/MWh) 22 21 21 22 22 22 AVG. MARGINAL COST ($/MWh) 37 28 28 26 25 24

FIXED COSTSTOTAL CAPITAL COST 2/ 137,424 347,862 463,674 601,098 741,829 884,422

TOTAL COSTTOTAL UTILITY COST 3,743,618 4,065,300 4,425,932 4,832,565 5,260,982 5,698,990 PRESENT VALUE OF COST 2,113,175 2,086,142 2,064,730 2,049,479 2,028,336 1,997,461 ACCUM. PRESENT VALUE 16,401,358 18,487,500 20,552,230 22,601,710 24,630,046 26,627,508

1/ See attached table of fuel usage by type. 2/ Capital costs for each addition discounted to the year of commissioning.


Table A6-3. Fuel Use by Type – Economic Base Case with NT2

2003 2004 2005 2006 2007 2008

GENERATION (GWh) GAS - Combined Cycle 70,572 74,726 76,619 77,642 79,500 90,080 GAS - Thermal 5,084 6,317 11,357 18,280 17,176 14,203 HFO (Heavy Fuel Oil) - 1,141 1,835 1,963 2,012 1,835 DIESEL 33 41 48 444 561 637 LIGNITE 15,747 15,796 15,747 15,747 15,747 15,796 COAL - Imported - - - - 7,905 9,738 TNB (tie line) - - - 21 61 75

THERMAL CAPACITY BY FUEL 1/ GAS - Combined Cycle 11,691 11,691 11,691 11,691 12,071 13,798 GAS - Thermal 5,048 5,048 5,048 4,856 4,665 4,521 HFO (Heavy Fuel Oil) - 287 287 287 287 287 DIESEL 597 597 597 597 597 597 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported - - - - 1,347 1,347 TNB (tie line) 300 300 300 300 300 300

FUEL BURNED (mmBtu) GAS - Combined Cycle 535,298 566,192 582,540 592,564 605,896 677,615 GAS - Thermal 50,068 61,487 108,820 174,300 163,722 135,567 HFO (Heavy Fuel Oil) - 11,659 17,543 18,631 19,043 17,551 DIESEL 306 383 453 4,132 5,377 6,058 LIGNITE 164,813 165,323 164,813 164,813 164,813 165,323 COAL - Imported - - - - 77,767 95,804 TNB (tie line) - - 3 248 719 887

TOTAL FUEL COST (US$ 000) GAS - Combined Cycle 1,279,362 1,381,507 1,398,095 1,398,451 1,405,679 1,565,291 GAS - Thermal 119,662 150,029 261,168 411,348 379,835 313,159 HFO (Heavy Fuel Oil) - 31,946 45,260 45,087 43,229 40,544 DIESEL 2,610 1,891 2,108 18,056 22,047 25,261 LIGNITE 199,424 198,388 196,128 192,831 189,535 188,469 COAL - Imported - - - - 117,428 143,706

AVG. FUEL USE (Btu/kWh) GAS - Combined Cycle 7.59 7.58 7.60 7.63 7.62 7.52 GAS - Thermal 9.85 9.73 9.58 9.54 9.53 9.54 HFO (Heavy Fuel Oil) - 10.22 9.56 9.49 9.46 9.56 DIESEL 9.27 9.34 9.44 9.31 9.58 9.51 LIGNITE 10.47 10.47 10.47 10.47 10.47 10.47 COAL - Imported - - - - 9.84 9.84 TNB (tie line) - - - 11.81 11.79 11.83

AVG. FUEL COST (US mills/kWh) GAS - Combined Cycle 18.13 18.49 18.25 18.01 17.68 17.38 GAS - Thermal 23.54 23.75 23.00 22.50 22.11 22.05 HFO (Heavy Fuel Oil) - 28.00 24.66 22.97 21.49 22.09 DIESEL 79.09 46.12 43.92 40.67 39.30 39.66 LIGNITE 12.66 12.56 12.45 12.25 12.04 11.93 COAL - Imported - - - - 14.85 14.76

CAPACITY FACTOR BY TYPE GAS - Combined Cycle 0.69 0.73 0.75 0.76 0.75 0.75 GAS - Thermal 0.11 0.14 0.26 0.43 0.42 0.36 HFO (Heavy Fuel Oil) - 0.45 0.73 0.78 0.80 0.73 DIESEL 0.01 0.01 0.01 0.08 0.11 0.12 LIGNITE 0.81 0.82 0.81 0.81 0.81 0.82 COAL - Imported - - - - 0.67 0.83

1/ Approximate capacity since some units use more than one fuel; see attached table of fuel use by plant.


