the barbados light & power company limited - · pdf file2.3.4 system load forecast ......

1.1 GeGeneration

The Barbados Light & Power Company Limited 2012 Integrated Resource Plan February 28th 2014

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan i

REVISION HISTORY DATE VERSION COMMENTS

February 28th 2014 Rev. 2 Inclusion of Scenario 6 to reflect government

proposed waste-to energy plant. Revision of

retirement dates and earliest installation date of

reciprocating capacity. Adjustment of heat rate

modeling setting in Plexos.

November15th 2013 Rev. 1 Revisions following review by Fair Trading

Commission and PPA Energy

March 21st 2013 Rev. 0 First Issue

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan ii

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan iii

2012 Integrated Resource Plan Final Report

Table of Contents

VOLUME I

1.1 GeGeneration .................................................................................................................................................

TABLE OF CONTENTS ......................................................................................................................... III

LIST OF TABLES ................................................................................................................................. VI

LIST OF FIGURES ............................................................................................................................ VIII

LIST OF ACRONYMS ......................................................................................................................... IX

1 EXECUTIVE SUMMARY ................................................................................................. 13

1.1 Background......................................................................................................................................... 13

1.2 Integrated Resource Planning ......................................................................................................... 13

1.3 Sustainable Energy Framework for Barbados .............................................................................. 15

1.4 Recommendation ............................................................................................................................... 15

1.5 Structure of Report ............................................................................................................................ 19

2 PLANNING PARAMETERS ....................................................................................... 21

2.1 Study Horizon and Reference Year................................................................................................. 21

2.2 Economic Assumptions ................................................................................................................... 21 2.2.1 Discount Rate ......................................................................................................................................... 21 2.2.2 Cost Estimates ....................................................................................................................................... 21 2.2.3 Capital Cost Estimates .......................................................................................................................... 22 2.2.4 Taxes & Duties ....................................................................................................................................... 22 2.2.5 Currency & Exchange Rates ................................................................................................................ 22 2.2.6 Economic Growth ................................................................................................................................... 22

2.3 Demand Forecast ............................................................................................................................... 23

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan iv

2.3.1 Electricity Prices Variability .................................................................................................................. 24 2.3.2 Weather Variability ................................................................................................................................. 27 2.3.3 Economic Variability .............................................................................................................................. 28 2.3.4 System Load Forecast .......................................................................................................................... 30 2.3.5 System Peak Forecast .......................................................................................................................... 31 2.3.6 Demand Side Management .................................................................................................................. 32 2.3.7 Renewable Energy Rider ...................................................................................................................... 34

2.4 Fuel Price Forecasts .......................................................................................................................... 35 2.4.1 Liquid Fuel .............................................................................................................................................. 36 2.4.2 Natural Gas ............................................................................................................................................. 42 2.4.3 Biomass ................................................................................................................................................... 46 2.4.4 Landfill Gas ............................................................................................................................................. 50 2.4.5 Calorific Values ...................................................................................................................................... 50

2.5 System Criteria ................................................................................................................................... 50 2.5.1 System Reliability ................................................................................................................................... 50 2.5.2 System Stability ...................................................................................................................................... 58

3 GENERATING TECHNOLOGIES ............................................................................. 66

3.1 Existing Plant ...................................................................................................................................... 66 3.1.1 Spring Garden Generating Station ...................................................................................................... 66 3.1.2 Seawell Generating Station .................................................................................................................. 66 3.1.3 Garrison Hill Generating Station .......................................................................................................... 67 3.1.4 Cost and Performance Parameters ..................................................................................................... 67

3.2 Candidate Plant .................................................................................................................................. 70 3.2.1 General Requirements .......................................................................................................................... 70 3.2.2 Conventional Candidate Plant ............................................................................................................. 71 3.2.3 Renewable Energy Technologies ........................................................................................................ 77 3.2.4 RE Technology Assumptions ............................................................................................................... 89 3.2.5 Environmental Criteria ........................................................................................................................... 93

3.3 Levelized Costs .................................................................................................................................. 94

4 MODELING METHODOLOGY................................................................................... 97

4.1 Worlds and Scenarios ....................................................................................................................... 97

4.2 Sensitivities......................................................................................................................................... 99

4.3 Software Model ................................................................................................................................. 100

5 RESULTS ...................................................................................................................... 101

5.1 Expansion Plans .............................................................................................................................. 101 5.1.1 Base Demand World ........................................................................................................................... 102 5.1.2 High Demand World ............................................................................................................................ 108

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan v

5.1.3 Low Demand World ............................................................................................................................. 109

5.2 Sensitivities....................................................................................................................................... 110

5.3 Analysis ............................................................................................................................................. 111 5.3.1 Natural Gas Availability & Interruption Risk ..................................................................................... 112 5.3.2 Biomass Availability & Risks .............................................................................................................. 116 5.3.3 Renewable Energy Policy Indicative Target .................................................................................... 117 5.3.4 Proposed Waste to Energy Facility ................................................................................................... 117 5.3.5 Other Policy Considerations ............................................................................................................... 120

5.4 Recommendation ............................................................................................................................. 122

5.5 Avoided Generating Costs ............................................................................................................. 123

6 SUMMARY AND CONCLUSION ........................................................................... 127

6.1 Sustainable Energy Framework for Barbados ............................................................................ 128

6.2 Recommendation ............................................................................................................................. 129

7 REFERENCES ............................................................................................................. 134

VOLUME II

APPENDICES

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan vi

List of Tables

Table 1: Scenario 6: Least-cost Integrated Resource Plan ............................................................ 17 Table 2: Fuel Price Escalation (2012-2036) ................................................................................. 25 Table 3: Electricity Price Growth Scenarios ................................................................................. 27 Table 4: Temperature Scenarios ................................................................................................... 28

Table 5: Economic Growth Scenarios .......................................................................................... 29 Table 6: System Load Growth ...................................................................................................... 31 Table 7: System Peak Demand Growth ........................................................................................ 32 Table 8: SEFB Energy Efficiency Initiatives ................................................................................ 34 Table 9: Renewable Energy Rider Historical and Projected Capacity ......................................... 35

Table 10: Fuel Price Projections for Reference Fuel Price Scenario (2012 $) ............................. 40

Table 11: Liquid Fuel Price Forecast Scenarios (2012 $)............................................................. 41

Table 12: Natural Gas price Forecast Scenarios without Fixed Costs (2012 $) ........................... 45 Table 13: Local Biomass Price Forecast Scenarios (2012 $) ....................................................... 47

Table 14: Imported Biomass Price Forecast Scenarios (2012 $) .................................................. 49 Table 15: Calorific Values Used In Study .................................................................................... 50

Table 16: Generation Reliability Standards in Select Countries .................................................. 53 Table 17: Cost/Benefit Analysis of Generation Reliability .......................................................... 55 Table 18: Comparison of impact of upper limit on reserve margin .............................................. 58

Table 19: Intermittent RE Penetration Levels on Other Island Grids ........................................... 64 Table 20: Cost & Performance Parameters for Existing Plant ..................................................... 68

Table 21: Financial & Performance Data for Liquid Fuel Candidate Plant ................................. 76 Table 22: Financial &Performance Data for Natural Gas Candidate Plant .................................. 76

Table 23: Overview of Renewable Technology Characteristics................................................... 77 Table 24: Cost & Technical Characteristics of Battery Storage Options (Source: BEW

Engineering, 2012) ........................................................................................................................ 86

Table 25: Battery Cost Estimates (Source: BEW Engineering, 2012) ......................................... 87 Table 26: Summary of RE Technologies Included In Study ........................................................ 90

Table 27: RE Technologies Excluded From IRP Study ............................................................... 91

Table 28: RE Technology Assumptions ....................................................................................... 92 Table 29: Environmental Impact Assumptions............................................................................. 94

Table 30: Scenario Matrix of Fuels & Technologies .................................................................... 99 Table 31: NPV Results for Worlds and Scenarios ...................................................................... 101 Table 32: Characteristics of Least-Cost Plans ............................................................................ 102

Table 33: Build Schedule for Liquid + RE Scenario in Base Demand World ........................... 103 Table 34: Build Schedule for Liquid + NatGas + RE Scenario in Base Demand World ........... 104

Table 35: Build Schedule for Liquid + NatGas Restricted + RE Scenario in Base Demand World

..................................................................................................................................................... 105 Table 36: Build Schedule for Liquid + NatGas Restricted + RE Forced Scenario in Base Demand

World .......................................................................................................................................... 106 Table 37: Build Schedule for Liquid + RE Forced Scenario in Base World .............................. 107

Table 38: Waste-to-Energy (Plasma Arc) Assumptions ............................................................. 118 Table 39: Build Schedule for Liquid + WtE Forced Scenario in Base World ............................ 119

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan vii

Table 40: NPV Results for the Six Scenarios ............................................................................. 120 Table 41: Characteristics of Least-Cost Plans ............................................................................ 122 Table 42: Build Schedule for Recommended Plan in Base Demand world ............................... 123 Table 43: Avoided Cost of Renewable Technologies ................................................................. 126

Table 44: Scenario Matrix of Fuels & Technologies .................................................................. 129 Table 45: Scenario 6: Least-cost Integrated Resource Plan........................................................ 130

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan viii

List of Figures

Figure 1: Forecasted Electricity Prices ......................................................................................... 26 Figure 2: Total Demand ................................................................................................................ 30 Figure 3: Forecast System Load ................................................................................................... 31

Figure 4: Forecast System Load under DSM ................................................................................ 33 Figure 5: Average Absolute Difference between the Forecast and Actual Projection Based On

AEO 1993 To 2010 Projections .................................................................................................... 37 Figure 6: AEO 2012 Low Sulphur Crude Oil Projections (2012 US$) ........................................ 38 Figure 7: Historical & Projected Fuel Prices - Reference Case (2012 $) ..................................... 40

Figure 8: World LNG Estimated November 2013 Landed Prices in US$/mm Btu (Source:

Waterborne Energy Inc. Data, October 2013) .............................................................................. 43 Figure 9: Natural Gas Price Forecast without Fixed Costs (2012 $) ............................................ 45

Figure 10: Local Biomass Price Forecast (2012 $) ....................................................................... 47 Figure 11: Imported Biomass Price Forecast (2012 $) ................................................................. 49 Figure 12: Marginal & Total Costs vs. Reserve Margin ............................................................... 56

Figure 13: Reserve Margin for Recommended Plan..................................................................... 56 Figure 14: Comparison of Typical Daily Electricity Demand and Solar PV Output ................... 61 Figure 15: Levelized Costs Based On Base Assumptions ............................................................ 96

Figure 16: NPV Sensitivities on Optimal Plans for each Scenario ............................................. 111 Figure 17: Proportion of Installed Generating Technologies in scenarios 1, 2 & 3 ................... 113

Figure 18: Impact of Delayed in Natural Gas Availability on NPV ........................................... 114 Figure 19: Impact of Delayed Natural Gas Availability on Total Generation Cost ................... 114 Figure 20: Impact of 1-Year Gas Interruption in 2018 on Fuel Cost .......................................... 115

Figure 21: Generation by Energy Source for Recommended Plan ............................................. 131

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan ix

LIST OF ACRONYMS

ACRONYM ACRONYM MEANING

AC Alternating Current

AD Anaerobic Digestion

AOE Annual Energy Outlook

BDS$ Barbadian Dollars

BL&P The Barbados Light & Power Company Limited

CCGT Combined Cycle Gas Turbine

CNG Compressed Natural Gas

CO2 Carbon Dioxide

COUE Cost of Unserved Energy

CSP Concentrating Solar Power

CUM PV Cumulative Present Value

DC Direct Current

DG Distributed Generation

DI Diversity Index

DSM Demand Side Management

ECA External cost Analysis

EIA US Energy Information Administration

EV Electric Vehicle

FCA Fuel Clause Adjustment

FoR Forced Outage Rate

FTC Fair Trading Commission

GDP Gross Domestic Product

GoB Government of Barbados

GoTT Government of Trinidad and Tobago

GWh Gigawatt-hour(s)

HECO Hawaiian Electric Company

HELCO Hawaii Electric Light Company

HFO Heavy Fuel Oil

HVDC High Voltage Direct Current

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan x

IDB International Development Bank

IMF International Monetary Fund

IPPs Independent Power Producers

IRP Integrated Resource Plan

ISO International Organization for Standardization

kV Kilovolt(s)

kW Kilowatt(s)

kWh Kilowatt-hour(s)

LOLE Loss of Load Expectation

LOLP Loss of Load Probability

LF Liquid Fuels, i.e. heavy fuel oil, diesel & Jet A1

LHV Lower Heating Value

LNG Liquefied Natural Gas

LSD Low Speed Diesel

MAUT Multi-Attribute Utility Theory

MECO Maui Electric Company

mmBtu Million British Thermal Unit

mmscf/day Million Standard Cubic Feet Per Day

MSD Medium Speed Diesel

MSW Municipal Solid Waste

MW Megawatt(s)

MWh Megawatt-hour(s)

NG/NatGas Natural Gas

NGr Natural Gas Restricted

NPV Net Present Value

NSEP National Sustainable Energy Policy

OCGT Open Cycle Gas Turbine

O&M Operations & Maintenance

OTEC Ocean Thermal Energy Conversion

PV Photovoltaic

RE Renewable Energy

REf Renewable Energy Forced

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan xi

SEFB Sustainable Energy Framework for Barbados Report

STEO Short Term Energy Outlook

T&D Transmission & Distribution

US$ United States Dollars

U.S. DOE United States Department of Energy

WACC Weighted Average Cost of Capital

WtE Waste to Energy

WTG Wind Turbine Generator

Existing Generating Units

CG01 1.5 MW Co-generating unit connected to units D10-D13

CG02 2.2 MW Co-generating unit connected to units D14 & D15

D10 12.5 MW Low Speed Diesel Generator






GT02 13 MW Gas Turbine Generator





S1 20 MW Steam Turbine Generator

S2 20 MW Steam Turbine Generator

Candidate Generating Technologies

Ana. Digestion Anaerobic Digester Unit

CCGT30 30MW Liquid-fueled Combined Cycle Gas Turbine

CCGT40 40MW Liquid-fueled Combined Cycle Gas Turbine

GT20 20MW Liquid-fueled Gas Turbine


Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan xii


Biomass Biomass Generating Unit

Imp Biomass Imported Biomass Fuel

L/fill Gas Landfill gas-to-energy

LSD17 17MW Low Speed Diesel Generator



MSD17 17MW Medium Speed Diesel Generator

NG-LSD17 17MW Natural gas dual-fuel LSD Generator



NG-MSD17 17MW Natural gas dual-fuel MSD Generator

NG-CCGT30 30MW Natural gas fired CCGT

NG-CCGT40 40MW Natural gas fired CCGT

NG-GT20 20MW Natural gas fired GT



Solar Solar Photovoltaic unit

WTE, WtE Waste to Energy

Wind Wind generator

Wind w/storage Wind generator with 10% battery storage

Barbados Light & Power Co. Ltd. - 2012 Integrated Resource Plan 13

1 EXECUTIVE SUMMARY

1.1 Background

The Barbados Light & Power Company Limited (BL&P) is an investor owned,

vertically integrated electric utility with a nonexclusive franchise1 for the generation,

transmission and distribution of electricity on the island of Barbados.

BL&P serves approximately 124,000 customers covering an area of 430 square

kilometres. The Company’s electricity generating portfolio consists of 239.1MW of

generating capacity made up of steam (40.0MW), low speed diesel (113.1MW) and

gas turbines (86.0MW) at three generating stations. The base load steam and low

speed diesel units operate on heavy fuel oil (HFO) and the gas turbines operate on

diesel and Jet A1. The transmission and distribution (T&D) network consists of

approximately 116 km of transmission lines operated at voltages of 24kV and 69kV,

and 2800 km of distribution lines at 11kV.

Approximately 104.5MW of existing generating capacity is scheduled for retirement

over the next ten years and electricity demand is expected to grow by an average of

around 1.2% per year. New supply and demand resources will therefore be required

to maintain supply reliability. This report identifies a 25-year resource plan to meet

Barbados’ future electricity requirements at the lowest cost while maintaining

reliability and taking into account energy security and environmental impacts.

1.2 Integrated Resource Planning

System expansion planning at BL&P has traditionally focused on identifying the

least-cost generation expansion plan from a range of generating supply options.

Integrated Resource Planning (IRP) enhances this process by taking into

1 BL&P’s current franchise expires in 2028


consideration demand side resource options as well as additional evaluation criteria

such as energy security and environmental impact.

Risk and uncertainties associated with variables like fuel price and electricity

demand growth were addressed through sensitivity and scenario analyses.

The study was conducted in accordance with IRP best practices2 and provides a

roadmap, outlining the options to be used in meeting future electricity demands in a

cost effective manner and in compliance with regulatory requirements. A

transparent and participatory approach was employed throughout the process. The

recommendations have been informed by broad consultations with stakeholders who

participated in the process by reviewing assumptions and preliminary results and

providing input into the planning decision.

The IRP was developed using models that incorporate the best information at the

time of planning and will be updated periodically or as conditions change materially.

The IRP is not an application for a review of rates or an investment plan, nor is it a

prohibition against specific third-party initiatives.

Technologies which are not technically or commercially viable and Transmission and

Distribution (T&D) expansion requirements have been excluded from the scope of

the IRP.

The Terms of Reference for the IRP is provided in Appendix A.

2 Best Practices Guide: Integrated Resource Planning For Electricity – The Tellus Institute


1.3 Sustainable Energy Framework for Barbados

In July 2010, the Government of Barbados (GoB) completed a study titled

‘Sustainable Energy Framework for Barbados’ (SEFB). The objective of the study,

which was conducted by Castalia Strategic Advisors and financed by the IDB, was to

identify viable investments in renewables and energy efficiency to reduce Barbados’

dependency on fossil fuels and thus reduce energy costs, improve energy security

and enhance environmental sustainability. These objectives were also captured in a

draft National Sustainable Energy Policy (NSEP) issued by the Government of

Barbados in March 2012.

Both the SEFB report and the draft NSEP identified indicative targets for renewable

energy (RE) and energy efficiency (EE) of 29% and 22% respectively by 2029.

BL&P’s recommended plan, described in section 1.4, achieves RE levels of 20.8%

by 2029 for the base demand forecast world. To achieve 29% RE by 2029 will

increase the NPV of the plan by 1%. The potential impact of EE measures are

accounted for in the low demand forecast world, which allows for up to 28.3%

reductions through EE by 2029.

Also arising out of the SEFB report were recommendations relating to legislative and

regulatory changes aimed at promoting the development of viable renewable energy

and energy efficiency resources. At the time of writing, the draft energy policy and

legislative changes were under review but not yet finalized by the GoB. However,

the IRP study takes the proposed changes into account and follows a methodology

which is consistent with the recommendations of the SEFB report.

