st lucias energy transition

FURTHER, FASTER, TOGETHER

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Saint Lucia National Energy Transition Strategy: Results October 17th 2016 Caribbean Renewable Energy Forum Miami


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Presenters Roy Torbert, Principal – Planning Rocky Mountain Ins9tute – Carbon War Room


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Sylvester Clauzel Permanent Secretary – Sustainable Development Victor Emmanuel Business Development Manager, St. Lucia Electricity Services Limited (LUCELEC)


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Agenda •  Context •  Process •  NETS Results

o  Energy o  Economic

•  Lessons Learned

•  Q&A

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Context 1

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Project Stakeholders and Supervisors LUCELEC is a ver9cally integrated public u9lity which currently has the sole responsibility for the genera9on, transmission, distribu9on and sale of electricity in Saint Lucia. In 2010, the Government of Saint Lucia approved the Na9onal Energy Policy, emphasizing RE deployment with the intent to lower the cost and price vola9lity of electricity and to reduce dependence on imported oil. In 2012, refined goals were announced which proposed a renewable energy penetra9on target of 35% by 2020 and a 20% reduc9on in energy consump9on for the public sector. In January of 2016, the Government passed a law crea9ng a new independent regulator, the Na9onal U9li9es Regulatory Commission.


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Independent Technical Partners Rocky Mountain Ins<tute-‐Carbon War Room & Clinton Climate Ini<a<ve, similar-‐minded nonprofits joined forces in 2015 to accelerate the transi9on of small island economies toward reliable, cost-‐effec9ve, and clean energy systems and to create a blueprint for other isolated economies


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DNV GL is the largest independent technical advisor on renewable energy with more than 1000 staff in renewable energy in 50 loca9ons, across 27 countries


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Saint Lucia Energy Landscape •  59 MW peak served by 87 MW diesel genera9on

•  Government target of 35% renewable energy penetra9on by 2020

•  Planned/Announced Projects: –  3 MW Solar PV

–  12 MW Wind

–  30 MW Geothermal

–  Government Energy Efficiency Projects •  Changing energy landscape driven by economics and RE energy

targets and commitments to climate change mi9ga9on

•  Requires careful technical analysis to make informed policy and investment decisions, along with alignment of key stakeholders


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National Energy Transition Strategy •  Na<onal Energy Transi<on Strategy (NETS)

signed jointly by Government of Saint Lucia and LUCELEC in January 2016

•  At its core, the NETS is an Integrated Resource Plan (IRP), with unique factors in Saint Lucia: –  Inclusive process involving both key partners at

each stage of results and decision making –  Independent facilita9on and analysis provided in-‐

kind by third-‐par9es –  Public input gathered through a stakeholder

consulta9on session

•  Both par9es will jointly submit the NETS/IRP to the Na9onal U9li9es Regulatory Commission (NURC).


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Process

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The NETS Core: An Integrated Resource Plan

The Integrated Resource Plan (IRP) considers forecasted loads over a 20-‐year period and

assesses the least-‐cost supply and demand side op9ons to reliably meet that load.


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Questions the NETS Seeks to Answer •  How will all our planned resource investments including solar, wind, and

geothermal interact with exis<ng diesel infrastructure?

•  Will large-‐scale renewable energy integra9on affect grid reliability?

•  How do different energy mix scenarios affect u<lity economics and rates?

•  Is there an op<mal geothermal generator size for the grid?

•  Should we consider other resources in the energy transi9on such as baSery storage or energy efficiency?

•  What are the costs and benefits of u<lity-‐owned assets versus distributed genera<on, both for renewables and conven9onal genera9on?


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Balancing Needs of All Stakeholders

Goal

Objec<ve

• Overarching priori9es for electrical system (e.g. reliability, cost stability)

• Targets set by both par9es to achieve the overall goal

Measurement • Specific metrics (e.g. ‘Return on Equity’ or ‘SAIDI’), measured across all examined scenarios

At the kickoff, partners agreed to a broad set of goals, and objec9ves and measurements were refined throughout the process:


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Explored Resources 13


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Saint Lucia: Developing Scenarios Stakeholders agreed to develop scenarios which explore the following variables:

•  Carbon-‐Intensity: conven9onal to renewable genera9on

•  Ownership Modality: highly centralized to highly decentralized system

Hybrid

U<lity-‐Owned

Distributed

Centralized Ownership

Decentralized Ownership

Conven5onal Renewable

Diesel Fuel Only

Natural Gas IPP Geothermal

Solar PV

Wind

Storage


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Results 3

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Resource Assessments Solar Resource Assessment: •  Applied GIS-‐Based Methodological Approach:

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Island-Wide Solar Resource Assessment •  RESULTS:

! GIS-‐generated .kmz and .shp files showing poten9al project sites for each technology (ground-‐mount, roolop, carport) •  Example (carport):

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Explored Scenarios 18


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2017 Dispatch Visualization Peak at 2PM Min at 4AM

*SOC means ‘state of charge’ for the ba?eries

Modeled peak day: June 23rd 2017 Es9mated Peak: 61.7 MW Storage: 0 MWh

0

20

40

60

80

100

0

20

40

60

80

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

BaSery State of Cha

rge (%

)