2009 2010 2011 2012 2013 2014

GENERATION (GWh) GAS - Combined Cycle 104,654 110,836 120,590 133,611 145,996 157,946 GAS - Thermal 11,043 10,195 10,873 9,087 9,045 9,668 HFO (Heavy Fuel Oil) 1,736 1,686 1,609 1,503 1,231 1,116 DIESEL 488 369 530 374 309 272 LIGNITE 15,747 15,747 15,747 15,796 15,747 15,747 COAL - Imported 9,708 9,708 9,708 9,738 9,708 9,708 TNB (tie line) 54 18 15 10 8 8

THERMAL CAPACITY BY FUEL 1/ GAS - Combined Cycle 15,526 16,226 17,626 19,726 21,826 23,926 GAS - Thermal 4,521 4,521 4,521 4,521 4,521 4,521 HFO (Heavy Fuel Oil) 287 287 287 287 287 287 DIESEL 597 827 1,287 1,287 1,287 1,287 LIGNITE 2,208 2,208 2,208 2,208 2,208 2,208 COAL - Imported 1,347 1,347 1,347 1,347 1,347 1,347 TNB (tie line) 300 300 300 300 300 300

FUEL BURNED (mmBtu) GAS - Combined Cycle 774,760 816,955 884,015 972,120 1,055,468 1,135,507 GAS - Thermal 105,684 98,919 106,414 89,521 90,273 97,498 HFO (Heavy Fuel Oil) 16,707 16,283 15,629 14,736 12,418 11,444 DIESEL 4,638 3,407 4,951 3,492 2,883 2,538 LIGNITE 164,813 164,813 164,813 165,323 164,813 164,813 COAL - Imported 95,509 95,509 95,509 95,804 95,509 95,509 TNB (tie line) 635 217 183 118 90 91

TOTAL FUEL COST (US$ 000) GAS - Combined Cycle 1,781,947 1,870,828 2,015,553 2,206,712 2,385,358 2,543,536 GAS - Thermal 243,073 226,524 242,623 203,213 204,017 218,395 HFO (Heavy Fuel Oil) 39,261 38,753 37,666 35,955 30,672 28,610 DIESEL 19,621 14,617 21,489 15,366 12,828 11,422 LIGNITE 184,591 182,943 181,294 178,549 174,702 173,054 COAL - Imported 141,353 140,398 138,487 137,958 136,577 134,667

AVG. FUEL USE (Btu/kWh) GAS - Combined Cycle 7.40 7.37 7.33 7.28 7.23 7.19 GAS - Thermal 9.57 9.70 9.79 9.85 9.98 10.08 HFO (Heavy Fuel Oil) 9.62 9.66 9.71 9.80 10.09 10.25 DIESEL 9.50 9.23 9.34 9.34 9.33 9.33 LIGNITE 10.47 10.47 10.47 10.47 10.47 10.47 COAL - Imported 9.84 9.84 9.84 9.84 9.84 9.84 TNB (tie line) 11.76 12.06 12.20 11.80 11.25 11.38

AVG. FUEL COST (US mills/kWh) GAS - Combined Cycle 17.03 16.88 16.71 16.52 16.34 16.10 GAS - Thermal 22.01 22.22 22.31 22.36 22.56 22.59 HFO (Heavy Fuel Oil) 22.62 22.99 23.41 23.92 24.92 25.64 DIESEL 40.21 39.61 40.55 41.09 41.51 41.99 LIGNITE 11.72 11.62 11.51 11.30 11.09 10.99 COAL - Imported 14.56 14.46 14.27 14.17 14.07 13.87

CAPACITY FACTOR BY TYPE GAS - Combined Cycle 0.77 0.78 0.78 0.77 0.76 0.75 GAS - Thermal 0.28 0.26 0.27 0.23 0.23 0.24 HFO (Heavy Fuel Oil) 0.69 0.67 0.64 0.60 0.49 0.44 DIESEL 0.09 0.05 0.05 0.03 0.03 0.02 LIGNITE 0.81 0.81 0.81 0.82 0.81 0.81 COAL - Imported 0.82 0.82 0.82 0.83 0.82 0.82

1/ Approximate capacity since some units use more than one fuel; see attached table of fuel use by plant.