1.4 Recommendation

To assess the risks and uncertainties associated with external market conditions, the

IRP study examined five scenarios representing plausible future paths relating to

fuel types and technologies used. Each of these scenarios was evaluated using

three possible electricity demand growth ‘worlds’, resulting in a total of fifteen plans


being initially evaluated. Sensitivities for changes in capital costs, fuel costs and

discount rates were also conducted on each of the fifteen plans. A sixth scenario

was also modeled in light of Government’s stated plan to commission up to 60 MW

of waste-to-energy generating capacity.

The least cost plan identified in the IRP is based on a natural gas expansion

scenario. Natural gas is however not yet available in sufficient quantities on the

island for power generation. Development work on the importation of natural gas is

in progress, but there is uncertainty as to when gas will become available. It is

therefore recommended that new generating capacity include reciprocating engines,

which have the capability of being converted to dual-fired gas operation when gas

becomes available. Further, given Government’s announcement on waste-to-energy

(WTE) as part of an integrated waste management strategy for the island, an

expansion plan that takes this development into consideration is recommended.

WTE is not selected in any of the initial five scenarios as it results in increased

electricity production costs, but the capacity announced by Government should be

factored into expansion plans to avoid potential generating overcapacity. Scenario 6

was therefore created to determine the least-cost expansion plan assuming that the

WTE is commissioned by Government in 2018.

The first ten years of the resulting least-cost plan for Scenario 6 are displayed in

Table 1 . The reciprocating units identified in this scenario should be designed to

allow for conversion to dual fired operation (HFO and natural gas) with minimum

time and effort when natural gas becomes available in the future.


Year Demand

GWh

Supply-side Resources Demand-side Resources

Retire New Capacity

2012 981

2013 980

2014 979

2015 984

2016 993 L/fill Gas –1.5 MW

Solar – 8 MW

Wind – 2 MW

2017 1005 S1, S2 – 40 MW

GT02 – 13 MW

Reciprocating Engines – 47 MW

L/fill Gas –1.5 MW

2018 1018 Biomass –25 MW

Waste to Energy – 60 MW

Wind – 1 MW

2019 1036 D10, D11, D12,

D13 – 50 MW

WH01 – 1.5 MW

2020 1054

2021 1074 Wind – 1 MW

Table 1: Scenario 6: Least-cost Integrated Resource Plan

The model assumes that all plant retirements take place at 00:00hrs on January 1st

of the years identified in the table. In practice, an overlap of around six months may

be required between retired and replacement capacity to ensure a reliable transition

and allow any ‘teething’ problems with the new plant to be addressed.

The IRP recommendations are contingent on the following:

Acquiring land access for the development of wind energy and/or successful

negotiation of Power Purchase Agreements with Independent Power

Producers (IPPs) for wind energy.

Access to a secure supply of biomass, municipal solid waste and landfill gas

at the prices used in the IRP.

Future DSM


The generating capacity and timing of waste-to-energy and biomass is

achieved. If there are variations in the scope and timing of these projects, the

retirement schedule of existing units could be affected.

Extension of BL&P’s franchise which currently expires in 2028.

Compliance with legislative requirements.

The plan laid out in Table 1 provides a roadmap of expansion options to be used in

meeting future electricity demands cost effectively, given the constraints and

assumptions used in Scenario 6. Investment plans by the utility and potential

Independent Power Producers should be guided by the IRP, while taking into

consideration licensing, land availability and location specific development costs.

Two key issues were identified during the IRP process which will require additional

work:

As identified in the IRP Terms of Reference, Demand Side Management

(DSM) options evaluated in the IRP study were to be derived from the energy

efficiency recommendations made in the SEFB study conducted by the IDB

for the Government of Barbados. However, based on subsequent feedback

received from the consultants who conducted the SEFB study, the energy

efficiency measures were found to be insufficiently well defined for modeling

in the IRP. A DSM study will be completed in 2014 to identify specific DSM

measures for implementation. It is important to note however, that the short-

term expansion recommendations (2013 to 2018) remain unchanged in the

low demand forecast world and are therefore compatible with the indicative

EE targets identified in the SEFB. It should be noted that DSM could change

the forecasted system load factor. This will be evaluated in more detail in the

forthcoming DSM study and the IRP revised accordingly.

Based on a preliminary review of system impacts and practices in other island

grids, an intermittent Renewable Energy (RE) limit of 10% of peak demand

has been used in the study. An Intermittent RE Penetration study will be


completed in 2014 to further evaluate the issues associated with intermittent

RE and allowable limits.

1.5 Structure of Report

This report consists of six chapters. Chapter 1 is the Executive Summary which

presents the background and introduction to the report and gives some detail on the

integrated resource planning process. The chapter also highlights the Sustainable

Energy Framework for Barbados and presents the recommended plan based on the

results of the study. Finally, this chapter presents the structure of the report.

Chapter 2 details the planning parameters used in the study. The economic

assumptions are presented followed by the electricity demand forecast for the

planning period. Fuel assumptions are also critical to the study being undertaken.

These are presented in this chapter. Finally, this chapter presents the system criteria

assumptions used in the study.

Chapter 3 reviews the existing and candidate technologies used in the model. The

cost and performance characteristics of the existing plant are presented followed by

similar data on the conventional generating technologies used in the study. The

chapter also presents a review of RE technologies and their present state of

development. RE technologies excluded from the study are then identified, followed

by those included in the study along with their assumed cost and performance

characteristics. The environmental assumptions for the generating technologies

used in the study are also presented. The chapter concludes with the levelized cost

for technologies included in the study.

Chapter 4 outlines the modeling methodology used in conducting the study. The

worlds and scenarios used to model the options available are presented followed by

information on how sensitivity analyses on the results were conducted. The chapter

also presents information on the software model used in the study and the decision


criteria used to evaluate the optimal plans produced by the software model. Finally,

information is presented on the decision model and software used in conducting the

decision analysis.

Chapter 5 presents the results of the worlds and scenarios modeled. Results are

presented for the five scenarios in the base, high and low electricity demand

“worlds.” This chapter also presents the sensitivity results. The results of the

decision analysis model are also presented as well as the recommended plan. The

avoided cost for technologies included in the study is also presented in this chapter.

Chapter 6 presents the conclusion and recommendations.

Appendices are provided containing further background information on study

assumptions, detailed model results, stakeholder consultations and communications.


2 PLANNING PARAMETERS

2.1 Study Horizon and Reference Year

The Integrated Resource Plan study period is 25 years, from the reference year

2012 up to and including 2036.

2.2 Economic Assumptions

2.2.1 Discount Rate

The discount rate is an important factor in determining the optimal expansion plan

due to the manner in which costs of the generation technologies are reflected in the

modeling. The discount rate used in developing the IRP is the weighted average

cost of capital (WACC) of 10% that was approved by the Fair Trading Commission

during the BL&P’s 2009 rate hearing. The real WACC of 7% was assumed for this

study and was derived using the Fisher Formula using a nominal WACC of 10% and

an expected inflation of 3%. The real discount rate of 7% was assumed for this study

and was derived using the Fisher Formula using the nominal discount rate of 10%

and an expected inflation of 3%. Sensitivity tests for the discount rate were

conducted at 5% and 9%.

All discounting was done to January 1st 2012 and all expenditures were assumed to

occur at the end of a calendar year.

2.2.2 Cost Estimates

The IRP uses real 2012 Barbados dollars (BDS$) over the period of the study, i.e.

inflation was not accounted for.


2.2.3 Capital Cost Estimates

Overnight capital cost is the cost of construction provided that no interest was

incurred during construction (i.e. cost if the project was completed "overnight"). In

reality however, the construction of new generating plant cannot be completed

overnight. In this report, the capital cost assumptions for the candidate technologies

are reported as overnight cost in keeping with industry practices while interest during

construction is accounted for in the model. The interest during construction for each

technology is dependent on the technology build time.

2.2.4 Taxes & Duties

Local taxes and duties were not included in the model. These have not been

included as the rates for taxes and duties over the planning period are unknown and

could vary over time, therefore causing distortions to the true cost of the

technologies.

2.2.5 Currency & Exchange Rates

The United States dollar and the British pound were the main currencies for which

cost estimates were denominated. The exchange rate of US$1 to BDS$2 was used

as the conversion for the United Sates dollar, while a conversion of GB£1 to

BDS$3.50 was employed as the conversion rate for the British pound.

2.2.6 Economic Growth

The impact of the growth of Gross Domestic Product (GDP) on the demand for

electricity is well accepted. The IRP assumes an average annual GDP growth of

1.6% as its base case growth rate and low and high growth case scenarios of 1%

below and above the average growth of the base scenario. The growth assumptions

are discussed further in the Demand Forecast.


2.3 Demand Forecast

The Integrated Resource Planning process requires the preparation of energy and

load demand forecasts for the planning period 2012 through to 2036 that represent

BL&P’s best estimate of the future demand for electricity within Barbados. Appendix

B –Demand and Load Forecast contains more detailed information regarding the

demand and load forecasts.

The base case annual average load forecast represents BL&P’s estimate of the

most probable outcome for load growth during the planning period and is based on

the most recent economic, demographic and weather forecasts for Barbados.

However, the actual path of future electricity demand is unlikely to follow the exact

path suggested by the base case load forecast. Therefore, two additional load

forecasts were prepared; these provide a range of possible load growths due to

economic uncertainty, electricity price changes and load variability associated with

abnormal weather. The high and low growth scenarios provide a range of possible

load growths over the planning period due to variable economic, demographic and

weather-related influences.

The demand and load demand forecast is created by developing a separate forecast

for each individual customer demand category. The major customer classes for

which demand forecasts are prepared include residential, small commercial, large

commercial & industrial and streetlights. These individual forecasts are aggregated

to provide a forecast of total demand. The total electricity demand forecast is

provided as billed and requires the addition of losses to convert this to a projection of

net system load. Loss factors are determined by BL&P’s System Planning and

Performance Department. The most recent five-year annual average energy loss

coefficient (6.8%) is multiplied by the aggregated demand forecast to derive system

load.


The forecast utilized a number of economic, weather and demographic variables as

forecast drivers within its models. Historical series for the economic variables were,

for the most part, obtained from publications of the Central Bank of Barbados and

the Barbados Statistical Service. Historical series for average daily temperatures,

the primary weather variable utilized in the models, were obtained from the

Barbados Meteorological Department. To the author’s knowledge, there exists no

local agency that develops and publishes short-term or long-term forecasts for the

variables included in the models. Forecasted values for a number of other input

variables were either developed by BL&P from national census and economic data

or obtained from publications of the International Monetary Fund (IMF).

Economic growth assumptions and expectations of normal temperatures influence

most of the individual customer class demand growth rates. In addition to the

economic and weather assumptions used to drive the base case forecast scenario,

several specific assumptions were incorporated in the forecasts for the individual

customer classes. These included assumptions related to customer growth, the

growth in the population and electricity prices.

Over the 25-year planning horizon, there could be major changes in the electric

utility industry, such as the impact of Government’s Sustainable Energy Policy,

changes to the Electric Light & Power Act, the introduction of IPP’s, energy

efficiency programmes and the potential for much higher electricity prices impacting

future electricity demand. The high degree of uncertainty associated with these

changes and the variability of the main input drivers are assumed to be reflected in

the high and low case scenarios described below.

2.3.1 Electricity Prices Variability

Fuel prices, in combination with economic drivers, impact long-term trends in

electricity demand. Changes in relative fuel prices can also have significant impacts

on the price of and demand for electricity. The US Energy Information Administration


(EIA) provides a forecast of long-term changes in nominal and real fuel prices in its

Annual Energy Outlook (AEO). Projections of long-term fuel prices relevant to BL&P

were estimated from the EIA projections after exchange rates and delivery charges

adjustments. The projected annual growth rates for the weighted average nominal

and real price of fuel over the planning period are presented in Table 2.

Nominal *Real

Fuel Prices …………………………………………... 3.2% 1.2%

*adjusted for inflation

(Average annual percent change)

Table 2: Fuel Price Escalation (2012-2036)

The impact of fuel prices on electricity prices are transmitted through the Fuel

Clause Adjustment (FCA). The Fuel Clause Adjustment is a major component of the

cost of electricity to customers and accounts for over 200% of the base rate of both

commercial & industrial and residential customers in 2011. Regression models are

used to identify the relationships between historical fuel prices and historical

movements in the price of electricity. These models are employed to project the

expected growth in the residential and large commercial & industrial electricity prices

using the fuel price projections (base, high and low scenarios) published by the EIA.

The modeling of future electricity prices assumes that price changes will mainly be

reflected in variations in the price of fuel and the mix of generation plant employed to

meet future electricity demand. The reasonableness of the electricity price forecast

was confirmed by comparing the forecasted electricity prices for the planning period

with the indicative tariff profile of the recommended plan. The electricity price

forecast and the tariff profile were found to be, on average, within 0.3% of each

other.


Figure 1: Forecasted Electricity Prices

Figure 1 illustrates the average electricity price paid by BL&P’s residential and large

commercial & industrial customers over the historical period 1986 to 2011 and over

the forecast period 2012 to 2036. Both nominal and real prices are shown. Nominal

electricity prices are expected to climb to over one dollar per kilowatt-hour (kWh) by

the end of the forecast period in 2036 from just over 62 cents per kilowatt hour in

2011 for residential customer class. The Large Commercial & Industrial price of

electricity is expected to rise from 64 cents per kilowatt-hour in 2011 to $1.14 per

kilowatt-hour at the end of the planning period. Real electricity prices (inflation

adjusted) for customers in the Residential and Commercial & Industrial customer

classes are expected to remain relatively unchanged by the end of the forecast

period. The base case scenario assumes that the average annual real growth in

electricity would be flat over the planning period. The high case annual price

increase is projected to average 0.7%, while a marginal average annual decline is

forecasted for the low case scenario (Table 3).


Scenarios

Real Average Growth Rate 2012-2036

Residential Large Industrial & Commercial

High Case …………………………………………...… 0.7% 0.7%

Base Case ………………………………………..….. 0.0% 0.0%

Low Case ……………………………………………… -0.6% -0.6%

Table 3: Electricity Price Growth Scenarios

The price of electricity and its elasticity are incorporated into the forecast models

because they measure the ratio between the demand for electricity and a change in

its price. A customer that is sensitive to price change has a relatively elastic demand

profile. Conversely, a customer that is unresponsive to price changes has a

relatively inelastic demand profile. Prior to 2008, BL&P’s customers displayed low

price sensitivity (-0.126 for residential and -0.069 for large commercial & industrial)

mainly due to infrequent base rate adjustments and relatively low volatility in the

Fuel Clause Adjustment. However subsequent to 2008, increased price sensitivity

has been observed in response to the electricity rate adjustment in 2010 and the rise

in the Fuel Clause Adjustment (-0.129 for residential and -0.111 for large commercial

& industrial).

2.3.2 Weather Variability

The future demand for electricity among BL&P’s customers is represented by three

load forecast scenarios reflecting a range of load uncertainty due to weather. The

base case load forecast assumes normal temperatures and a 50% chance that

loads will be higher or lower than the base case load due to cooler than average or

warmer than average temperatures. Since actual loads can vary significantly

depending on weather conditions, two alternative scenarios were considered that


address load variability due to temperatures within weather sensitive customer

classes (i.e., residential and large commercial & industrial classes).

Higher loads are expected when temperatures are at their highest levels, conversely

lower loads are anticipated when temperatures are at their lowest. Temperature data

obtained from the Government Metrological Department over the most recent thirty

(30) years indicates that average temperatures were 27 °C. The 90th percentile

temperature of 27.5°C represents the high case average temperature scenario and

indicates a probability of one out of ten years that this temperature would be

exceeded. The 10th percentile temperature indicates a probability of one in ten years

that the average annual temperature would fall below 26.5°C. In the high case

scenario for residential and large commercial & industrial load forecasts,

temperatures were assumed to be at the 90thpercentile of normal temperatures,

while the low case scenario assumes temperatures to be in the 10th percentile of

normal temperatures (Table 4).

Scenarios Temperature Probability

High Case (90th Percentile) 27.5 °C 1-in-10 years above

Base Case (normal temperature) 27.0°C 1-in-2 years

Low Case (10th Percentile) 26.5°C 1-in-10 years below

Table 4: Temperature Scenarios

There is some weather sensitivity within BL&P’s system load and these scenarios

allow an examination of load variability and how it may impact future resource

requirements.

2.3.3 Economic Variability

Electricity fuels a local economy that historically has been dependent on sugarcane

cultivation and related activities. However, in recent years the economy has

diversified into light industry and tourism with about three-quarters of GDP and 80%


of exports being attributed to services. The economy experienced significant growth

between 2003 and 2007 bolstered by increases in construction projects and tourism

related revenues. These sectors however registered declines at the end of 2008 with

the global economic downturn. After two years of negative growth, real GDP growth

in 2010 was a mere 0.2% and 0.5% in 2011. The economy registered no growth in

2012 as its main traded sectors were stagnant during the year.

Scenarios Average Growth

High Case …………………………………………...… 2.6%

Base Case ……………….…………………………… 1.6%

Low Case ……………………………………………… 0.6%

Table 5: Economic Growth Scenarios

Growth in electricity sales is influenced to a large extent by growth in output within

the general economy. In recent years, a high correlation has been observed

between GDP and the growth in electricity consumption, therefore periods of robust

future growth in the economy are expected to result in strong demand for electricity.

The base case load forecast is based on the most recent economic forecast for

Barbados and represents the most probable outcome for load growth during the

planning period. A forecast of economic growth for Barbados was obtained from the

Central Bank of Barbados up to 2018 and was estimated by BL&P thereafter based

on the historical distribution of growth rates. The real Gross Domestic Product

(GDP) of Barbados is projected to decline marginally by 0.7% at the end of 2013, but

is expected to grow steadily in the future to register an average annual growth of

1.6% over the planning period. The low and high growth case scenarios are 1%

below and above, respectively, the average annual growth of the base scenario

(Table 5). The distribution of GDP growth rates over the past twenty-five years

suggest that a narrow cone of ±1% growth is very realistic and appropriate over the

planning period.


2.3.4 System Load Forecast

The system load forecast was developed by applying the five-year annual average

energy loss coefficient (details provided in Appendix C) to the total demand forecast

that was derived by aggregating the individual residential, small commercial, large

commercial& industrial and streetlights forecasts (Figure 2). Current system losses

are relatively low by regional and international standards and non-technical losses

on the system are negligible. No changes to the network that would significantly

impact system losses are anticipated over the planning period. The Company will

continue to judiciously manage system losses and believes that the current five-year

average of 6.8% is a reasonable assumption for the IRP model.

Figure 2: Total Demand

In the base case scenario, BL&P’s system load is forecasted to increase from 980

GWh in the year 2012 to 1,358 GWh in 2036 (Figure 3). In the base case, system

load growth is projected to average 1.2% per year over the 25 years of the planning

period (2012–2036). In the low case load scenario, the system load is forecasted to

reach 903 GWh at the end of the planning period, while the high case load forecast

scenario is projected to reach 1,986 GWh in the year 2036 (Table 6).