Power (M

W)

Solar / High DG, Peak Load

Diesel U9lity PV Distributed PV Load


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Modeled peak day: June 23rd 2019 Es9mated Peak: 61.25 MW Storage: 7 MWh

0

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40

60

80

100

0

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40

60

80

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

BaSery State of Cha

rge (%

)

Power (M

W)

Solar / High DG, Peak Load

Diesel U9lity PV Distributed PV Load Net Load SOC


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Modeled peak day: June 23rd 2024 Es9mated Peak: 63.4MW Storage: 20 MWh

0

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40

60

80

100

0

20

40

60

80

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

BaSery State of Cha

rge (%

)

Power (M

W)

Solar + Wind / High DG, Peak Load

Diesel Wind U9lity PV Distributed PV Load Net Load SOC


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0

20

40

60

80

100

0

20

40

60

80

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

BaSery State of Cha

rge (%

)

MW

Solar + Wind + Geo / High DG, Peak Load

Geothermal Diesel Wind U9lity PV

Distributed PV Load Net Load SOC

Modeled peak day: June 23rd 2024 Es9mated Peak: 63.4MW Storage: 20 MWh


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Grid Integration Study - Methodology 23

Defini<on of grid

regula<on

Result of viola<on

Mi<ga<on

Thermal Loading

Grid regula<ons define a maximum (100%) thermal load on lines, conductors, wires and other equipment

Loading above 100% could cause equipment damage

or fires

Equipment upgrades can be required to avoid thermal overloading

Reverse Power Flow Current equipment meters do not typically sense the flow of power from the genera<on area to the

line.

Reverse flow from distributed genera<on such as solar PV could cause voltage problems

Equipment upgrades could be required to sense power flow from both

direc<ons

Over and under voltage

Regula<ons require voltage at all points on the distribu<on system to be between 95% and 105% of

nominal

Over or under voltage results in customer’s equipment issues or

damage, and service may be lost

Installa<on of line regulators, smart

inverters, and capacitor banks could be required

Tes<ng select scenarios in future years for grid stability


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Distribution Study: Methodology Data inputs provided by LUCELEC •  Conductor data •  Historical load data by feeder •  Distribu9on maps in AutoCAD Methodology •  Distribu9on maps converted to Synergi

analy9cal model •  Grid regula9on compliance review •  Verify results with substa9on

measurements •  Tests a variety of load and DG scenarios •  Feeder peak day9me load and feeder

minimum day9me load •  For each load and DG scenario, sta9c and

quasi-‐sta9c load flow analyses were performed to iden9fy technical viola9ons on the distribu9on system.

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Transmission Study: Methodology •  Inves9gates the impact of new genera9on

resources (solar, wind and geothermal) •  Analyses done at minimum day9me load and

peak day9me load, as well as during normal condi9on and N-‐1 condi9on.

•  Dynamic simulates the outage of the largest generator and the ability of the system to recover with various RE penetra9ons and technologies.

•  Tests the impact of voltage and frequency ride through.

•  Examines spinning reserve based on diesel opera9ons, and presumes spinning reserve when determining system changes and recovery.

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Transmission map provided by LUCELEC, and modeled in PowerWorld and GE tools


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Capital and Operating Cost Projections 26


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Total Cost and Renewable Target Implications 27

Reducing total costs while mee9ng renewable energy goals is possible


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LUCELEC Participation is Key •  A few situa9ons make Independent Power Producers (IPPs)

the right choice for genera9on: –  Large projects requiring capital infusion the u9lity normally does not

have access to –  Technological complexity that exceeds the capability of the u9lity –  U9lity is insolvent or poorly managed and cannot access capital at a

decent rate

•  LUCELEC is a viable, well-‐managed, u9lity with access to low-‐cost capital

•  LUCELEC ownership of certain renewable energy assets (such as solar and storage) play a role for least-‐cost genera9on


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Best Practices & Lessons Learned 4

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Positive Outcome – Holistic Approach •  In the past, LUCELEC commissioned individual

studies, e.g., biomass, heat recovery and alterna9ve fuels

•  Government sets targets, e.g. renewable energy, climate commitments and energy efficiency.

•  Individual projects are then typically assessed in silos

•  The NETS assesses all technology op9ons

simultaneously, and analyzes their interac9ons between each other and the impact on economics

•  Allows u9lity to develop investment strategy and Government to make long-‐term policy decisions, at the same 9me and on the same basis

•  Integra9ng with ongoing projects helps prove the assump9ons of the IRP.


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Challenges Data Collec<on: •  Data does not always exist or is not in

the right format –  RMI-‐CWR interviewed key personnel to

gather data –  RMI-‐CWR hired temporary worker to

transcribe handwripen generator data •  Limited access to proprietary data

–  For each resource, it is cri9cal to have both energy & economic inputs

–  Extrapola9ng from one data source, or from outdated data, has limita9ons

Government Turnover: •  Complex and new discussions require

con9nuity of staff engagement. This was well managed by GoSL.