Table A6-4. Fuel Type by Individual Plant – Economic Base Case with NT2

Code THERMAL Unit CAPACITY FUEL FUEL COMM'N RETIREM'TNo. UNIT No. MW CLASS YEAR YEAR

Existing Gas-fired C-C - with some Diesel support1 LKB 1 232 DGLKB GCC 1970 20502 NPO_CC 1 347.2 DGNP GCC 1992 20173 NPO_CC 2 347.2 DGNP GCC 1994 2019

Existing Gas-fired C-C Plant4 BPK_CC 1 372.7 GAS_MIX GCC 1983 20075 BPK_CC 2 372.7 GAS_MIX GCC 1983 20086 BPK_CC 3 300.9 GAS_MIX GCC 1992 20167 BPK_CC 4 300.9 GAS_MIX GCC 1992 20178 SB_CC 1 328.1 GAS_MIX GCC 1994 20199 SB_CC 2 610.3 GAS_MIX GCC 1998 202210 WN_CC 1 632.5 GAS_MIX GCC 1997 202311 WN_CC 2 632.5 GAS_MIX GCC 1998 202312 WN_CC 3 708.3 GAS_MIX GCC 1998 202316 RY_CC 1 301.8 GAS_MIX GCC 1992 201517 RY_CC 2 301.8 GAS_MIX GCC 1992 201518 RY_CC 3 301.8 GAS_MIX GCC 1992 201519 RY_CC 4 301.8 GAS_MIX GCC 1993 201520 KN_CC 1 165.1 GAS_MIX GCC 1995 201621 KN_CC 2 165.1 GAS_MIX GCC 1995 201622 KN_CC 3 165.1 GAS_MIX GCC 1995 201623 KN_CC 4 165.1 GAS_MIX GCC 1995 201624 RB_CC 1 725 GAS_MIX GCC 2002 202725 RB_CC 2 725 GAS_MIX GCC 2002 202726 RB_CC 3 725 GAS_MIX GCC 2003 202727 IPT 1 700 GAS_MIX GCC 2000 202528 EPEC 1 350 GAS_MIX GCC 2003 202229 TECO 1 700 GAS_MIX GCC 2000 202030 Bowin 1 713 GAS_MIX GCC 2003 2027

Existing Gas- and Oil-fired Thermal Plant31 SB_TH 1 191.2 GAS_TH GTH 1971 200532 SB_TH 2 191.2 GAS_TH GTH 1972 200633 SB_TH 3 296.4 GAS_TH GTH 1974 200934 SB_TH 4 296.4 GAS_TH GTH 1976 201035 SB_TH 5 296.4 GAS_TH GTH 1978 201236 NB_TH 1 71.9 HOIL_2S HFO 1961 200137 NB_TH 2 71.9 HOIL_2S HFO 1963 200138 NB_TH 3 83.8 HOIL_2S HFO 1969 200139 BPK_TH 1 524.2 GAS_TH GTH 1983 201340 BPK_TH 2 524.2 GAS_TH GTH 1984 201441 BPK_TH 3 571.9 GAS_TH GTH 1992 202142 BPK_TH 4 571.9 GAS_TH GTH 1993 202144 KA_TH1 1 287.4 HOIL_2S HFO 2004 203345 PPB_TH 1 71.9 GAS_TH GTH 1981 200746 PPB_TH 2 71.9 GAS_TH GTH 1989 200747 RB_TH 1 720 GAS_TH GTH 2000 202548 RB_TH 2 720 GAS_TH GTH 2001 2025