Figure 3: Forecast System Load

Scenarios (GWh) 2012 2020 2028 2036 Average Growth Rate 2012-2036

High Case…………………………... 981 1,233 1,570 1,986 3.0%

Base Case………………….………. 981 1,200 1,200 1,358 1.2%

Low Case…………………………… 981 864 870 903 -0.4%

Table 6: System Load Growth

2.3.5 System Peak Forecast

The system peak load forecast was prepared in conjunction with the load demand

forecast. In the past ten (10) years, BL&P’s system peak normally occurred in the

months of May and October when average daily temperatures were generally


highest. The peak demand forecast uses statistically derived peak day temperatures

based on the most recent thirty (30) years of average daily temperatures.

BL&P’s system peak load is expected to grow to 208.1 MW in 2036 from the 2011

actual system peak of 163.0 MW. The projected growth in system peak is

considerably higher than the highest system peak on record, 167.5 MW, registered

in 2010. In the base case scenario, BL&P’s system peak increases at an average

growth rate of 1.0% per year over the 25 years of the planning period (Table 7).

Table 7: System Peak Demand Growth

2.3.6 Demand Side Management

Demand Side Management (DSM) consists of policies and measures which serve to

modify the demand for electricity. The goal of DSM initiatives is usually to influence a

reduction in the amount of energy demanded by consumers through financial

incentives, education and/or availability of more energy efficient technologies. In July

2010, the Government of Barbados published its ‘Sustainable Energy Framework for

Barbados’ (SEFB) report which identified a number of energy efficiency options for

the country by 2029. The analysis contained in the SEFB report suggested that

energy efficiency initiatives could reduce the base case load growth scenario by

22% by 2029. The impact of DSM on the future demand for electricity is considered

within the IRP by applying the energy efficiency initiatives and targets outlined in the

SEFB to the IRP’s base case load forecast scenario.

Scenarios (MW) 2012 2020 2028 2036 Average Growth Rate 2012-2036

High Case…………………………... 156.7 195.8 242.8 300.0 2.5%

Base Case…………………..……... 156.7 167.2 186.7 208.1 1.0%

Low Case…………………………… 156.7 137.9 136.3 139.2 -0.6%


Figure 4: Forecast System Load under DSM

The energy efficiency initiatives outlined within the SEFB report are highlighted in

Table 8. Total system load after adjustments for DSM initiatives targeted within the

SEFB is expected to decline to 940.3GWh by the end of 2036. The average annual

growth in the demand for electricity over the forecast period when DSM targets are

taken into account is expected to be -0.3% over the planning period (Figure 4). The

demand forecast, taking into account the targeted DSM initiatives, exceeds the low

case average system load forecast of -0.4%. The impact of DSM initiatives over the

planning period can therefore be presumed to be reflected in the low system load

growth scenario. In addition to their impact on system load, it should be noted that

DSM initiatives could have an impact on the forecasted system load factor and that

this will be evaluated in more detail in the forthcoming DSM study and in subsequent

revisions to the IRP.


• Lighting - Compact Fluorescent Lamps (CFLs) - T8 Fluorescent Lamps with Occupancy Sensor - T5 High Output Fluorescent Lamps - Street Lighting technologies (Magnetic Induction Street

Lighting, LED, and Solar LED) • Air Conditioning

- Efficient Window A/C Systems - Efficient Split A/C Systems

• Refrigeration - Efficient Residential Refrigerators - Efficient Retail Refrigerators

• Mechanical

- Premium Efficiency Motors - Variable Frequency Drives - Efficient Chillers

• Other efficient appliances

- LCD Computer Monitors - Power Monitors

Table 8: SEFB Energy Efficiency Initiatives

2.3.7 Renewable Energy Rider

In July 2010, BL&P introduced, on a pilot basis, a Renewable Energy Rider for

connection of distributed solar and wind generators. The pilot period ended in June

2012 at which time BL&P made recommendations to the regulator to make the Rider

permanent, with some modifications. In August 2013, the regulator approved the

Rider on a permanent basis with a review of the rate to be conducted every three

years. Currently, the Rider caters for a total of 7.0 MW and allows for customer-

owned solar and wind systems with maximum individual customer capacities of 1.5

times the customer’s current usage up to a maximum capacity of 150 kW.

At the end of August 2013, there were approximately 200 customers on the RE

Rider representing approximately 2.1 MW. The historical and projected growth on

the Renewable Energy Rider is shown in Table 9.


Date Renewable Energy Rider

Capacity (MW)

January 2012 0.02

June 2012 0.13

January 2013 1.0

June 2013 1.7

January 2014 2.6

January 2015 4.4

January 2016 7.0

Table 9: Renewable Energy Rider Historical and Projected Capacity

In developing the demand forecast to be used in this study, the energy generated

from the systems on the Renewable Energy Rider was not included in the demand

forecast. This is based on the assumption that these systems are used to offset

customers’ internal demand and hence would reduce the customers’ demand from

the grid. However, the energy from these systems was taken into account in

accounting for the amount of intermittent generation on the system.

2.4 Fuel Price Forecasts

For this study, two possible conventional fuel supply scenarios have been

considered: Liquid fuels (HFO, Diesel &Jet A1) and natural gas. This study also

takes into consideration biomass plant as a candidate technology; hence biomass is

treated as a fuel.

This section sets out the fuel price assumptions for both conventional and biomass

fuels that will be used in this study.


2.4.1 Liquid Fuel

2.4.1.1 Source for Liquid Fuel Projections

Projections of long-term oil prices are performed regularly by third party oil market

analyst groups and can show significant variation of results. In this report, and in line

with previous studies undertaken by BL&P, the most recent oil price forecast

produced by the U.S. Energy Information Administration (EIA) was used.

The EIA is the statistical and analytical agency within the U.S. Department of Energy

(DOE). It collects, analyzes and disseminates independent and impartial energy

information to promote sound policymaking, efficient markets and public

understanding of energy and its interaction with the economy and the environment.

The EIA publishes two reports which form the basis for the fuel price forecast:

Short-Term Energy Outlook (STEO): Energy projections for the next

eighteen (18) months, updated monthly.

Annual Energy Outlook (AEO): Projection and analysis of U.S. energy

supply, demand and prices over a 25 to 30 year period based on the EIA's

National Energy Modeling System.

The EIA’s fuel price forecasts include Reference, High and Low fuel price scenarios

which have been used in the IRP for sensitivity testing.

In addition to forecasting fuel energy prices, the EIA provides a report on the

accuracy of their forecasts in the Retrospective Review Report3. Figure

5demonstrates that the average absolute difference between the forecast and actual

projections for the first eleven (11) years, based on the AEO 1993 to 2010

projections, is less than 7%. After year eleven (11), the accuracy decreases rather

rapidly as shown in Figure 5.

3 Annual Energy Outlook Retrospective Review: Evaluation of 2011 and Prior Reference Case Projections-

March 2012- http://www.eia.gov/forecasts/aeo/retrospective/pdf/retrospective.pdf

http://www.eia.gov/forecasts/aeo/retrospective/pdf/retrospective.pdf


Figure 5: Average Absolute Difference between the Forecast and Actual Projection Based On AEO 1993

To 2010 Projections

2.4.1.2 Crude Oil Prices

The EIA’s AEO 2012 report4 has been used to forecast the crude oil prices. The

prices in the AEO 2012 reference case predicts that world prices for imported low

sulphur crude oil will increase from US$98per barrel in 2012 to approximately

US$107in 2013. The price is then projected to steadily increase through to 2036,

reaching a price of US$151per barrel by the end of the study period (all prices are

expressed in real 2012 dollars).

Due to the significant variation that can be experienced in fuel prices, the EIA also

produces high and low scenarios for fuel prices in the AEO 2012 report. The

projections for imported low sulphur crude oil are shown in Figure 6 below. Further

data can be found in Appendix E.

4 AEO 2012 Report - http://www.eia.gov/oiaf/aeo/tablebrowser/#release=AEO2012&subject=0-

AEO2012&table=12-AEO2012&region=0-0&cases=ref2012-d020112c

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Figure 6: AEO 2012 Low Sulphur Crude Oil Projections (2012 US$)

2.4.1.3 Liquid Fuel Forecast Methodology

In determining the price forecast for HFO, Diesel and Jet A1, the following

methodology was used:

The forecast for 2012 was based on the average delivery price up to

December2012.

The forecast for 2013 to 2036 was based on the AEO 2012report - June

20125. The residual oil and Jet fuel forecast was used as the basis of the

forecast.



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Crude Oil Forecast - Base Case Crude Oil Forecast - High Case Crude Oil Forecast - Low Case




A relationship was determined between the historical residual oil price and the

HFO delivered price over the period 2001 to 2011. This was used to

determine the delivered HFO price for the price forecast.

A relationship was determined between the historical Jet fuel price and the

Jet A1 delivered price over the period 2001 to 2011. This was used to

determine the Jet A1 price for the price forecast.

A relationship was determined between the historical Jet fuel price and the

Diesel delivered price over the period 2001 to 2011. This was used to

determine the Diesel price for the price forecast.

High and low fuel price scenarios published in the AEO 2012 report were

used following the above methodology to arrive at the price forecast for the

high and low fuel scenarios.

2.4.1.4 Liquid Fuel Forecast

Using the methodology outlined above, Table 10 shows the fuel price projections

derived for the base fuel price scenario. Figure 7 shows how the forecast compares

with actual historical prices for the three fuels.

Additional information related to the high and low scenarios can be found in

Appendix E.


Year

Imported Low Sulphur

Light Crude Oil HFO Price Diesel Jet A1

US$/bbl Bds$/ton Bds$/ton Bds$/ton

2012 102.50 1464 1992 2197

2013 110.32 1321 1813 2161

2014 114.73 1418 1918 2286

2015 117.90 1485 1990 2372

2016 115.38 1510 2025 2413

2017 117.02 1540 2061 2457

2018 117.68 1552 2076 2474

2019 118.59 1569 2092 2493

2020 119.74 1587 2117 2523

2021 120.84 1600 2139 2549

2022 122.33 1627 2156 2569

2023 123.39 1644 2175 2592

2024 124.41 1654 2192 2613

2025 125.39 1665 2217 2643

2026 126.17 1663 2236 2665

2027 126.87 1658 2251 2682

2028 127.78 1672 2266 2701

2029 129.42 1677 2294 2734

2030 130.88 1682 2312 2755

2031 132.39 1686 2356 2808

2032 133.58 1683 2391 2850

2033 134.85 1665 2377 2833

2034 136.31 1681 2402 2863

2035 137.54 1694 2441 2910

2036 138.78 1707 2481 2957 Note: 2012 fuel prices are based on average delivery prices

Table 10: Fuel Price Projections for Reference Fuel Price Scenario (2012 $)

Figure 7: Historical & Projected Fuel Prices - Reference Case (2012 $)


Table 11 presents the delivered fuel price projections as derived and proposed by

BL&P expressed in 2012 prices. The table sets out the projected fuel price scenarios

used in this study (base, high and low) based on the AEO2012 price projections.

Year

Base - Bds$/mmbtuLHV High - Bds$/mmbtuLHV Low - Bds$/mmbtuLHV

HFO Jet A1 Diesel HFO Jet A1 Diesel HFO Jet A1 Diesel

2012 37.14 52.62 48.51 37.14 52.62 48.51 37.14 52.62 48.51

2013 33.53 51.75 44.14 55.87 83.77 71.45 18.35 30.99 26.43

2014 36.00 54.75 46.70 58.08 84.74 72.28 18.12 30.50 26.01

2015 37.69 56.81 48.45 58.97 84.14 71.76 18.14 30.16 25.72

2016 38.32 57.80 49.30 59.47 83.65 71.34 17.87 29.93 25.53

2017 39.07 58.84 50.19 59.82 83.91 71.57 17.92 30.04 25.62

2018 39.39 59.25 50.53 60.10 83.08 70.86 17.84 29.77 25.39

2019 39.83 59.71 50.93 59.88 82.34 70.23 17.49 29.38 25.06

2020 40.27 60.44 51.55 59.32 82.50 70.36 17.07 28.94 24.68

2021 40.60 61.06 52.08 59.37 82.45 70.32 17.13 28.96 24.70

2022 41.28 61.54 52.48 59.60 84.78 72.31 17.26 29.10 24.82

2023 41.72 62.09 52.95 59.70 85.10 72.58 17.79 30.07 25.65

2024 41.98 62.58 53.38 59.59 85.12 72.59 17.95 30.28 25.83

2025 42.25 63.29 53.98 59.75 85.65 73.05 18.12 30.59 26.09

2026 42.19 63.84 54.45 59.80 85.65 73.05 18.57 31.28 26.67

2027 42.08 64.25 54.80 60.02 85.91 73.27 18.67 31.49 26.86

2028 42.43 64.69 55.18 60.16 85.93 73.29 18.63 31.61 26.96

2029 42.57 65.49 55.86 60.54 86.30 73.60 18.54 31.84 27.16

2030 42.69 65.99 56.28 60.34 86.30 73.60 18.44 31.90 27.20

2031 42.79 67.25 57.35 60.95 87.24 74.40 18.59 32.16 27.43

2032 42.72 68.26 58.21 60.89 87.34 74.49 18.59 32.34 27.58

2033 42.25 67.85 57.87 60.40 87.31 74.46 18.42 32.69 27.88

2034 42.67 68.57 58.49 60.73 87.77 74.85 18.41 33.03 28.17

2035 43.00 69.69 59.44 60.56 88.05 75.10 18.26 33.35 28.44

2036 43.33 70.83 60.41 60.39 88.33 75.34 18.11 33.67 28.72

Table 11: Liquid Fuel Price Forecast Scenarios (2012 $)


2.4.2 Natural Gas

The Government of Barbados (GoB) has stated its intent to supply natural gas to the

island in order to assist in the reduction of the national fuel bill. The GoB has been in

negotiation with the Government of Trinidad and Tobago (GoTT) regarding the

supply of gas via an undersea pipeline. Other methods by which natural gas can be

delivered to the island are LNG tanker and CNG tanker. The forecast prepared for

this study is not based on any single transport method. A range of natural gas prices

is presented based on current available information and is wide enough to cover any

of the three transportation methods.

While there are well established global price benchmarks for crude oil like WTI and

Brent, there is no equivalent “global” index for natural gas. This is partially due to the

relatively expensive and dedicated infrastructure generally required to either pipe,

liquefy or compress the gas. Consequently, gas prices in the three major regional

gas consuming markets - US, Europe and Asia - tend to be driven by energy price

references within their own regions and vary widely. In the US, gas prices are

referenced to the Henry Hub index whereas in Japan, the world’s largest LNG

importer, prices are indexed to a basket of imported crudes. Increasing supplies of

shale gas in the US have significantly depressed the Henry Hub price of gas in that

market. However prices in Europe and Asia are significantly higher, as shown in

Figure 8.

At the time of writing this report, the source of natural gas for Barbados is likely to be

Trinidad & Tobago (T&T) which is located approximately 180 miles south-west of

Barbados. T&T currently exports all of its gas as LNG at prices that are typically

based on medium to long-term gas contracts held between Atlantic LNG, the lone

LNG producer, and its suppliers and customers. These contracts are confidential

and therefore not accessible; however, a ‘Net Back’ pricing mechanism is used in

which all parties in the value chain share in the end market value of gas. T&T makes

use of spot market based trading to diversify its LNG export markets and benefit


from higher prices in regions other than the US. In 2012, approximately 75% of its

LNG exports were to Europe, Asia, Latin America and the Caribbean.

Current pricing information suggests that the price of imported natural gas from T&T

will likely be linked to a crude oil price index. Consequently, the escalation rates

used for natural gas in this study are the escalation rates for crude oil as projected in

the AEO 2012 report.

Figure 8: World LNG Estimated November 2013 Landed Prices in US$/mm Btu (Source: Waterborne

Energy Inc. Data, October 2013)

For the purpose of this study, it is assumed that natural gas would be available from

January 1st 2017. The maximum off-take was assumed to be 28 mmscf/day.

2.4.2.1 Natural Gas Pricing Methodology

Based on current information, the delivered natural gas price is expected to

comprise fixed and variable cost components. Fixed cost includes costs for transport

and maintenance of transport infrastructure while variable cost refers to the actual

cost of the gas.


The gas pricing assumptions used are based on the most current pricing information

provided by proponents of the various transportation modes, with the gas pipeline

company being the most advanced at the time of preparing the report.

In determining the price forecast for natural gas, the following methodology was

used:

Based on the best estimates available, a fixed cost of $128,762,000 was used

in the base case for this study.

A fixed cost of $178,286,000 was used in the high case.

A fixed cost of $99,048,000 was used in the low case.

Based on the best estimates available to BL&P regarding natural gas prices,

a base gas price of $11.93/ mmBtuLHV was used in the study.

A high gas price of $16.51/ mmBtuLHV was used.

A low gas price of $9.17/ mmBtuLHV was used.

The real year-on-year escalation rates based on the projections of the crude

oil forecast in the AEO 2012 report6was used to escalate gas prices

throughout the forecast.

2.4.2.2 Natural Gas Price Forecast

Using the methodology outlined above, Table 12 and Figure 9 show the natural gas

price projections for the base, high and low scenarios without the fixed cost.






Year

Bds$/mmbtuLHV

Year

Bds$/mmbtuLHV

Base High Low Base High Low

2012 2025 13.18 18.25 10.14

2013 2026 13.28 18.38 10.21

2014 2027 13.36 18.50 10.28

2015 2028 13.46 18.64 10.36

2016 11.93 16.51 9.17 2029 13.63 18.87 10.48

2017 12.22 16.92 9.40 2030 13.77 19.07 10.60

2018 12.33 17.08 9.49 2031 13.91 19.26 10.70

2019 12.45 17.24 9.58 2032 14.04 19.44 10.80

2020 12.60 17.45 9.69 2033 14.16 19.60 10.89

2021 12.73 17.63 9.79 2034 14.30 19.80 11.00

2022 12.87 17.82 9.90 2035 14.42 19.97 11.09

2023 12.98 17.97 9.98 2036 14.54 20.13 11.18

2024 13.08 18.11 10.06

Table 12: Natural Gas price Forecast Scenarios without Fixed Costs (2012 $)

Figure 9: Natural Gas Price Forecast without Fixed Costs (2012 $)

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Natural Gas Forecast - Base Case Natural Gas Forecast - High Case Natural Gas Forecast - Low Case


2.4.3 Biomass

Biomass burning plant is one of the candidate technologies considered in this study.

Consequently, a forecast of biomass prices was prepared. Indications currently

suggest that biomass can either be obtained locally or imported. Local biomass will

consist of bagasse, which is one of the by-products of the sugar production process,

supplemented with Leucaena (referred to locally as “river tamarind”) which is not

currently purpose-grown. Biomass could also be imported in the form of pellets or

wood chips. Current estimates show that the delivered cost of imported biomass is in

the range of three to five times the projected cost for local biomass, largely due to

transportation costs.

2.4.3.1 Local Biomass Pricing Methodology

In determining the price forecast for local biomass, the following methodology was

used:

Based on the best estimates available to BL&P regarding local biomass

prices, a base price of $6.72/ mmBtuLHV was used in the study.

A high price of $8.06/ mmBtuLHV was used in the study.

A low price of $5.38/ mmBtuLHV was used in the study.