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Questions? 32

Support Provided By:

Partners:


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Appendix

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Load Forecast – Inputs & Methodology •  Annual and Monthly historical sales by customer category provided by LUCELEC for

the last 10 years •  DNV GL conducted a site visit week of 27th January to interview LUCELEC, Invest

Saint Lucia, and future Hotels & Commercial Customers for special projects •  Macro-‐socioeconomic data from Eastern Caribbean Central Bank and World Bank •  Modeled this out to 2025. Preliminary data shows that load growth can achieve a

30MW base-‐load.

(Number of Customers) x (Average Consump5on per Customer) = Total Consump9on


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Least Cost Generation Options Methodology •  Build upon the HOMER model developed by John Glassmire, Director of Energy

Engineering at HOMER Energy for the work funded through World Bank –  What mix of energy sources (whether renewable and/or fossil fuel) is the most economical to

provide power for Saint Lucia (looking only at genera9on)?

•  Use input projec9ons to run HOMER for various years in the future and determine op9mal supply mix for each year –  In what years should new supply resources be added to the system? –  How will the mix of supply resources operate in each year (hourly dispatch)?

•  Use HOMER outputs (supply mix, opera9on of supply resources, fuel used, etc.) as inputs to next models: grid integra9on, u9lity business model, & rate impact

•  Have contracted HOMER Energy for addi9onal support and QC

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Utility Business Model - Methodology Approach: •  Assess LUCELEC’s current governing

regula9ons for rate determina9on (allowable rate of return)

•  Use current regula9ons and financial statements to assess how different renewable assets will influence LUCELEC financial status and tariffs in coming years

•  Specifically consider debt and equity op9ons for renewable and thermal investments, as well as the implica9ons of energy efficiency, distributed genera9on, and storage.

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Volumetric Rate Structure (charged per kWh

$0.499

$0.474

-‐$0.196

-‐$0.400

-‐$0.200

$-‐

$0.200

$0.400

$0.600

$0.800

$1.000

$1.200

Fuel Adjustment

Fuel Passthrough

Base Rate

2016 Commercial Low Tension: ECD $.777

*The base rate is set in the 2006 ESA Amendment


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Load Forecasting - Results

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•  Energy Sales:


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Load Forecasting - Results

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•  Peak Demand:


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Demand Side Management & Energy Efficiency

!  DNV GL developed satura9on and energy consump9on es9mates for specific end use components for each Class (domes9c, commercial, hotels):

•  Example:

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Refrigeration27.3%

Water Heating20.5%

TV12.7%

Lighting7.2%

Space Cooling6.2%

Freezer5.7%

PC5.6%

Miscellaneous4.4%

Pool Pump3.5%

Clothes Washer

3.3% Cooking1.6%

Clothes Dryer1.6%

Dishwashers0.3%


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Island-Wide Solar Resource Assessment •  Developed constructability parameters for each solar PV technology (ground-‐mount,

roolop, carport) •  Example (roolop):

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Rate reduction is maximized with LUCELEC ownership 41

$0.89

$0.91

$0.84

$0.80

$0.85

$0.84

$0.74

$0.76

$0.78

$0.80

$0.82

$0.84

$0.86

$0.88

$0.90

$0.92

1. Fossil Fuel Only 2. Solar High DG 3. Solar Mid DG 7. Solar Wind Low DG

13. Solar Geo Wind Low DG

14. Thermal IPP

$ E

CD

/ k

Wh

Customer Rate (after 20 years)


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LUCELEC debt burden over time

2016 2021 2026 2031

tota

l d

eb

t b

urd

en

Debt Burden (Total Long Term Debt Divided by Tangible Net Worth)

Fossil Fuel Only

Solar, High DG, Debt Constrained

Solar, Mid DG

Solar + Wind, Low DG

Solar + Wind + Geo, Low DG

Thermal IPP

1

2

0

* long term debt divided by tangible net worth

No scenarios exceed current LUCELEC targets

Natural gas debt can be reduced if supplier finances all Saint Lucia infrastructure (storage, receiving terminal, generator retrofits)


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Sensitivity Analysis: Fuel Price Forecast Four alterna<ve scenarios were inves<gated, with varying pathways for fuel price.

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$0.0

$0.2

$0.4

$0.6

$0.8

$1.0

$1.2

$1.4

$1.6

$1.8

$2.0

2006 2011 2016 2021 2026 2031

Diesel Pric

e (USD

/ liter)

Examined Fuel Sensi<vi<es

Reference Case (pre-‐hedging)

Fuel Returns to 2012 Level in Five Years

Vola9le Future (based on historical vola9lity)

Globally Depressed Fuel Prices

Results forthcoming


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A renewable transition reduces exposure to volatile fuel futures

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$-‐ $2,000 $4,000 $6,000 $8,000

Reference Case

Fuel Returns to 2012 Level in Five Years

Vola9le Future (based on historical vola9lity)

Globally Depressed Fuel Prices

Millions of ECD

20-‐Year Expenditure to Operate Electricity System

Solar, Wind, and Low DG Scenario Fossil Fuel Only (Reference Case)

In a vola9le and high fuel future, total costs increase 38% when opera9ng diesel, versus 28% for a renewable mix

st lucias energy transition

Environment