Existing Lignite-fired Thermal Plant49 MM_TH 1 69 LIGN_MM LIGN 1978 200250 MM_TH 2 69 LIGN_MM LIGN 1979 200251 MM_TH 3 69 LIGN_MM LIGN 1981 200252 MM_TH 4 138 LIGN_MM LIGN 1984 201453 MM_TH 5 138 LIGN_MM LIGN 1984 201454 MM_TH 6 138 LIGN_MM LIGN 1985 201555 MM_TH 7 138 LIGN_MM LIGN 1985 201556 MM_TH 8 276 LIGN_MM LIGN 1989 201857 MM_TH 9 276 LIGN_MM LIGN 1990 201958 MM_TH 10 276 LIGN_MM LIGN 1991 202159 MM_TH 11 276 LIGN_MM LIGN 1991 202160 MM_TH 12 276 LIGN_MM LIGN 1995 202461 MM_TH 13 276 LIGN_MM LIGN 1995 2025


Code THERMAL Unit CAPACITY FUEL FUEL COMM'N RETIREM'TNo. UNIT No. MW CLASS YEAR YEAR

Committed Gas-fired C-C Plant (IPPs)62 UPDC 1 700 GAS_MIX GCC 2008 203263 UPDC 2 700 GAS_MIX GCC 2009 203364 GULF 1 700 GAS_MIX GCC 2008 2032

Committed Coal-fired Plant (IPPs)66 BLCP 1 673.3 COAL_IND COAL 2007 203167 BLCP 2 673.3 COAL_IND COAL 2007 2031

Existing Diesel-fired GT Plant68 NC_GT 1 119.4 DIESEL DISE 1995 201569 NC_GT 2 119.4 DIESEL DISE 1995 201570 NC_GT 3 119.4 DIESEL DISE 1995 201571 NC_GT 4 119.4 DIESEL DISE 1995 200072 SRTGT 1 119.4 DIESEL DISE 2001 201673 SRTGT 2 119.4 DIESEL DISE 2001 2016

Existing tie with Malaysia74 TNB_300 1 300 TNB TNB 2002 205075 TNB OLD 1 80 TNB TNB 1994 2002

Committed Gas-fired C-C Plant114 KNCCD2 1 380.2 GAS_MIX GCC 2007 2031

ECONOMIC BASE CASE - Recommended Additions (including Reconditioning)229 CC700 229 700 GAS_NEW GCC 2014 2038230 CC700 230 700 GAS_NEW GCC 2014 2038231 CC700 231 700 GAS_NEW GCC 2014 2038232 BKT1 232 524.2 GAS_TH GTH 2014 2028233 CC700 233 700 GAS_NEW GCC 2013 2037234 CC700 234 700 GAS_NEW GCC 2013 2037235 CC700 235 700 GAS_NEW GCC 2013 2037236 SBT5 236 296.4 GAS_TH GTH 2013 2027237 CC700 237 700 GAS_NEW GCC 2012 2036238 CC700 238 700 GAS_NEW GCC 2012 2036239 CC700 239 700 GAS_NEW GCC 2012 2036240 GT230 240 230 DIESEL DISE 2011 2025241 GT230 241 230 DIESEL DISE 2011 2025242 CC700 242 700 GAS_NEW GCC 2011 2035243 CC700 243 700 GAS_NEW GCC 2011 2035244 SBT4 244 296.4 GAS_TH GTH 2011 2025245 GT230 245 230 DIESEL DISE 2010 2024246 CC700 246 700 GAS_NEW GCC 2010 2034247 SBT3 247 296.4 GAS_TH GTH 2010 2024248 CC700 248 700 GAS_NEW GCC 2009 2033249 CC700 249 700 GAS_NEW GCC 2009 2033250 CC700 250 700 GAS_NEW GCC 2008 2032

CANDIDATE ADDITIONS (including Reconditioning)121 O700 1 700 HOIL_2S HFO123 C700 1 700 COAL_IND COAL127 CC700 1 700 GAS_NEW GCC130 GT230 1 230 DIESEL DISE157 SBT3 3 296.4 GAS_TH GTH158 SBT4 4 296.4 GAS_TH GTH159 SBT5 5 296.4 GAS_TH GTH160 BKT1 1 524.2 GAS_TH GTH161 BKT2 2 524.2 GAS_TH GTH164 MM4 4 138 LIGN_MM LIGN171 RYC1 1 301.8 GAS_MIX GCC

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