The real year-on-year escalation rates were based on the projections of the

crude oil forecast in the AEO 2012 report7.

2.4.3.2 Local Biomass Price Forecast

Using the methodology outlined in section 2.4.3.1, Table 13 and Figure 10 shows

the local biomass price projections for the base, high and low scenarios.






Year

Bds$/mmbtuLHV

Year

Bds$/mmbtuLHV


2012 6.72 8.06 5.38 2025 9.40 11.28 7.52

2013 7.36 8.83 5.89 2026 9.47 11.36 7.58

2014 7.87 9.44 6.29 2027 9.53 11.44 7.62

2015 8.29 9.95 6.63 2028 9.60 11.52 7.68

2016 8.51 10.21 6.81 2029 9.72 11.66 7.78

2017 8.72 10.46 6.97 2030 9.82 11.79 7.86

2018 8.80 10.56 7.04 2031 9.92 11.90 7.94

2019 8.88 10.66 7.11 2032 10.01 12.01 8.01

2020 8.99 10.78 7.19 2033 10.10 12.12 8.08

2021 9.08 10.90 7.26 2034 10.20 12.24 8.16

2022 9.18 11.02 7.34 2035 10.28 12.34 8.23

2023 9.26 11.11 7.40 2036 10.37 12.44 8.30

2024 9.33 11.20 7.46

Table 13: Local Biomass Price Forecast Scenarios (2012 $)

Figure 10: Local Biomass Price Forecast (2012 $)

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

16.00

18.00

20.00

2012 2017 2022 2027 2032 2037

Lo

ca

l B

iom

ass P

rice

Fo

reca

st ($

/mm

btu

)

Year

Biomass Forecast - Base Case Biomass Forecast - High Case Biomass Forecast - Low Case


2.4.3.3 Imported Biomass Pricing Methodology

In determining the price forecast for imported biomass, the following methodology

was used:

Based on market prices for wood pellets, a base price of US$150 /ton, high

price of US$175 /ton and low price of US$125 /ton were used in determining

delivered biomass prices.

Transportation costs were determined based on the wood pellets being

supplied in 40 ft. containers.

Based on the best information available to BL&P regarding imported biomass

prices, a base price of $26.79/ mmBtuLHV was used in the study.

A high price of $30.04/ mmBtuLHV was used in the study.

A low price of $23.54/ mmBtuLHV was used in the study.

The real year-on-year escalation rates were based on the projections of the

crude oil forecast in the AEO 2012 report8.

2.4.3.4 Imported Biomass Price Forecast

Using the methodology outlined in section 2.4.3.3, Table 14 and Figure 11 show the

imported biomass price projections for the base, high and low scenarios.






Year

Bds$/mmbtuLHV

Year

Bds$/mmbtuLHV


2012 26.79 30.04 23.54 2025 37.49 42.04 32.95

2013 29.33 32.89 25.78 2026 37.75 42.33 33.17

2014 31.37 35.17 27.56 2027 38.00 42.61 33.39

2015 33.07 37.08 29.06 2028 38.29 42.94 33.65

2016 33.92 38.03 29.80 2029 38.76 43.46 34.06

2017 34.76 38.98 30.54 2030 39.17 43.92 34.42

2018 35.07 39.33 30.82 2031 39.55 44.35 34.75

2019 35.42 39.71 31.12 2032 39.92 44.76 35.08

2020 35.83 40.18 31.48 2033 40.26 45.15 35.38

2021 36.20 40.59 31.81 2034 40.67 45.60 35.74

2022 36.61 41.05 32.16 2035 41.01 45.98 36.03

2023 36.91 41.38 32.43 2036 41.35 46.36 36.33

2024 37.21 41.72 32.69

Table 14: Imported Biomass Price Forecast Scenarios (2012 $)

Figure 11: Imported Biomass Price Forecast (2012 $)

20.00

25.00

30.00

35.00

40.00

45.00

50.00

2012 2017 2022 2027 2032 2037

Imp

ort

ed

Bio

ma

ss P

rice

Fo

reca

st ($

/mm

btu

)

Year

Imported Biomass Forecast - Base Case Imported Biomass Forecast - High Case Imported Biomass Forecast - Low Case


2.4.4 Landfill Gas

Reciprocating engines burning landfill gas is one of the candidate technologies being

considered in this study. At this time however, no indication is available of the price

that would be charged for landfill gas. Consequently, no cost was attributed to the

landfill gas used in this study. Further information on landfill gas costs would be

needed for additional analysis.

2.4.5 Calorific Values

Table 15 shows the Lower Heating Values (LHV) calorific values for all the fuels

considered that were used in determining the fuel forecast for this study.

Fuel

Calorific Values

(LHV) Units

Bunker C 17591 Btu/lb

Diesel 18337 Btu/lb

Jet A1 18639 Btu/lb

Natural Gas 38314 Btu/cu.m.

Biomass – Bagasse 3611 Btu/lb

Biomass - River Tamarind 5311 Btu/lb

Biomass - Imported Wood Pellets 7290 Btu/lb

Table 15: Calorific Values Used In Study

2.5 System Criteria

2.5.1 System Reliability

The reliable operation of the electric power grid is critical to any country’s economic

and social welfare. The cost of an electricity outage to an economy is normally a

multiple of the cost of electricity that would otherwise have been supplied during that

outage (Khatib, 2003).Setting too low a reliability target during the resource planning

process will lead to under-investment in generating capacity, low generating reserve

margins and increased economic costs to the country from electricity outages.

Conversely, too high a reliability target leads to over-investment and increased


operating costs which translate to higher costs to customers. An efficient reliability

target is therefore one where the benefits from improved reliability are balanced by

the cost of providing that additional reliability.

Electricity reliability can be defined in a number of ways, but for the purpose of the

IRP, it is considered to be the adequacy of electrical generating capacity to meet

system electricity demand at specified voltages and frequency. In this context, the

reliability of the electric power system is established by ensuring that there is

sufficient generating reserve capacity to meet the system demand in the event of a

generator failure or other supply disruption.

There are three common measures of reliability used in electricity system planning:

Largest Unit Contingency – Additional generating capacity is installed to

ensure that single or double contingency criteria is satisfied, i.e. electricity

service is uninterrupted in the event of the single largest generator (N-1) or

two largest generators (N-2) being out of service.

Reserve Margin - This is the difference between the installed generating

capacity and the capacity required to meet the peak demand, expressed as a

percentage of the peak demand. A minimum reserve margin is set at which

new generating capacity is required.

Loss of Load Probability (LOLP) – This is the probability that the system

demand will exceed the generating capacity during a given period. It is often

expressed as the number of days per year in which the peak demand is

expected to exceed the available generating capacity, which is more

accurately referred to as Loss of Load Expectation (LOLE). The two terms

are, however, often used interchangeably. LOLP takes into consideration the

stochastic nature of system behaviour, and therefore provides a more robust

measure of system reliability than the previous two deterministic measures.


BL&P has historically used a reliability standard of one (1) day per year LOLE for

expansion planning. The relationship between LOLE and reserve margin is not linear

and varies depending on the number, size and operating performance

characteristics of the generating units installed on the system. Based on a review of

past expansion studies and the characteristics of existing plant, the one (1) day per

year LOLE standard has been found to be approximately equivalent to a reserve

margin limit of 32% for BL&P’s system.

Table 16 summarizes the electricity planning reliability criteria used in a number of

countries regionally and internationally.

At the time of preparing the IRP report, the Plexos software that was used to model

the system was capable of reporting LOLP for the expansion plans but could only

optimize on reserve margin. A minimum reserve margin of 32% was therefore used

in the IRP study as the reliability standard for expansion modeling and simulation.

The LOLP for the optimized plans were subsequently reviewed for compliance with

the one (1) day per year LOLP standard.


Reliability Criteria

Country LOLP Reserve

Margin (%) Loss of

Unit References

USA / Canada 2.4 hours/year

PJM Interconnection (October 2003)

Curacao 3.0

Carilec (2010)

Hawaii 5.3 hours/year

HECO (February 2011)

Ireland 8.0 hours/year

EirGrid (January 2013)

Trinidad 12.0hours/year

Clarke (2010)

Barbados 1 day/year 32% *

Jamaica 2 days/year 25%

Argonne National Laboratory (July 1999)

Belize 48 hours/year 20%

Carilec (2010)

Bermuda

N-3 Carilec (2010)

Cayman Islands

N-3 Carilec (2010)

St. Lucia

N-2 Carilec (2010)

Dominica

N-2 Carilec (2010)

Grand Bahamas

N-2 Carilec (2010)

Bangladesh 192 hours/year

Bangladesh Power Development Board

Kenya 240hours/year

Republic of Kenya (March 2011)

* Minimum reserve margin derived from past expansion studies using an LOLP of 1 day per year

Table 16: Generation Reliability Standards in Select Countries

2.5.1.1 Evaluation of Reliability Criterion

Reliability standards are often based on past practice and general notions regarding

the quality of service that would be acceptable to electricity users. However, as

described in section 2.5.1, an optimal reliability level is achieved when the marginal

benefits of providing improved reliability is equal to the marginal cost of expansion.

The cost of improving reliability can be determined by comparing the cost of

expansion plans at varying levels of target reserve margins. The benefits of

improving reliability are more difficult to determine, but can be estimated by

multiplying the reduction in unserved energy, resulting from the improved reserve

margin target, by the estimated Cost of Unserved Energy.


The Cost of Unserved Energy (COUE) is a difficult number to estimate, but a

methodology for doing so and an estimate for Barbados is presented in Appendix F.

The unserved energy at different levels of reserve margin were calculated in the

planning model and a summary of the costs and benefits for increasing levels of

reserve margin, based on the $5 per kWh COUE estimate derived in Appendix F,

are presented in Table 17. Plotting the unserved energy against the reserve margin,

the equation that best represented the relationship between reserve margin and

unserved energy was determined and used to estimate the unserved energy and

hence the cost of unserved energy for other reserve margin levels. Similarly, a plot

of NPV of the plan against reserve margin was created and the equation that best

represented the relationship between reserve margin and NPV determined and used

to estimate the NPV for different reserve margins.

The optimal reserve margin is represented by the point at which the net benefit of

the reserve margin improvement equals zero, i.e. when the marginal benefits and

costs of improving reliability are equal. The results are graphically presented in

Figure 12.

The results suggest that the optimal reserve margin for the system is around 38%.

The results presented in Table 17 are indicative, as COUE cannot be measured

directly and will vary significantly by type of customer and outage timing.


Table 17: Cost/Benefit Analysis of Generation Reliability

Actual Estimate Actual Estimate

15 25.098 24.767 123,834 4,698,797 4,715,023 4,838,857

16 23.301 116,506 7,328 4,716,341 1,318 6,010 4,832,847

17 21.922 109,611 6,894 4,717,685 1,343 5,551 4,827,296

18 20.625 103,125 6,486 4,719,054 1,369 5,117 4,822,178

19 19.404 97,022 6,103 4,720,448 1,394 4,708 4,817,470

20 18.256 91,281 5,741 4,721,868 1,420 4,322 4,813,149

21 17.176 85,879 5,402 4,723,313 1,445 3,956 4,809,193

22 16.159 80,797 5,082 4,724,784 1,471 3,611 4,805,581

23 15.203 76,016 4,781 4,726,281 1,496 3,285 4,802,297

24 14.303 71,517 4,498 4,727,803 1,522 2,976 4,799,320

25 14.253 13.457 67,285 4,232 4,711,412 4,729,350 1,547 2,685 4,796,635

26 12.661 63,303 3,982 4,730,923 1,573 2,409 4,794,227

27 11.911 59,557 3,746 4,732,522 1,598 2,148 4,792,079

28 11.315 11.207 56,033 3,524 4,714,032 4,734,146 1,624 1,900 4,790,179

29 10.543 52,717 3,316 4,735,795 1,649 1,666 4,788,512

30 9.919 49,597 3,120 4,737,470 1,675 1,445 4,787,067

31 9.332 46,662 2,935 4,739,170 1,700 1,235 4,785,833

32 9.153 8.780 43,901 2,761 4,718,056 4,740,896 1,726 1,035 4,784,798

33 8.261 41,303 2,598 4,742,648 1,751 846 4,783,951

34 7.772 38,859 2,444 4,744,425 1,777 667 4,783,284

35 6.324 7.312 36,559 2,300 4,722,723 4,746,227 1,802 497 4,782,787

36 6.879 34,396 2,163 4,748,055 1,828 336 4,782,451

37 6.472 32,361 2,035 4,749,909 1,853 182 4,782,269

38 5.881 6.089 30,446 1,915 4,727,347 4,751,788 1,879 36 4,782,233

39 5.729 28,644 1,802 4,753,692 1,904 (103) 4,782,336

40 5.390 26,949 1,695 4,755,622 1,930 (235) 4,782,571

41 5.071 25,354 1,595 4,757,577 1,955 (361) 4,782,932

42 5.482 4.771 23,854 1,500 4,734,931 4,759,558 1,981 (481) 4,783,412

43 4.488 22,442 1,412 4,761,565 2,006 (595) 4,784,007

44 4.223 21,114 1,328 4,763,597 2,032 (704) 4,784,711

45 3.973 19,865 1,249 4,765,654 2,057 (808) 4,785,519

46 3.738 18,689 1,176 4,767,737 2,083 (907) 4,786,426

47 3.517 17,583 1,106 4,769,846 2,108 (1,002) 4,787,429

48 3.309 16,543 1,041 4,771,980 2,134 (1,093) 4,788,522

49 3.113 15,564 979 4,774,139 2,159 (1,181) 4,789,703

50 2.929 14,643 921 4,776,324 2,185 (1,264) 4,790,967

Total Cost

($'000)

Net benefit

($'000)

Reserve

Margin (%)

CUM PV of Unserved

Energy (GWh)Cost of

unserved

Energy ($'000)

Delta Cost to

Economy

($'000)

Delta Annual

Cost ($'000)

CUM PV of Annual Costs

($'000)


Figure 12: Marginal & Total Costs vs. Reserve Margin

Figure 13: Reserve Margin for Recommended Plan

500

1,500

2,500

3,500

4,500

5,500

6,500

7,500

8,500

4,750,000

4,760,000

4,770,000

4,780,000

4,790,000

4,800,000

4,810,000

4,820,000

4,830,000

4,840,000

15 20 25 30 35 40 45 50

Mar

gin

al c

ost

of

Un

serv

ed E

ner

gy, E

xpan

sio

n P

lan

($

'00

0)

Tota

l Co

st (

$'0

00

)

Reserve Margin (%)

Total Cost ($'000)

Marginal Cost of Unserved Energy ($'000)

Marginal Cost of Expansion Cost ($'000)

0

10

20

30

40

50

60

70

80

90

0

0.5

1

1.5

2

2.5

3

Cap

acit

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ese

rve

Mar

gin

(%

)

LOLE

(d

ays)

Year

Annual Maximum LOLE (days)

LOLE Target

Capacity Reserve Margin (%)


2.5.1.2 Reserve Margin Criteria

Based on the foregoing, the 32% minimum reserve margin used in the IRP study

was considered reasonable. The actual reserve margins for the recommended plan

remain over 40% between 2016 and 2021, as shown in

Figure 13, since expansion in these early years is driven by the cost minimization

objective of the IRP rather than the 32% minimum reserve margin constraint. The

short-term recommendations are therefore not sensitive to changes in the reserve

margin constraint between 30% and 40%.

No upper limit was placed on the reserve margin, thereby allowing the model to

determine the least cost solution without constraints on the maximum allowable

reserve margin. Consequently, reserve margins of as much as 92% were observed

in some scenarios.

To analyze the impact of an upper limit on the reserve margin, scenario 3 (LF + NGr

+ RE) in the base case was used to determine the impact on the plan net present

value with an upper reserve margin of 55%. Table 18 shows the reserve margin for

this scenario with and without the upper limit on reserve margin. The net present

value for the plan without the upper limit is $4.213 billion while that for the plan with

the upper limit is $4.248 billion. Consequently, it can be concluded that if an upper

limit is set on the reserve margin, the overall cost of the plan would increase. For this

reason, no upper limit was set on the reserve margin in the model.


Table 18: Comparison of impact of upper limit on reserve margin

2.5.2 System Stability

2.5.2.1 Intermittent Renewable Energy There is no inherent energy storage capacity in electric grids. Electricity demand

must therefore be instantaneously matched by electricity generation in order to

maintain a stable system frequency. BL&P operates with a minimum spinning

reserve requirement of 5MW to cater to small supply/demand imbalances associated

with system faults, and employs an under-frequency load-shedding scheme to

prevent system overloads and grid collapse in the event of significant generation

Capacity Reserve

Margin (%) LOLP (%)

Capacity Reserve

Margin (%) LOLP (%)

2012 37.3 0.205 37.3 0.205

2013 37.9 0.205 37.9 0.205

2014 37.4 0.205 37.4 0.205

2015 37.7 0.205 37.7 0.205

2016 36.2 0.252 36.2 0.252

2017 85.3 0.000 54.6 0.145

2018 84.4 0.000 53.9 0.008

2019 53.6 0.008 43.9 0.052

2020 51.3 0.011 51.4 0.012

2021 48.9 0.016 49.0 0.016

2022 40.4 0.089 40.6 0.082

2023 38.5 0.115 38.7 0.113

2024 36.7 0.154 46.3 0.020

2025 33.3 0.298 33.5 0.292

2026 32.5 0.307 32.6 0.318

2027 38.7 0.059 36.2 0.140

2028 35.8 0.097 33.3 0.189

2029 33.8 0.127 32.1 0.265

2030 32.8 0.133 39.6 0.047

2031 39.6 0.034 37.7 0.075

2032 37.8 0.043 36.0 0.092

2033 36.0 0.064 34.2 0.149

2034 34.2 0.090 32.4 0.156

2035 32.3 0.107 38.5 0.0332036 33.5 0.141 33.3 0.141

Without Upper Limit With Upper Limit of 55%

Datetime


losses. High penetrations of intermittent RE resources present reliability and stability

challenges for small island grids which lack the interconnections and ‘infinite’ grid9

characteristics typical of utilities on continents. The primary issues introduced by

high intermittent RE levels involve the magnitude and distribution of spinning

reserves/operating reserves across conventional generating units, unit ramping and

cycling capabilities, limitations of existing unit control systems, voltage control and

maintenance scheduling considerations.

Studies on other island grids have indicated that for high intermittent RE penetration

levels, additional reserves of up to 30% of the intermittent RE capacity may be

required to provide capacity reserves for contingency conditions (BEW Engineering,

2012).

The capability of conventional generating units to ramp up and down as the RE and

customer load varies is another issue. For example, wind speed data collected by

BL&P shows the average hourly up ramp at 55% of the wind turbine capacity and a

down ramp at 74%. In other words, if BL&P installed 20 MW of wind turbine

capacity, the hourly up ramp could be as high as 11 MW, while the down ramp could

be 15 MW, excluding ramping for load variability. The exact ramping requirement

could be lower due to the diversity and distribution of the wind turbine installations

over the land space. This will have to be modeled in a stability study taking into

account the distribution of RE at various substation buses. On the other hand, the

generators need to respond to variations in seconds and minutes, so the ramping

may be higher than the average hourly values. Consequently, the high ramping of

wind turbines may require modifications to the conventional generating units’ control

systems to increase unit response times. The control systems for certain RE

systems may also be required to meet prescribed design criteria.

9An ‘infinite” grid is one which has a capacity that is infinite in comparison to the individual generator capacities on the grid.


Similarly, short term variations in solar PV output must also be smoothed out by

conventional generators or storage technologies to maintain system stability. Figure

14shows an example of solar PV output and system electricity demand, expressed

on a per-unit basis, for one-minute intervals on March 15th2013. The aggregate

output of multiple solar PV systems spread across the island is expected to exhibit

less variability, however further research will be required to determine the smoothing

effect of geographic diversity.

Storage technologies have been explored with a view to understanding how these

technologies can be deployed to (i) absorb excess energy supplied by the distributed

RE; (ii) cope with fast balance or imbalance changes and (iii) provide ride through

between the failure of the utility grid and startup of a backup generator. These are

described in section 3.2.3.11.

Other critical issues are voltage, frequency, flicker, harmonics and transient and

dynamic stability under various contingency conditions. Rapid change in wind or

solar generation may cause a sudden change in voltage and frequency as the

generating units are ramping up or down. This can cause existing solar inverters

and wind turbines to trip off line which causes the system condition to become more

unstable.


Figure 14: Comparison of Typical Daily Electricity Demand and Solar PV Output

The final issues relate to maintenance scheduling of generating units and

transmission/distribution switching routines. Depending on the penetration of RE

resources, maintenance scheduling of conventional generating units may need

modifications. The season of the highest RE variability may impact the scheduling

since specific units, as determined by a stability study, will be required to be on-line

during these periods. Also, time periods having minimum wind generation require

units to remain on-line and alter maintenance scheduling. Utilities have discovered

that the old, existing scheduling routines of transmission and distribution circuits may

not be adequate for high RE penetrations.

2.5.2.2 Intermittent RE Limit

The type of analyses required to determine potential penetrations limits depend on

the RE resource types and location. For high penetrations of distributed RE, the

analysis must begin at the distribution level. The distributed RE resources could be

central plant (connected to the distribution feeder directly) or a customer owned RE

system like those existing on BL&P’s RE Rider behind the meter. Connecting RE

alters loss performance of distribution networks. Small penetrations of RE tend to

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

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6:0

0 A

M

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0 A

M

8:0

0 A

M

9:0

0 A

M

10

:00

AM

11

:00

AM

12

:00

PM

1:0

0 P

M

2:0

0 P

M

3:0

0 P

M

4:0

0 P

M

5:0

0 P

M

6:0

0 P

M

7:0

0 P

M

1-Minute System Demand & Solar PV Output

Per UnitSystemDemand

Per UnitSolar PVOutput


reduce network power flows and thus reduce losses. When RE penetration is high

then there will be power export to the grid which may cause an increase in losses.

The distribution feeders will have to be studied first, to determine the maximum

distributed RE that can be connected to the individual feeders and to the substation.

Some island utilities, such as Hawaii, have set 15% of each individual feeder peak

demand as the maximum trigger value before conducting detailed transient and

dynamic stability studies to determine the maximum penetration value that can be

connected to the feeder. When a proposed single or multiple RE installation has a

generating capacity that exceeds the trigger value, a detailed study must be

conducted to determine the potential impact to the feeder and the mitigation

measures. The individual maximum peak demands are non-coincident between

feeders. This is an important factor when studying individual feeders and total

system RE penetrations. In either case, the determination of the maximum feeder

RE penetration is determined through distribution feeder studies.

If a substation has multiple feeders, the summation of the individual feeder limits

does not always equal the substation limit. The substation limit could be lower than

the summation of the individual feeder limits. The substation or system total peak

demand is a coincident peak, while the individual feeder peaks are non-coincident

peak demands. The entire substation and feeders must be studied to determine

potential substation transformer tap changer impacts or voltage issues on adjoining

feeders connected to the same common bus. This analysis must be conducted for

all feeders and substations on the island utility. Given these results, a study of the

relay protection is then required to determine if the relays will operate correctly under

different contingency and feeder switching routines.

After conducting the feeder analysis, the transmission system must be studied. The

projected distributed RE resources are added to the transmission power flow base

case and different transmission system RE penetrations are developed and studied.


These studies are normally conducted for the system peak time, maximum daytime

peak demand and the minimum peak demand. This sets the limits for penetrations

on the transmission grid. The transmission and distribution penetrations may not be

coincident in time so adjustments must be made to the final limitations. For the

Hawaiian utilities of HECO, MECO and HELCO, the total system RE penetration

limit is currently set to 20% of the system coincident peak demand. When this

limitation is reached, then the Hawaiian utilities must conduct a detailed study to

determine the upper level of potential RE penetration.

The foregoing analyses focus on load flow analysis and relay protection. Production

cost analysis must also be considered to determine the impacts to the conventional

generating units on the system. The production cost analysis determines the

reserve requirements, ramping requirements, fuel usage, start-up costs, emissions

and other factors. The final RE resource penetration is derived from the various

studies described above, and is likely to result in a mixture of individual feeder,

transmission and system limitations.

BL&P will be conducting an Intermittent RE Penetration study for Barbados in 2013.

In the interim, an intermittent RE penetration limit of 10% of the annual peak demand

was used in the recommended plan. Based on internal analyses, this penetration

level is not expected to cause stability problems or require additional spinning

reserve. It is also consistent with intermittent RE levels existing in other island

states, as summarized in Table 19.


Table 19: Intermittent RE Penetration Levels on Other Island Grids

2.5.2.3 Largest Generating Unit

The level of system overload experienced when a generator trips, is directly

proportional to the size of the generator. Generators which are very large relative to

overall system demand create system overload conditions, when they trip, that could

lead to system instability and outages.

This has been the BL&P’s experience, where trips of unit sizes greater than 20% of

peak load have resulted in major operational challenges on BL&P’s grid. This is

exacerbated at minimum load demands. For example, using this criterion for a peak

of 160 MW, the maximum unit size allowed for selection would be 32 MW which

would represent 36% of a system minimum load of 90 MW.

Based on past operating experience, in order to maintain frequency stability, BL&P

determined that the maximum generating unit size on the network should not exceed

20% of the projected peak demand. Consistent with previous expansion studies, the

maximum allowable individual generating unit size was set at 20% of the projected

peak demand.

Intermittent RE

Penetration(% of peak

demand)

Maui 30 4.6 204 17% YesHawaii DEBDT (2012);

HECO (2010)

Hawaii 31 6.8 203 19% YesHawaii DEBDT (2012);

HECO (2010)

Crete 106 0 605 18% No Karapidakis (2011)

Mauritius 39 0 389 10% No Castalia (2011)

Jamaica 38 0 644 6% No Jamaica OUR (2010)

ReferencesIsland

Wind

Penetration

(MW)

Distributed

RE

Penetration

(MW)

Peak

Demand

(MW)

Storage

Installed


2.5.2.4 Generation Spinning Reserve

Generating Spinning Reserve is the on-line generating reserve capacity which is

available to maintain balance between electricity supply and demand in emergency

situations.

In 2000, BL&P conducted a spinning reserve study to determine the appropriate

spinning reserve that should be maintained on the system. The study concluded that

the optimal spinning reserve on BL&P’s current system was between 2MW and

6MW depending on the system demand, with the higher end of the range required

for lower system demands. In practice, BL&P maintains a minimum spinning reserve

of 5MW throughout the day for operational flexibility and security. For this study, the

minimum spinning reserve requirement was set to 5MW.

In the model, spinning reserve is specified as a constraint that must be satisfied at

every hour over the planning period. To analyze the impact of increased levels of

spinning reserve on the model, the spinning reserve requirement was increased

from 5MW to 10MW on the recommended plan. For a spinning reserve of 5MW the

net present value of the plan over the planning horizon was $4.741 billion while the

net present value for 10MW was $4.779 billion. In addition, the build schedule for the

two levels of spinning reserve also changed due to the need to have additional

capacity available to supply this requirement.


3 GENERATING TECHNOLOGIES

3.1 Existing Plant

The existing generating system comprises three power stations, these are: Spring

Garden, Seawell and Garrison Hill. A brief overview of the existing generating

stations is provided in the following subsections.

3.1.1 Spring Garden Generating Station

The Spring Garden generating station was first developed in 1967. This station is the

main generating station for the Barbados system and is the location for the

Generation Central Control Room. With the addition of the Low Speed Diesel Station

‘B’ in 2005, BL&P has determined that the site cannot accommodate any more units

without the retirement of existing units. The administrative offices of the Generation

Department are also located on this site.

The site is divided into three main stations; Steam Station (Units S1 & S2); Low

Speed Diesel Station ‘A’ (Units D10-D13) and the new Low Speed Diesel Station ‘B’

(Units D14 & D15) commissioned in 2005. One gas turbine unit (GT01) is also

located at this site but has been officially retired. Due to the time required to

construct new capacity, the earliest retirement date for the steam station is January

2017.

The total installed capacity at the Spring Garden site is 153.1 MW.

3.1.2 Seawell Generating Station

The Seawell generating station is located near the Grantley Adams International

Airport, approximately 12km south east of Bridgetown. The station has one 13MW

gas turbine unit (GT03) installed in 1996 and three gas turbines (GT04 – GT06) with


a nominal capacity of 20MW each, added to the system in 1999, 2001 and 2002

respectively. This site is currently fully developed.

The retirement dates assumed for these units are the end of 2021, 2024, 2026 and

2027 respectively. Units GT03, GT04 and GT06 have been refueled to burn diesel

instead of Jet A1. Seawell is an unmanned station that is monitored and controlled

remotely via a fiber optic link from the Central Control Room at Spring Garden where

the units are dispatched as required. Also located on this site is an 11/24kV

substation, which is monitored and controlled via the SCADA Control Room, located

at Garrison Hill.

The total installed capacity at the Seawell site is 73.0MW.

3.1.3 Garrison Hill Generating Station

The Garrison Hill site is of historic and architectural significance. Furthermore, due to

the limited space available and other constraining factors relating to the adjacent

properties, no future development of this site is considered within this study.

The gas turbine unit, GT02, located at the Garrison Hill generating station was

installed in 1990 and operates on diesel fuel. It is assumed that unit GT02 will

continue to provide capacity until it is retired at the end of 2016.

The installed capacity of this unit is 13.0MW.

3.1.4 Cost and Performance Parameters

Table 20 presents a summary of the latest cost and performance parameters

adopted for this study. Further information is included in the following sub-sections.


Table 20: Cost & Performance Parameters for Existing Plant

3.1.4.1 Retirement Dates

In this study, the retirement dates that will be used are based on the expected

lifetime of the units (Table 20). No life extension measures will be considered or

proposed as part of this study.

3.1.4.2 Heat Rates

Periodically, BL&P conducts heat rate tests on its units. The heat rates shown in

Table 20 are based on the heat rate tests that were conducted in 2009. The gross

heat rate relates to the heat rate at gross capacity of the plant using the lower

S1 S2 D10 D11 D12 D13 D14 D15

Installed Capacity (MW) 20.0 20.0 12.5 12.5 12.5 12.5 29.7 29.7

Retirement Date 01/01/17 01/01/17 01/01/19 01/01/19 01/01/19 01/01/19 01/01/36 01/01/36

Fuel Type HFO HFO HFO HFO HFO HFO HFO HFO

Gross Heat Rate (Btu/kWh)12,325 12,325 8,063 8,063 8,063 8,063 7,456 7,456

Average Annual Maintenance

(Days) 74 74 35 35 35 35 41 41

FoR (%) 5.7 5.7 6.1 6.1 6.1 6.1 2.0 2.0

Annual Availability (%) 74.0 74.0 84.3 84.3 84.3 84.3 86.8 86.8

Auxilary Power Consumption

(%) 6.9 6.9 4.1 4.1 4.1 4.1 3.8 3.8

Fixed O&M (Bds$/ kW/ month)19.21 19.21 13.89 13.89 13.89 13.89 9.24 9.24

Variable O&M

Bds$/ MWh 18.13 18.13 33.65 33.65 33.65 33.65 10.38 10.38

CG01 CG02 GT02 GT03 GT04 GT05 GT06

Installed Capacity (MW) 1.5 2.2 13.0 13.0 20.0 20.0 20.0

Retirement Date 01/01/19 01/01/36 01/01/17 01/01/22 01/01/25 01/01/27 01/01/28

Fuel Type Diesel Diesel Diesel Av-Jet Diesel

Gross Heat Rate (Btu/kWh) 13,276 13,276 11,134 11,134 11,134


(Days) 56 51 67 39 27 27 27

FoR (%) 12.4 5.0 17.5 2.6 4.3 4.3 4.3

Annual Availability (%) 72.3 81.0 64.1 86.7 88.3 88.3 88.3


(%) 1.0 0.8 1.0 1.0 1.0

Fixed O&M (Bds$/ kW/ month)4.74 3.43 0.89 0.89 0.89

Variable O&M

Bds$/ MWh 52.09 34.86 104.65 104.65 104.65

Low Speed Diesels

Cogen Gas Turbines

Steam


heating value (LHV) of fuel. While Table 20 shows the heat rate at full load and

minimum load, the actual heat rate curves were used in the model.

3.1.4.3 Annual Maintenance Rate

Annual maintenance rate is the number of hours the unit is unavailable for planned

or corrective maintenance divided by the total number of hours in the year.

Information in respect of the annual maintenance rate for the existing units was

reviewed and average values over the 5-year period (2007 – 2011) determined

based on the units’ historical data.

3.1.4.4 Forced Outage Rate

Forced outage rate is the number of hours the unit is unavailable due to emergency

outages divided by the total number of hours the unit is available. Information in

respect of the forced outage rate for the existing units was reviewed and average

values over the 5-year period (2007 – 2011) determined based on the units’

historical data.

3.1.4.5 Auxiliary Power Consumption

The auxiliary power consumption is the amount of energy used within the plant

during the production of electricity. Information in respect of the auxiliary power

consumption for the existing units was reviewed and average values over the 5-year

period (2007 – 2011) determined based on the units’ historical data.

3.1.4.6 Fixed Operating and Maintenance Cost

Information in respect of the fixed operating and maintenance cost was reviewed

and average values over a 3-year period determined based on the units’ historical

data.


3.1.4.7 Variable Operating and Maintenance Cost

Information in respect of the variable operating and maintenance cost was reviewed

and average values over a 3-year period determined based on the units’ historical

data.

3.1.4.8 Nat Gas Conversion of D14/D15

When natural gas becomes available, units D14 and D15 can be converted to dual

fuel operation meaning that 92% of the units’ energy would be produced from natural

gas while the remaining 8% of the units’ energy would be produced from the pilot oil

(HFO) when the units are generating at full load. Should the gas supply be

interrupted the engines can continue operation on HFO.

For scenarios where natural gas is available, D14 and D15 are assumed to be

converted to dual fuel operation in 2017. Based on the information available, the

conversion of each unit is assumed to take three months at a cost of BDS $12.5

million per unit. The cost and performance characteristics of these units, following

the conversion, are assumed to be the same as those prior to the conversion as

outlined in Table 20.

3.2 Candidate Plant

The generating technologies considered as future generating options in this study

have been categorized into conventional fossil fuel technologies and renewable

technologies.

3.2.1 General Requirements

For the 2012 Integrated Resource Plan, only commercially and technically proven

generating technologies were considered.


Commercially and technically proven technologies are those that have been

designed, constructed and operated on a commercial scale (not a pilot plant or

research facility) for at least three years in a reliable manner.

3.2.2 Conventional Candidate Plant

The choice of future supply options presented in this report is primarily based on

technologies applicable to the available fuel. Candidate plant comprises low speed

diesel units (LSD), medium speed diesel units (MSD), combined cycle plant (CCGT)

and open cycle gas turbine units (OCGT). These technologies will be modeled as

single and dual fired units.

Capital cost estimates are based upon data obtained by BL&P during an industry

scan with manufacturers10and financial lending agencies11conducted between July

and September 2012. In addition, data from The Institution of Diesel and Gas

Turbine Engineers (which collects operational and performance data on diesel and

gas turbine units around the world), the Lazard's Levelized Cost of Energy Analysis-

June 2011 report and information from BL&P’s consultant who conducted the

previous Generation Expansion Study in 2010 was considered. Performance

parameters were obtained from manufacturers during the industry scan and from

operational reports for similar plants operating in various locations around the world.

Historical data on BL&P’s plant operation has been considered when estimating cost

and performance parameters for candidate plant. Performance parameters have all

been adjusted from ISO conditions to take account of ambient conditions in

Barbados.

10

Discussions held with Man B&W, Wartsilla, BWSC, Doosan Engineering, Hyundai Heavy Industries 11

European Investment Bank, Inter-American Developmental Bank, International Financial Corporation


3.2.2.1 Low Speed Diesel Units

Low speed diesel units have been considered as candidate plant in this study. The

inclusion of these units is as a result of, but not limited to, the following reasons:

As a prime mover for electricity generation, two-stroke low speed diesels offer

very high fuel efficiencies in the range of power outputs under consideration

compared with other thermal generating plant.

Their ability to burn cheap low quality fuels while maintaining relatively high

levels of availability and reliability.

BL&P’s familiarity with two-stroke low speed diesel technology.

Compared with other reciprocating plant, two-stroke low speed diesel units have

higher installed capital costs per kilowatt, but lower operating costs per unit of

energy generated. In island utility environments, where land area for the

development of power plants is limited, these units offer a high ratio of installed

power per unit of land, but their construction times can be up to twice as long as

medium speed diesel units.

Modern low speed diesel units have thermal efficiencies in the range of 46% to 50%.

The efficiencies of these units are relatively constant across their output range and

they are not subject to significant de-rating as a result of the ambient conditions in

which they operate.

Dual fuel operation means that 92% of the unit's energy will be generated from

burning natural gas with the remaining 8% of the unit's energy being produced from

the pilot oil (HFO or diesel oil) at full load. Should the gas supply be interrupted, the

engine can continue its operation on HFO.

Based upon the selected planning criteria, the sizes of low speed diesel plant

considered are 17 MW, 30 MW and 38 MW.


The low speed diesel units being considered incorporate a waste heat recovery

boiler and a turbine representing approximately 1MW of the overall plant capacity.

The cost and performance assumptions of these units have been determined with

this consideration.

The cost assumptions adopted for the low speed diesel units in the liquid case

assume that the units are designed to allow for conversion to dual-fueled operation

with minimum time and effort in the future.

Cost and performance parameters adopted for candidate plant for the liquid fuel

case are set out in Table 21 whilst the corresponding values for the dual-fueled

scenario are given in Table 22. These tables are shown at the end of this Section.

3.2.2.2 Medium Speed Diesel Units

HFO-fired as well as dual-fueled medium speed diesel units were considered as

candidate plant for the IRP study. Depending on the capacity required, multiple unit

configurations may be required due to the fact that these units are presently limited

to a maximum size of less than 20 MW. This would, therefore, require BL&P to

allocate a larger area of land per unit of capacity for medium speed units than for low

speed diesel units.

Medium speed diesel units are not as efficient as equivalent low speed diesel units

so the associated fuel costs with this type of unit are higher. Operating and

maintenance costs are also higher for medium speed units owing to their multiple

cylinder configurations and their associated maintenance schedule.

For the medium speed diesel units, dual fuel operation means that 99% of the unit's

energy will be generated from burning natural gas with the remaining 1% of the unit's

energy being produced from the pilot oil (HFO) at full load.


Should the gas supply be interrupted, the engine can continue its operation on HFO.

We have included HFO-fired units for the liquid fuel scenario and the dual-fueled

units for the natural gas scenario. The cost assumptions adopted for the medium

speed diesel units in the liquid case assume that the units are designed to allow for

conversion to dual-fueled operation with minimum time and effort in the future.

Cost and performance parameters adopted for candidate plant for the liquid fuel

case are set out in Table 21 while the corresponding values for the dual-fueled

scenario are given in Table 22. These tables are shown at the end of this Section.

3.2.2.3 Open Cycle Gas Turbines

Open cycle gas turbines (OCGT) plant falls into two categories: industrial units and

aero-derivative units. The gas turbines currently operated by BL&P are classed as

industrial units. These units are of a proven design with open cycle efficiencies

between 29%and 34%. The capacity range available for this type of generation plant

is appropriate for the unit sizes to be considered for this IRP study.

Industrial OCGTs are of a robust design with high availability and low specific

maintenance costs. BL&P is already familiar with this technology and the majority of

maintenance can be done on the island with the appropriate maintenance tools.

Exceptions to this are highly specialized maintenance functions, such as refurbishing

blades.

Aero-derivative gas turbine units, as the name suggests, are land-based adaptations

of the units used in aircraft jet propulsion. These units require a smaller area for

installation (smaller footprint) and offer marginally higher open cycle efficiencies and

faster start times than industrial units. Typical efficiencies for aero-derivative units, in

the range under consideration, are between 38%and 42%.


While aero-derivative gas turbine units offer advantages over the industrial units,

their overall lifecycle costs are higher due to their specialized maintenance

requirements. The typical maintenance pattern would require a spare gas generator

section, which would be installed when the main unit is undergoing repairs. This

calls for a leasing or unit exchange agreement with the vendor which, in itself, is not

a complicated arrangement but would leave BL&P exposed to higher maintenance

costs during overhauls.

For the purpose of this IRP study, we have selected 20 MW, 30 MW and 40 MW

industrial gas turbines as candidate plant.

Cost and performance parameters adopted for liquid-fired candidate gas turbines

are set out in Table 21, while the corresponding values for dual-fueled units are

given in Table 22. These tables are shown at the end of this Section.

3.2.2.4 Combined Cycle Gas Turbines

Combined cycle gas turbines (CCGTs) have specific capital costs that are

approximately 30% higher than OCGTs. They also have a much higher lifecycle

operating and maintenance costs. These higher costs are offset by the significantly

higher unit efficiencies, which are in excess of 48%.

Compared to a simple open cycle gas turbine, CCGT plant is more complex to

operate because of the presence of the additional steam cycle. CCGT units also

require large quantities of treated water for use in its boiler.

For the purpose of this generation planning study, we have selected the nominal

sizes of 30 MW and 40 MW combined cycle generating units as candidate plant.

Recognizing the relatively small unit sizes, all units are assumed to be single shaft

units in a 1+1 configuration.


Cost and performance parameters adopted for liquid and gas fired candidate

combined cycle gas turbines are set out in Table 21and Table 22 respectively.

Table 21: Financial & Performance Data for Liquid Fuel Candidate Plant

Table 22: Financial &Performance Data for Natural Gas Candidate Plant

Medium

Speed Diesel

LSD17 LSD30 LSD38 MSD17 GT20 GT30 GT40 CCGT30 CCGT40

Installed Capacity (MW) 18.5 31.7 38.5 17.1 21.0 31.0 39.8 30.2 42.1

Lifetime (yrs) 30 30 30 25 25 25 25 25 25

Max No. of units built in

planning horizon20 20 20 20 20 20 20 20 20

Max No. of units built per year 3 3 3 3 3 3 3 3 3

Earliest Build Date 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017

Fuel Type HFO HFO HFO HFO Diesel Diesel Diesel Diesel Diesel

Gross Heat Rate (Btu/kWh) 7,358 7,355 7,318 7,779 10,383 9,427 9,720 7,200 6,941


(Days)37 37 37 44 15 15 17 20 20

FoR (%) 3.0 3.0 3.0 4.0 4.5 4.5 4.5 5.0 5.0

Annual Availability (%) 86.9 86.9 86.9 83.9 91.4 91.4 90.8 89.5 89.5


(%)4.7 4.7 4.7 4.0 0.3 0.7 1.0 2.3 2.3

Overnight Cap.Cost 2012

($/kW)2,853 2,853 2,955 2,344 2,261 1,829 1,786 3,698 3,114

Fixed O&M (Bds$/ kW/ month) 9.58 9.17 8.75 13.75 2.17 2.17 2.17 9.17 8.75

Variable O&M

Bds$/ MWh12.00 12.00 11.00 18.00 80.00 80.00 80.00 10.00 10.00

10% variation was assumed for high and low case sensitivities on the capital, fixed and variable O & M costs

Low Speed Diesel OC Gas Turbines CC Gas Turbines

Medium

Speed

Diesel

NG-LSD17 NG-LSD30 NG-LSD38 NG-MSD17 NG-GT20 NG-GT30 NG-GT40 NG-CCGT30 NG-CCGT40

Installed Capacity (MW) 17.6 31.7 38.5 17.1 21.0 32.0 41.0 30.3 43.5

Lifetime (yrs) 30 30 30 25 25 25 25 25 25

Max No. of units built in

planning horizon20 20 20 20 20 20 20 20 20

Max No. of units built per

year3 3 3 3 3 3 3 3 3

Earliest Build Date 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017 1/1/2017

Fuel Type92% NG

8% HFO

92% NG

8% HFO

92% NG

8% HFO

99% NG

1% HFONG NG NG NG NG

Gross Heat Rate (Btu/kWh) 7,358 7,355 7,318 7,659 10,353 9,392 9,575 7,162 6,923


(Days)37 37 37 44 15 15 17 20 20

FoR (%) 6.0 6.0 6.0 5.0 4.5 4.5 4.5 5.0 5.0

Annual Availability (%) 83.9 83.9 83.9 82.9 91.4 91.4 90.8 89.5 89.5


(%)6.0 6.0 6.0 5.0 1.0 1.0 1.0 2.5 2.5

Overnight Cap.Cost 2012

($/kW)3,261 3,261 3,363 2,649 2,269 1,786 1,742 3,129 2,555

Fixed O&M (Bds$/ kW/

month)9.58 9.17 8.75 13.75 0.92 0.92 0.92 9.17 8.75

Variable O&M

Bds$/ MWh12.00 12.00 11.00 18.00 80.00 80.00 80.00 10.00 10.00

10% variation was assumed for high and low case sensitivities on the capital, fixed and variable O & M costs

OC Gas Turbines CC Gas TurbinesLow Speed Diesel


3.2.3 Renewable Energy Technologies

In determining the RE technologies to be included in this IRP study, a review was

conducted of available renewable technologies and their current state of

development. Results of this review are summarized in Table 23. Only utility scale

RE technologies are included as candidate plant in the IRP. The impact of

distributed RE technologies can be accounted for under the low electricity demand

world.

Table 23: Overview of Renewable Technology Characteristics

A brief overview of each of these RE technologies is provided in the following

sections.

3.2.3.1 Solar PV

Solar photovoltaic (PV) panels are used to convert sunlight to electricity directly.

Photovoltaic conversion is the direct conversion of sunlight into electricity with no

intervening heat engine. When light photons of sufficient energy strike a solar cell,

Technology

Carbon

Neutral

State of

Technology

Customer

Located

Central

Station Intermittent Peaking

Load-

Following Base Load

Solar PV Commercial /

Evolving

Solar Thermal Emerging

Biomass Direct * Mature

Wind Mature

Geothermal Mature

MSW-to-Energy Commercial /

Evolving

Landfill Gas-to-Energy Commercial

Biogas Commercial

Tidal Barrage Emerging

Tidal Current R&D

OTEC R&D

Wave R&D

* Provided bio-crops sustainably harvested

Location Dispatch


electrons move within the silicon crystal structure, resulting in a voltage between

electrodes.

Solar photovoltaic panels are solid-state. At present, panels based on crystalline and

polycrystalline silicon solar cells are the most common. Thin-film solar panels,

especially cadmium telluride (CdTe) and copper indium gallium diselenide (CIGS)

based cells, are gaining market share because of their lower costs and increased

efficiencies. For example, the efficiencies of multi-junction cells and concentrating

PV have been reported to be as high as 40% and most panels available in the

market have efficiencies of the order of 15%.

Solar cells are arranged together on a solar module, which is installed on the roofs

of houses or in large ground mounted installations. Solar modules generate Direct

Current (DC) electricity, which needs to be converted into Alternating Current (AC)

before it can be fed into the electricity grid and used in homes and businesses. The

device used to convert DC to AC is called an inverter and thus, the two key

components of PV generation, are the modules and the inverter.

3.2.3.2 Solar Thermal

Concentrating Solar Power (CSP) plants produce electric power by converting the

sun's energy into high-temperature heat using various mirror configurations. The

heat is then channeled through a conventional generator. The plants consist of two

parts - one that collects solar energy and converts it to heat and another that

converts heat energy to electricity.

CSP systems can be sized for village power (10 kilowatts) or grid-connected

applications (up to 100 megawatts). Some systems use thermal storage during

cloudy periods or at night. The amount of power generated by a concentrating solar

power plant depends on the amount of direct sunlight. Like concentrating


photovoltaic concentrators, these technologies use only direct-beam sunlight, rather

than diffuse solar radiation.

CSP technology utilizes three alternative technological approaches: trough systems,

power tower systems and dish/engine systems. For each of these, various design

variations or different configurations exist.

3.2.3.3 Biomass

Biomass is any organic matter that is available on a renewable or recurring basis

and includes forest and mill residues, agricultural crops and wastes, wood and wood

wastes, animal wastes, livestock operation residues, aquatic plants and municipal

and industrial wastes. Biomass can be used in solid form or converted into gaseous

or liquid form before use.

The biomass sector is varied both from a technological and an input fuel

perspective. The technologies range from those that are proven commercially (for

example, solid fuel combustion), through to those that are entering commercial

demonstration and proving commercial reliability (for example, gasification).

To effectively develop productive energy from biomass resources, a number of

considerations need to be addressed such as availability of resources, economics of

collection, storage and transportation and evaluating and delivery of technical,

environmental and publicly acceptable options for conversion into useful electricity

(and heat). The availability of the feedstock in close proximity to the biomass power

project, is a critical factor in the efficient utilization of this resource and will often

dictate the technology and size of the proposed project, in addition to dramatically

impacting on the financial model (for example, quantity of fuel needed, maintenance

cycle, cost of fuel/gate fee).

The main biomass fuels available include:


Energy crops

Crop residues: cane trash

Stemwood: hardwood and softwood tree trunks

Forestry residues: wood chips from branches, tips and poor quality stemwood

Sawmill co-product: wood chip, sawdust and bark

Arboricultural arisings: stemwood, wood chips, branches and foliage

Waste wood: clean and contaminated

Organic waste: paper/card, food/kitchen, garden/plant and textiles wastes

Sewage sludge: from waste water treatment

Animal manures/slurry: from cattle, pigs, sheep and poultry

Landfill gas: captured from biodegradable waste decomposition

First generation bio-fuels: ethanol (from sugar and starch crops), bio-diesel

from oil crops

Algae: oil and biomass from photosynthetic algae (are emerging as a

potential fuel source).

Biomass can be converted into electric power through several methods. The most

common is direct combustion of biomass material, such as agricultural waste or

woody materials. Other options include gasification, pyrolysis, and anaerobic

digestion. Gasification produces a synthesis gas, with usable energy content, by

heating the biomass with less oxygen than needed for complete combustion.

Pyrolysis yields bio-oil by rapidly heating the biomass in the absence of oxygen.

Anaerobic digestion produces a renewable natural gas when organic matter is

decomposed by bacteria in the absence of oxygen.

Different methods work best with different types of biomass. Typically, woody

biomass such as wood chips, pellets, and sawdust are combusted or gasified to

generate electricity. Very wet wastes, like animal and human wastes, are converted

into a medium-energy content gas in an anaerobic digester. In addition, most other


types of biomass can be converted into bio-oil through pyrolysis, which can then be

used in boilers and furnaces.

Compared to many other renewable energy options, biomass has the advantage of

dispatchability, meaning it is controllable and available when needed, similar to fossil

fuel electric generation systems. The disadvantage of biomass for electricity

generation however, is that the fuel needs to be procured, delivered, and stored.

Also, biomass combustion produces emissions, which must be carefully monitored

and controlled to comply with regulations.

The efficiency of a direct combustion or biomass gasification system is influenced by

a number of factors, including biomass moisture content, combustion air distribution

and amounts (excess air), operating temperature and pressure and flue gas

(exhaust) temperature.

The biomass application being investigated for Barbados is a fixed-bed direct

combustion system with cane bagasse and Leucaena (referred to locally as “river

tamarind”) as the fuel sources.

3.2.3.4 Anaerobic Digestion / Biogas

Anaerobic Digestion (AD) is a process whereby bacteria break down organic

feedstocks in the absence of oxygen to produce a gas that is rich in methane. The

resulting biogas can be used in direct combustion to generate heat and/or power, or

be further refined to produce bio-methane for vehicle fuel or injection into the gas

grid network. The by-product is an organic digestate that has potential to be returned

to the land as soil improver.

The technological developments in AD are not so much associated with the

generation equipment, but more with the Digester technology and the clean-up of

the resultant gases before combustion. Electricity generation from biomass is often


achieved using gas engine generators, which are largely based upon established

diesel technology. Only relatively minor adjustments are necessary for the different

fuel types. Leading gas engine suppliers offer an energy conversion efficiency of up

to 42% and no significant efficiency increases are expected in the future.

3.2.3.5 Landfill Gas-to-Energy

Landfill gas is generated through the degradation of municipal solid waste (MSW) by

microorganisms. The quality of the gas is highly dependent on the composition of

the waste, presence of oxygen, temperature, physical geometry and time elapsed

since waste disposal. In anaerobic conditions, as is typical of landfills, methane and

CO2 are produced in equal amounts. Methane (CH4) is the important component of

landfill gas as it has a calorific value of 33.95 MJ/Nm3 which gives rise to energy

generation benefits. The amount of methane that is produced varies significantly

based on the composition of the waste. Most of the methane produced in MSW

landfills is derived from food waste, composite paper and corrugated cardboard. The

rate of landfill gas production varies with the age of the landfill.

Landfill gas is gathered from landfills through extraction wells placed, depending on

the size of the landfill. Landfill gas must be treated to remove impurities, condensate,

and particulates. The treatment system depends on the end use. Minimal treatment

is needed for the direct use of gas in boiler, furnaces, or kilns. Using the gas in

electricity generation typically requires more in-depth treatment. If the landfill gas

extraction rate is large enough, a gas turbine or internal combustion engine could be

used to produce electricity to sell commercially or use on site.

3.2.3.6 Wind Energy

Wind power is the conversion of wind energy into a useful form of energy, such as

using wind turbines to make electrical power, windmills for mechanical power, wind

pumps for water pumping or drainage, or sails to propel ships. A wind farm consists


of several individual wind turbines which are connected to the electric power

transmission network.

On-shore wind is a mature renewable technology, which appears to have converged

on a horizontal axis (generally three-blade) machine. The basic equipment varies

little between sites and scales, with steel tubular towers being the predominant

support for wind turbine generators (WTG) above 1 MW.

Offshore-wind is at an early stage of deployment, with only a decade since the first

commercial installation in Denmark. Offshore wind farms can harness more frequent

and powerful winds than are available to land-based installations and have less

visual impact on the landscape, but construction costs are considerably higher and

they must be installed in relatively shallow water.

3.2.3.7 Waste-to-Energy (WtE)

Waste-to-Energy (WtE) technologies range from the mature application of direct

incineration to emerging technologies which process the waste to another form for

combustion to avoid direct combustion.

The dominant WtE technology is incineration, chiefly because of its relatively low

capital cost and operating risks. Some separation or pre-processing of the waste

may be required for the various processes. The main incineration technologies

utilized worldwide are moving grate, fluidized bed and rotary kiln combustion

chambers. Exhaust gas boilers, steam turbines, turbo alternators and flue gas

cleaning systems complete the electricity generation process. These incineration

systems form the majority of the world’s WtE facilities.

Alternative thermal WtE technologies are, at this stage, more expensive and carry

greater operating risks.


3.2.3.8 Tidal Barrage

Tidal power is a form of hydropower derived from tidal flows and currents. Tidal

power may be tapped by two main means.

Tidal barrage technologies: these employ potential energy by entrainment of tidal

floods to capture water for the movement of low-head turbines.

Tidal stream technologies: these employ kinetic energy by harnessing currents to

move turbines in a manner similar to wind turbines.

Tidal barrage technology is one of the most mature technologies available for

harnessing tidal energy. It is best suited for regions where the local geography

results in a large tidal range in a suitable channel.

The development of tidal barrage systems has been hampered by the large

infrastructural cost of such projects, their long construction times as well as

opposition to their environmental impacts.

Tidal stream technology is immature, with most prototypes having been deployed

only within the last ten (10) years but is being facilitated by the increasing availability

of test berths and hubs.

3.2.3.9 Ocean Thermal Energy Conversion (OTEC)

OTEC uses the temperature difference between cooler deep and warmer shallow, or

surface ocean waters, to run a heat engine and produce useful work, usually in the

form of electricity. However, if the temperature differential is small, this impacts the

economic feasibility of ocean thermal energy for electricity generation. OTEC plants

pipes in hot and cold seawater and run them through heat exchangers and water

condensers, in the process spinning turbines that generate electricity. It can only be

done efficiently where the thermal gradient within the upper 1,000 meters of the

ocean is more than 20° Celsius.


The most commonly used heat cycle for OTEC is the Rankine cycle using a low-

pressure turbine. Systems may be either closed-cycle or open-cycle. Closed-cycle

engines use working fluids that are typically thought of as refrigerants such as

ammonia or R-134a. Open-cycle engines use vapour from the seawater itself as the

working fluid.

OTEC can also supply quantities of cold water as a by-product. This can be used for

air conditioning and refrigeration and the fertile deep ocean water can feed biological

technologies. Another by-product is fresh water, distilled from the sea.

Demonstration plants were first constructed in the 1880s and continue to be built,

but no large-scale commercial plants are in operation.

3.2.3.10 Wave Energy

Wave power is distinct from the diurnal flux of tidal power and the steady gyre of

ocean currents. Wave-power generation is not currently a widely employed

commercial technology, although there have been attempts to use it since at least

1890.

Wave power devices are generally categorized by the method used to capture the

energy of the waves, by location and by the power take-off system. Method types

are point absorber or buoy; surfacing following or attenuator, oriented parallel to the

direction of wave propagation; terminator, oriented perpendicular to the direction of

wave propagation; oscillating water column and overtopping. Locations are

shoreline, near shore and offshore. Types of power take-off include hydraulic ram,

elastomeric hose pump, pump-to-shore, hydroelectric turbine, air turbine and linear

electrical generator. Some of these designs incorporate parabolic reflectors as a

means of increasing the wave energy at the point of capture. These capture systems

use the rise and fall motion of waves to capture energy. Once the wave energy is


captured at a wave source, power must be carried to the point of use or to a

connection to the electrical grid by transmission power cables.

3.2.3.11 Energy Storage Options

There are three battery storage options available for consideration: Flow Battery

(Vanadium-Mixed Acid), Lead Acid and Sodium Sulfur (NaS). Other forms of energy

storage, like compressed air and hydro pumped storage, are not considered in this

evaluation due to geographical limitations on the island. The three batteries have

significantly different capital and operating costs but provide the same level of

generation. All batteries have an efficiency of 70%. The estimates presented here

are representative in nature. Concept design and quotes from vendors would be

required to get accurate cost estimates.

Table 24 provides a comparison of cost and technical characteristics for these three

battery options to provide firm capacity for wind energy in the IRP model (BEW

Engineering, 2012).

Flow Battery Lead Acid Sodium Sulfur

Capital Cost ($/kW) 700 600 200

Energy Rate ($/kWh) 150 250 570

O&M ($/yr) 6,400 32,000 32,000

Mean Time to Repair 2 N/A N/A

Life (years) 20 20 20

Efficiency (%) 70 70 70

Table 24: Cost & Technical Characteristics of Battery Storage Options (Source: BEW Engineering, 2012)

In evaluating the option of coupling storage with wind or solar technologies, the

approach taken was to first evaluate a storage option coupled with the most


economical intermittent RE option, i.e. wind energy. The cost of storage required to

provide firm capacity with wind generation is less than that associated with

equivalent solar capacity. This is because solar energy is only available for half of

the day and therefore has a lower capacity factor. The “wind with storage” option

was found to be uneconomic and therefore the “solar with storage” option was not

considered.

Table 25 shows the amount of battery storage needed to support 10%, 20% and

30% firm capacity for a 1MW wind turbine, based on wind speed characteristics at

the proposed Lamberts wind farm site. For a 100 kW battery, there are about four (4)

days of low wind that require 7.64 MWh of battery energy. The battery cost varies

from $1.21 million to $4.35 million, depending on the battery type. For a 300 kW

battery, the number of days increases to seven (7) and the capital costs increase

about five to six times the 100 kW battery. The 100kW (10%) flow battery storage

option was modeled in the IRP.

Size

(KW)

Energy

(MWh)

Flow Lead Acid Sodium Sulfur

100 7.64 $1.21 million $1.9 million $4.35 million



Table 25: Battery Cost Estimates (Source: BEW Engineering, 2012)

3.2.3.12 Geothermal

Geothermal power is generated by using steam or a hydrocarbon vapour to turn a

turbine generator set to produce electricity. There are currently three main types of

geothermal power plants:


Dry steam plants using steam from underground wells to rotate a turbine, which

activates a generator to produce electricity. Dry steam power plants systems

were the first type of geothermal power generation plants built.

Flash steam plants using hot-water resources, which are ‘flashed’ by reducing

the pressure, to produce steam (normally in the 15% - 20% dryness range).

Some plants use double and triple flash to improve the efficiency. The steam is

then used to power a generator and any leftover water and condensed steam is

returned to the reservoir.

Binary Cycle or Organic Rankine Cycle (ORC) plants using the heat from

lower temperature reservoirs to boil a working fluid, which is then vaporized in a

heat exchanger and used to power a generator. Usually, a wet or dry cooling

tower is used to condense the vapour after it leaves the turbine, to maximize the

temperature and pressure drop between the incoming and outgoing vapour and

thus increase the efficiency of the operation. The hot water, which never comes

into direct contact with the working fluid, is then injected back into the ground to

be reheated.

Geothermal energy is not available in Barbados. The potential for geothermal

development does, however, exist in neighboring islands, which could present an

opportunity for energy import by subsea cables in the future.

3.2.3.13 Subsea DC Cables

Subsea High Voltage Direct Current (HVDC) cables, when installed, form the

backbone of an electric power system. They combine high reliability with a long

useful life. The core component is the power converter, which serves as the

interface to the AC transmission system. The conversion from AC to DC and vice

versa, is done by controllable electronic switches in a three-phase bridge

configuration. Two advantages HVDC has over AC transmission are there is no


technical limit to the length of a HVDC cable connection (the upper limit on AC

submarine transmission is around 110km) and there is no requirement that the

linked systems run in synchronism.

The four closest islands to Barbados for which submarine electrical cable

interconnections might be considered are St. Lucia, St. Vincent, Grenada and

Trinidad & Tobago (T&T). The first three predominantly use diesel for electricity

generation, but the potential for geothermal electricity production exists. No

geothermal feasibility studies have been to date done in any of these three islands,

so the true potential remains uncertain. An electrical connection to T&T would

provide potential access to relatively low cost natural gas fired generation. The

distance between T&T and Barbados is well over the upper limit for viable AC

submarine transmission and therefore HVDC would be required. The water depth

between the two islands exceeds6000 feet in areas which exceed current record set

by the SAPEI in the Mediterranean Sea at depths of up to 1,600 metres.

In 2010, the World Bank commissioned a study on ‘Caribbean Regional Electricity

Generation, Interconnection and Fuels Supply Strategy’ conducted by Nexant, which

screened energy interconnection options between islands in the Caribbean.

Potential submarine cable interconnections were evaluated for several Caribbean

islands. However, for Barbados, the report focused primarily on the potential for a

natural gas pipeline link between T&T and Barbados and did not consider any

submarine cable links in any detail.

3.2.4 RE Technology Assumptions

In the IRP study, only commercially and technically proven RE generating

technologies were considered. Commercially and technically proven technologies

are defined as those that have been designed, constructed and operated on a

commercial scale (not a pilot plant or research facility) for at least three years in a

reliable manner.


The RE technologies that were considered in the current study are listed in Table 26.

The technologies that will not be considered in the current study are identified in

Table 27. These technologies will continue to be monitored and will be included in

future studies when technically and commercially proven.

Technology Scale

Capacity of each

installation (MW) Notes

Solar PV Utility 1

Distributed <0.15 This will be considered as part of the DSM initiatives.

Wind Utility 1

Distributed <0.15 This will be considered as part of the DSM initiatives.

Biomass Utility 25

Anaerobic Digestion Utility 1.25

Waste-to-Energy Utility 13.5

Landfill Gas-to-Energy Utility 2

Wind With Storage Utility 1

Wind with 10% storage from flow batteries. 10% of capacity treated as firm.

Table 26: Summary of RE Technologies Included In Study


Technology Firm cap

State of Technology

Indigenous Resource Notes

OTEC Yes R&D Yes No commercial applications. High Risk.

Subsea DC cable from neighboring islands Yes

Commercial/ Evolving No

Water depths between Barbados and neighboring islands around 6,000 feet. Deepest existing submarine cable (SAPEI) at 5,200 feet and 260 miles.

Off shore wind No Evolving Yes

Water depths beyond 1 mile of Barbados coast exceed limit for commercially available technologies (<100’ depths)

Solar Thermal No Emerging Yes

Wave No R&D Yes

Tidal Barrage No Emerging Yes Future potential low due to small tidal variations.

Tidal Current No R&D Yes Future potential low due to small tidal variations.

Table 27: RE Technologies Excluded From IRP Study

An industry scan12 was conducted to determine the cost and performance

parameters for the RE technologies modeled in the IRP. Information on the sources

utilized can be found in Appendix H. Cost estimates from technology providers were

also used in determining some of the assumptions.

The RE assumptions used in the current IRP study are summarized in

Table 28.

12

Discussions held with Uriel Renewables, Barbados Cane Industry Corporation, European Investment Bank,

Inter-American Developmental Bank, International Financial Corporation


Table 28: RE Technology Assumptions

ANAEROBIC

DIGESTIONBIOMASS

IMPORTED

BIOMASS

LANDFILL

GASSOLAR

WASTE

TO

ENERGY

WINDWIND WITH

STORAGE

Capacity per unit

(MW)1.3 25.0 25.0 1.5 1.0 13.5 1.0 1.0

Firm Capacity (MW) 1.3 25.0 25.0 1.5 0.0 13.5 0.0 0.1

Max No. of units built

in planning horizon2 1 1 (Note 1) 1 20 (Note 2) 1 12 (Note 3) 12 (Note 3)

Max No. of units built

per year1 1 1 1 1 1 5 5

Earliest Build Date 1/1/2016 1/1/2018 1/1/2020 1/1/2016 1/1/2016 1/1/2018 1/1/2016 1/1/2016

Configuration Digester

Steam

Turbine,

Biomass

boiler

Steam

Turbine,

Biomass

boiler

Reciprocati

ng Engine

Ground

Mounted

Boiler &

Turbine

Lifetime (yrs) 20 30 30 20 20 30 20 20

Output

22.1 MW-

7months/yr;

18.5 MW-

3 months/yr

Modeled

using solar

profile

Modeled

using wind

profile

Modeled

using wind

profile

Capacity Factor 75.0 90.0 90.0 85.0 85.0 32.0 32.0

Fuel

Farm, Food,

Brewery

Waste

Bagasse/

BiomassBiomass Landfill Gas

Landfill

Material

Heat Rate (Btu/kWh) 10,250 13500 13500 10,060

Forced Outage Rate

(%)8.0 3.0 3.0 8.0 6.0 3.0 3.0

Average Annual

Maintenance (Days)14 28 28 14 1 30 4 4

Auxiliary Power

Consumption (%)11.6 11.6 4.0 7.0 1.9 1.9

Overnight Capital

Cost ($/kW)

11,000 -

19,000

7,000 -

10,000

7,000 -

10,000

4,500 -

7,500

3,000 -

6,000

18,000 -

25,000

4,500 -

7,500

8,518 -

11,518

Fixed O & M Cost

($/kW/yr)300 - 1,500 200 - 300 200 - 300 400 - 1,200

50.00 -

80.00

700 -

1,40060 - 150 125 - 215

Variable O & M

($/MWh)15

12.00 -

18.0012.00 - 18.00

15.00 -

20.00

Note 1 - An additional imported biomass plant is available for selection from 1/1/2025 in the LF + Ref + NGr scenario in the high demand world.

Note 2 - 50 solar units are available for selection in the LF + Ref + NGr scenario in the high demand world.Note 3 - Wind and Wind with storage units available for selection as follows: 2 units - 1/1/2016; 5 units -1/1/2018; 12

units - 1/1/2020.


3.2.5 Environmental Criteria

Several of the technologies used to generate electricity result in CO2 being

produced. From an environmental perspective it is useful to determine the amount of

CO2 produced by each expansion scenario. The volume of CO2 produced from each

of the generating technologies considered in this study were derived using the

carbon coefficients from the U.S. Environmental Protection Agency (2004) along

with the average heat rate values for existing and candidate technologies.

Different technologies have different land area requirements. For this reason it is

useful to report the land requirements for different expansion scenarios. Industry

publications along with BL&P’s own experience were used in arriving at the land

requirement areas for the different technologies. Some of these assumptions were

also determined based on information supplied by stakeholders during the

stakeholder consultations. The land requirements for existing units, along with that

for previously contemplated projects, were also considered. Publications used

included CEC (2005); correspondence from suppliers of medium and low speed

diesel units and solar generators and feasibility reports prepared for BL&P.

According to PAHO (2013), Barbados is ranked as the 15thwater scarce country in

the world. As a result it is prudent to determine the amount of water required for

each expansion scenario. Water consumption for the technologies included in the

study was determined using industry performance reports along with BL&P’s

operating experience. Publications referenced included NREL (2011), Mielkeet. al

(2010) and CEC (2005).

The assumptions for CO2, land usage and water usage used in the study are shown

in Table 29.


Technology

CO2 Coefficient (kg CO2/MWh)

Land Usage acres/MW

Water Usage (gal/MWh)

Existing Generation

Steam – HFO 1048.0 N/A 73

Low Speed Diesel – HFO 630.4 N/A 10

Gas Turbine 881.3 N/A 1

Candidate Conventional

Low Speed Diesel – HFO 734.4 0.06 10

Low Speed Diesel - Natural Gas 551.8 0.06 10

Medium Speed Diesel – HFO 514.1 0.08 10

Medium Speed Diesel - Natural Gas 371.4 0.08 10

Gas Turbine – Diesel 575.2 0.03 1

Gas Turbine - Natural Gas 376.7 0.03 1

Combined Cycle Gas Turbine - Diesel 591.0 0.05 30

Combined Cycle Gas Turbine - Natural Gas 387.3 0.05 30

Candidate Renewables

Biomass N/A 0.06 553

Solar N/A 5.5 2

Wind N/A 30 0

Anaerobic Digestion N/A 3.75 235

Waste to Energy N/A 12 553

Landfill Gas N/A 3.75 350

Table 29: Environmental Impact Assumptions

3.3 Levelized Costs

The Levelized Cost of Energy (LCOE) is a methodology used to compare the life-

cycle cost of producing a unit of electricity from various technologies. It is defined by

the US Energy Information Administration as “the present value of the total cost of


building and operating a generating plant over an assumed financial life and duty

cycle, converted to equal annual payments and expressed in terms of real dollars to

remove the impact of inflation”13. According to the US EIA14, it provides a convenient

summary measure of the overall competitiveness of different generating

technologies. It serves as a useful tool for policy discussions, but evaluates

technologies on a ‘stand-alone’ basis and therefore cannot be used as the basis for

determining expansion requirements.

Levelized costs for the various technologies considered in the IRP were calculated

using the Economic and Candidate Plant Assumptions for 2017 as outlined in

Appendix G. The results are presented in Figure 15, with the ranges reflecting the

low and high sensitivity values for capital (including interest during construction),

O&M and fuel costs. The results shown on the chart are expressed in terms of net

generation and bus bar costs.

The specific formulae used in the levelized cost calculations are as follows:

LCOE = I + O&M + F

Where, I = annualized investment cost (BDS$/kWh)

O&M = operation and maintenance cost (BDS$/kWh)

F = fuel cost (BDS$/kWh)

and I = Capital cost x Capital Recovery Factor

Capital Recovery Factor = i(1+i)n

(1+i)n-1

13

http://www.eia.gov/forecasts/aeo/pdf/2016levelized_costs_aeo2011.pdf 14

http://www.eia.gov/forecasts/aeo/electricity_generation.cfm

http://www.eia.gov/forecasts/aeo/pdf/2016levelized_costs_aeo2011.pdf

http://www.eia.gov/forecasts/aeo/electricity_generation.cfm


Figure 15: Levelized Costs Based On Base Assumptions


4 MODELING METHODOLOGY

4.1 Worlds and Scenarios

Specific plans will always be subject to uncertainty and changes in input

assumptions. Prudence therefore dictates that plans be developed and evaluated

across a range of plausible input assumptions and external market conditions. To

assess the inherent risks and uncertainties, a scenario planning approach was used

in the development of the IRP and final recommendation.

The IRP study considered three possible electricity demand growth ‘worlds’ derived

from the econometric model described in Section 2.3. These are:

High Demand (3.0% avg. annual growth)

Base Demand (1.2% avg. annual growth)

Low Demand (-0.4% avg. annual growth)

For each of these demand worlds, five scenarios representing plausible future paths,

relating to fuel types and technologies used, were evaluated, resulting in a total of

fifteen scenario and world combinations. The planning model was then allowed to

select the least-cost mix of resources for each scenario and world combination.

Further uncertainty surrounding input assumptions were addressed, by conducting

sensitivity tests to examine the impacts that changes in capital costs, fuel costs and

discount rates had on the twelve least-cost plans.

As to be expected, the time and effort involved in completing the study is

proportional to the number of scenario and world combinations modeled. Careful

consideration was therefore given to the following factors when selecting the

scenarios and worlds:

Plausibility – How likely is it to occur?

Uniqueness – How different is it from other Worlds and Scenarios?


Stress test – Does it place sufficient stress on the resource selection

process?

Stakeholder interests – Does it capture key stakeholders’ interests?

Regulatory & Policy – Is it consistent with regulatory and policy requirements?

The five scenarios selected for the IRP are defined around the fuel type and

technologies used in the generation of electricity.

Scenario 1 represents a future in which only liquid fuels (i.e. HFO, diesel and Jet

A1) along with renewable energy options described in section 3.2.4 are available for

selection in the expansion plan. This scenario is abbreviated ‘Scenario 1: LF+RE’ in

the IRP.

Scenario 2 builds on the first scenario by introducing the availability of imported

natural gas and consequently the model is permitted to select dual-fuel gas burning

reciprocating engines and simple and combined cycle gas turbines in addition to the

generating options in scenario 1. This scenario is abbreviated ‘Scenario 2:

LF+RE+NG’ in the IRP.

Scenario 3 represents a variation of Scenario 2 in which the model is restricted from

selecting simple and combined cycle gas turbines. This scenario was introduced as

a hedge against the fuel price shocks that would occur in the event that there were

gas supply interruptions, requiring gas turbines to switch from natural gas to diesel.

Diesel prices in the model are projected to be around 75% higher than natural gas

prices. This scenario is abbreviated ‘Scenario 3: LF+RE+NGr’ in the IRP.

Scenario 4 is a variation of Scenario 3, in which the model is forced to achieve 29%

renewable energy generation by 2029, based on the indicative target identified in the

SEFB report. This scenario was introduced because the indicative target was not


being achieved in scenarios 1 to 3. This scenario is abbreviated ‘Scenario 4:

LF+REf+NGr’ in the IRP.

Scenario 5 is a variation of Scenario 1, in which the model is forced to achieve 29%

renewable energy generation by 2029, based on the indicative target identified in the

SEFB report. This scenario was introduced because the indicative target was not

being achieved in scenario 1.This scenario is abbreviated ‘Scenario 5: LF+REf’ in

the IRP.

A summary of the five scenarios and their associated fuels and technologies is

presented in Table 30.

Table 30: Scenario Matrix of Fuels & Technologies

4.2 Sensitivities

Sensitivity studies are usually undertaken to assess the impact of uncertainties that

are inherent within the assumptions employed. Sensitivity tests were conducted as

part of this study.

After determining the optimal plan using the base assumptions for each scenario,

sensitivities were performed on the optimal plans. Sensitivities were conducted in

relation to:

Fuel: Base, High and Low fuel projections as identified in the Fuel

Assumptions in Section 2.4.

Scenario 1:

LF+RE

Scenario 2:

LF+RE+NG

Scenario 3:

LF+RE+NGr

Scenario 4:

LF+REf+NGr 1

Scenario 5:

LF+Ref 1

Liquid Fuel (LF)

Natural Gas (NG) x x

Renewable Energy (RE)

Gas Turbines 2

x x

Notes

1. The model is forced to install 29% RE by 2029 in scenarios 4 & 5.

2. Gas turbines excluded in scenarios 3 & 4 due to high gas interruption cost


Cost: Base, High and Low capital and O&M costs as identified in the

Technology Assumptions in Section 3.2.

Discount Rate: Base, High and Low discount rates as identified in the Economic

Assumptions in Section 2.2.1.

The NPV results for the sensitivities are reported in Section 5.2.

4.3 Software Model

The software package used during the study was the PLEXOS 6.208R08Utility

Planning and Risk Management Software by Energy Exemplar. The Plexos software

is used by utilities, the ISO, consulting firms and regulatory agents for operations,

planning and market and transmission analyses. Plexos is a Mixed Integer

Programming (MIP) energy market simulation and optimization software package,

which is licensed in the United States, Europe, Asia-Pacific, Russia and Africa and

used at over 100 sites.

The software seeks to minimize the net present value of forward-looking costs (i.e.

capital and production costs), subject to fuel mix constraints including renewable

energy targets, reliability and security of supply criteria and normal operating

constraints.

The planning horizon fuel and demand forecasts, typical load duration curve,

existing plant and candidate plant data, reliability criteria as well as other criteria and

constraints are inputted into the model and used in determining the least-cost plan.

Using the Plexos software, a model was built to model BL&Ps current system, along

with assumptions for the candidate plant. Energy Exemplar was contracted to

perform an independent review of the completed model to ensure that it reflected the

assumptions being model. The report of the review is included in Appendix AA.


5 RESULTS

5.1 Expansion Plans

Table 31 shows the net present value results for the fifteen scenarios in the base,

high and low electricity demand ‘worlds.’

Worlds Scenarios Description NPV ($000)

Base

Scenario 1 LQ + RE 4,985,051

Scenario 2 LQ + RE + NG 4,227,676

Scenario 3 LQ + RE + NGr 4,457,170

Scenario 4 LQ + REf + NGr 4,645,222

Scenario 5 LQ + REf 5,035,424

High






Low






Table 31: NPV Results for Worlds and Scenarios


Table 32 summarizes the performance of each scenario’s least-cost expansion plan

in relation to several additional criteria.

Table 32: Characteristics of Least-Cost Plans

5.1.1 Base Demand World

In the base world, the electricity demand is predicted to grow at an average of 1.2%,

per annum, over the planning period.

The liquid +RE scenario requires the installation of 314.2 MW of new capacity over

the planning period according to the build schedule shown in Table 33. Landfill gas,

anaerobic digestion, wind and solar renewable technologies all feature in the optimal

plan, representing 20.0% of energy generated in 2036. The net present value of this

plan is $4.985 billion.

Worlds Scenarios NPV ($000)

C02

(million

MT)

Water

(million

Ga)

Land Use

(acres)

Fuel

Diversity

Foreign

Exchange

($000) Achievability

2017 Gas

Interruption

Cost ($000)

Renew %

in 2029

Renew % in

2036

LQ + RE 4,985,051 18,316 2,512 523 35.94% 4,452,779 High 0 20.8% 20.0%

LQ + RE + NG 4,227,676 13,889 769 70 42.78% 3,916,366 Medium 97,864 0.9% 3.3%

LQ + RE + NGr 4,457,170 15,589 430 31 47.58% 4,074,542 Medium 51,947 1.7% 2.3%

LQ + REf + NGr 4,645,222 13,556 2,480 687 71.11% 4,105,925 Low 39,485 29.0% 29.0%

LQ + REf 5,035,424 17,615 2,958 749 42.78% 4,464,125 Medium 0 29.5% 29.0%

LQ + RE 5,961,262 23,698 2,587 842 31.35% 5,376,707 High 16.6% 15.0%

LQ + RE + NG 4,937,955 16,672 1,819 708 59.37% 4,499,457 Medium 15.8% 14.6%

LQ + RE + NGr 5,185,558 20,461 1,752 993 64.32% 4,687,628 Medium 14.3% 19.8%

LQ + REf + NGr 5,365,404 17,263 3,264 972 71.28% 4,800,408 Low 19.4% 29.0%

LQ + REf 6,095,605 22,109 3,718 952 43.67% 5,452,355 Medium 29.0% 29.0%

LQ + RE 4,112,078 13,711 2,447 344 41.47% 3,616,876 High 27.8% 27.4%

LQ + RE + NG 3,904,750 11,728 289 17 50.83% 3,625,233 Medium 1.3% 2.3%

LQ + RE + NGr 3,942,138 12,009 304 14 50.78% 3,614,724 Medium 1.3% 1.2%

LQ + REf + NGr 4,080,506 10,865 1,817 281 72.94% 3,302,322 Low 29.0% 29.0%

LQ + REf 4,113,915 13,615 2,471 337 43.56% 3,614,519 Medium 29.0% 29.0%

Base

High

Low


Table 33: Build Schedule for Liquid + RE Scenario in Base Demand World

In the Liquid +NatGas+ RE scenario, 284.0 MW of new capacity is required over the

planning period which is made up predominately by open cycle and combined cycle

gas turbines, as shown in Table 34. RE technologies begin to feature in this plan in

2033, with the installation of one 1.5 MW landfill gas unit and one 1.0 MW solar unit.

Additional RE capacity is added in the period 2034 to 2036 with landfill gas, solar,

Capacity Retired Total Capacity Peak Demand Reserve Margin1

LOLP

MW MW Type MW MW % %

2012 239.1 157.4 37.3 0.205

2013 239.1 156.7 37.9 0.205

2014 239.1 157.2 37.4 0.205

2015 239.1 156.9 37.7 0.205

2016 11.5

L/fill Gas – 1 x 1.5 MW

Wind – 2 x 1 MW

Solar - 8 x 1 MW 250.6 158.6 37.2 0.209

2017 53 70.6

LSD30 – 1 x 30 MW

LSD17 – 2 x 17 MW

L/fill Gas – 1 x 1.5 MW 268.2 160.3 48.1 0.017

2018 26

Biomass - 1 x 25 MW

Wind – 1 x 1 MW 294.2 161.1 61.0 0.001

2019 51.5 31.7 LSD17 – 1 x 17 MW 274.4 164.6 49.3 0.022

2020 274.4 167.2 46.9 0.028

2021 1 Wind – 1 x 1 MW 275.4 169.9 44.6 0.052

2022 13 262.4 172.4 36.2 0.223

2023 262.4 174.7 34.4 0.278

2024 262.4 177.0 32.6 0.362

2025 20 32

GT30 – 1 x 30 MW

Wind – 1 x 1 MW 274.4 179.2 37.1 0.230

2026 274.4 181.5 35.4 0.278

2027 20 18.7 LSD17 – 1 x 17 MW 273.1 184.1 32.5 0.323

2028 20 31 GT30 – 1 x 30 MW 284.1 186.7 36.5 0.240

2029 1 Wind – 1 x 1 MW 285.1 189.5 34.4 0.264

2030 285.1 192.1 32.6 0.289

2031 18.7 LSD17 – 1 x 17 MW 303.8 194.7 40.1 0.124

2032 1 Wind – 1 x 1 MW 304.8 197.2 38.3 0.184

2033 304.8 199.8 36.5 0.222

2034 304.8 202.5 34.7 0.246

2035 304.8 205.4 32.8 0.287

2036 73.1 70.95

LSD38 – 1 x 38 MW

LSD17 – 1 x 17 MW

Wind – 7 x 1 MW


Solar - 4 x 1 MW

Ana. Digestion – 1 x 1.25 MW

Retire

Wind – 2 x 1 MW


Solar - 8 x 1 MW 302.65 208.1 32.4 0.402

1 - Reserve Margin based on net capacity and demand.

Capacity AddedYear


anaerobic digestion and wind with storage units being added to the system. By the

end of the planning period, RE technologies account for 7.25 MW. Overall, RE

technologies account for 3.3% of the energy generated in 2036. This scenario, at a

cost of $4.228billion, has the lowest net present value cost of all the base world

scenarios.

Table 34: Build Schedule for Liquid + NatGas + RE Scenario in Base Demand World

Table 35 shows the build schedule for the Liquid + Natural Gas Restricted + RE

scenario, which requires a total of 293.3MW of new capacity over the planning

period, made up predominately of natural gas and HFO burning reciprocating

engines. Landfill gas generating technologies are included in the optimal plan from

2026 and account for 3.0 MW of installed capacity by 2030. The RE technologies in

Capacity Retired Total Capacity Peak Demand Reserve Margin1LOLP


2012 239.1 157.4 37.3 0.205

2013 239.1 156.7 37.9 0.205

2014 239.1 157.2 37.4 0.205

2015 239.1 156.9 37.7 0.205

2016 239.1 158.6 36.2 0.252

2017 53 122.9

NG-CCGT30 – 3 x 30 MW

NG-GT30 – 1 x 30 MW 309 160.3 79.8 0.013

2018 309 161.1 78.9 0.001

2019 51.5 257.5 164.6 48.3 0.132

2020 257.5 167.2 46.0 0.207

2021 257.5 169.9 43.6 0.302

2022 13 244.5 172.4 35.2 0.477

2023 30.3 NG-CCGT30 – 1 x 30 MW 274.8 174.7 50.4 0.104

2024 274.8 177.0 48.4 0.143

2025 20 254.8 179.2 35.5 0.502

2026 254.8 181.5 33.8 0.509

2027 20 31 GT30 – 1 x 30 MW 265.8 184.1 37.8 0.515

2028 20 30.3 NG-GT30 – 1 x 30 MW 276.1 186.7 41.1 0.543

2029 276.1 189.5 39.0 0.543

2030 276.1 192.1 37.2 0.543

2031 276.1 194.7 35.3 0.543

2032 276.1 197.2 33.6 0.543

2033 2.5


Solar - 1 x 1 MW 278.6 199.8 32.6 0.543

2034 2.75


Ana. Digestion - 1 x 1.25 MW 281.35 202.5 32.2 0.543

2035 18.7 LSD17 - 1 x 17 MW 300.05 205.4 39.1 0.530

2036 61.6 45.5

NG-CCGT40 – 1 x 40 MW

Solar – 1 x 1 MW

wind w/storage - 1 x 1 MW 283.95 208.1 32.0 1.910


Capacity AddedYear


this plan account for 2.3% of the energy generated in 2036. The net present value of

this plan is $4.458 billion.

Table 35: Build Schedule for Liquid + NatGas Restricted + RE Scenario in Base Demand World

In the Liquid + Natural Gas Restricted + RE forced scenario, renewable technologies

are selected in order to attain the target of 29% of energy generated by renewables

by 2029. Table 36 shows the build schedule for this plan, which requires a total of

313.6 MW of new capacity. Biomass, landfill gas, wind, anaerobic digestion, wind

coupled with battery storage, waste to energy and imported biomass technologies

feature in this plan which represent 29% of the energy generated in 2029 and 2036.

The net present value of this plan is $4.645 billion.



2012 239.1 157.4 37.3 0.205

2013 239.1 156.7 37.9 0.205

2014 239.1 157.2 37.4 0.205

2015 239.1 156.9 37.7 0.205

2016 239.1 158.6 36.2 0.252

2017 53 136.7

NG-LSD30 – 1 x 30 MW


NG-MSD17 – 3 x 17 MW 322.8 160.3 85.3 0.000

2018 322.8 161.1 84.4 0.000

2019 51.5 271.3 164.6 53.6 0.008

2020 271.3 167.2 51.3 0.011

2021 271.3 169.9 48.9 0.016

2022 13 258.3 172.4 40.4 0.089

2023 258.3 174.7 38.5 0.115

2024 258.3 177.0 36.7 0.154

2025 20 17.6 NG-MSD17 – 1 x 17 MW 255.9 179.2 33.3 0.298

2026 1.5 L/fill Gas – 1 x 1.5 MW 257.4 181.5 32.5 0.307

2027 20 36.3

LSD17 – 1 x 17 MW

NG-MSD17 – 1 x 17 MW 273.7 184.1 38.7 0.059

2028 20 18.7 LSD17 – 1 x 17 MW 272.4 186.7 35.8 0.097

2029 272.4 189.5 33.8 0.127

2030 1.5 L/fill Gas – 1 x 1.5 MW 273.9 192.1 32.8 0.133

2031 17.6 NG-MSD17 – 1 x 17 MW 291.5 194.7 39.6 0.034

2032 291.5 197.2 37.8 0.043

2033 291.5 199.8 36.0 0.064

2034 291.5 202.5 34.2 0.090

2035 291.5 205.4 32.3 0.107

2036 61.6 63.4 NG-LSD30 – 2 x 30 MW 293.3 208.1 33.5 0.141


Capacity AddedYear


Table 36: Build Schedule for Liquid + NatGas Restricted + RE Forced Scenario in Base Demand World

For the Liquid + RE forced scenario, biomass, landfill gas, wind, anaerobic digestion,

wind coupled with battery storage, waste to energy and imported biomass

technologies feature in this plan which represent 29% of the energy generated in

2029 and 2036. The plan requires an addition of 318.2 MW of new capacity as

shown in Table 37. The net present value of this plan is $5.035 billion.


LOLP


2012 239.1 157.4 37.3 0.205

2013 239.1 156.7 37.9 0.205

2014 239.1 157.2 37.4 0.205

2015 239.1 156.9 37.7 0.205

2016 1.5 L/fill Gas – 1 x 1.5 MW 240.6 158.6 37.2 0.209

2017 53 119.3


NG-LSD17 –2 x 17 MW

NG-MSD17 – 3 x 17 MW 306.9 160.3 76.0 0.002

2018 306.9 161.1 75.2 0.000

2019 51.5 255.4 164.6 44.6 0.048

2020 25 Biomass – 1 x 25 MW 280.4 167.2 55.6 0.004

2021 280.4 169.9 53.1 0.007

2022 13 267.4 172.4 44.5 0.034

2023 267.4 174.7 42.6 0.046

2024 1.5 L/fill Gas – 1 x 1.5 MW 268.9 177.0 41.6 0.048

2025 20 19.6

NG-MSD17 – 1 x 17 MW

Wind – 2 x 1 MW 268.5 179.2 38.2 0.095

2026 1 Wind –1 x 1 MW 269.5 181.5 36.4 0.130

2027 20 19.95

LSD17 – 1 x 17 MW

Ana. Digestion – 1 x 1.25 MW 269.45 184.1 34.2 0.164

2028 20 19.95

LSD17 – 1 x 17 MW


2029 21.5

Waste to energy - 1 x 13.5MW

Wind – 8 x 1 MW 290.9 189.5 36.7 0.089

2030 2 Wind –2 x 1 MW 292.9 192.1 34.8 0.106

2031 2 Wind w/ storage –2 x 1 MW 294.9 194.7 33.1 0.147

2032 25 Imp. Biomass – 1 x 25 MW 319.9 197.2 42.7 0.018

2033 319.9 199.8 40.8 0.025

2034 319.9 202.5 38.9 0.034

2035 1 Wind – 1 x 1 MW 320.9 205.4 37.0 0.046

2036 63.1 54.3

NG-MSD17 – 3 x17 MW


Retire

L/fill Gas – 1 x 1.5 MW 312.1 208.1 33.6 0.084


Capacity AddedYear


Table 37: Build Schedule for Liquid + RE Forced Scenario in Base World

Further details of the results of the scenarios in the base demand world are included

in Appendix I.



2012 239.1 157.4 37.3 0.205

2013 239.1 156.7 37.9 0.205

2014 239.1 157.2 37.4 0.205

2015 239.1 156.9 37.7 0.205

2016 4.5


Solar - 1 x 1 MW

Wind – 2 x 1 MW 243.6 158.6 37.2 0.209

2017 53 70.6

LSD30 – 1 x 30 MW

LSD17 – 2 x 17 MW


261.2 160.3 48.1 0.017

2018 28

Biomass - 1 x 25 MW

Wind – 3 x 1 MW 289.2 161.1 61.0 0.001

2019 51.5 31.7 LSD30 – 1x 30 MW 269.4 164.6 49.3 0.022

2020 5 Wind – 5 x 1 MW 274.4 167.2 46.9 0.028

2021 1 Wind – 1 x 1 MW 275.4 169.9 44.6 0.052

2022 13 262.4 172.4 36.2 0.223

2023 262.4 174.7 34.4 0.278

2024 262.4 177.0 32.6 0.362

2025 20 32

GT30 – 1 x 30 MW

Wind – 1 x 1 MW 274.4 179.2 37.1 0.230

2026 1.25 Ana. Digestion - 1 x 1.25MW 275.65 181.5 36.0 0.264

2027 20 18.7 LSD17 – 1 x 17 MW 274.35 184.1 33.1 0.303

2028 20 22.25

GT20 – 1 x 20 MW

Ana. Digestion - 1 x 1.25MW 276.6 186.7 32.4 0.355

2029 13.5 Waste to energy - 1 x 13.5MW 290.1 189.5 37.1 0.189

2030 1 Wind w/ storage – 1 x 1 MW 291.1 192.1 35.3 0.236

2031 1 Wind w/ storage – 1 x 1 MW 292.1 194.7 33.6 0.283

2032 25 Imp. Biomass - 1 x 25 MW 317.1 197.2 43.1 0.044

2033 317.1 199.8 41.2 0.056

2034 317.1 202.5 39.3 0.083

2035 1 Wind – 1 x 1 MW 318.1 205.4 37.4 0.122

2036 66.1 61.7

LSD38 – 1 x 38 MW

LSD17 – 1 x 17 MW

Wind – 3 x 1 MW


Retire

Wind – 2 x 1 MW

Solar 1 x 1 MW

L/fill Gas – 1 x 1.5 MW 313.7 208.1 36.3 0.214


Capacity AddedYear


5.1.2 High Demand World

In the high world, electricity demand is predicted to grow at an average of 3.0% per

annum over the planning period. Consequently, the actual reserve margin is

expected to be below the planning criteria of 32% from 2013 until new generation

comes on-line in 2017.

In the Liquid +RE scenario, 472.6 MW of new capacity is required over the planning

period. Solar, wind and landfill gas technologies feature in the plan from 2016, while

biomass and anaerobic digestion technologies start to feature in the plan from 2018

and 2034 respectively. Overall, biomass accounts for 25.0 MW, landfill gas –

3.0MW, anaerobic digestion –1.25MW, solar – 14.0 MW and wind –20.0 MW. By

2036, RE technologies account for 15.0% of the energy generated. The net present

value of this plan is $5.961 billion.

Over the planning horizon, the Liquid + NatGas + RE scenario requires the addition

of 451.2 MW of capacity. While natural gas features heavily in this plan, HFO and

diesel continue to feature throughout the plan due to the limit of 28 mmscf/day

assumed for natural gas. RE technologies included in this plan are landfill gas, wind,

anaerobic digestion, biomass and solar technologies. These technologies represent

14.6% of the energy generated in 2036. The net present value of this plan is $4.938

billion.

The Liquid + Natural Gas Restricted + RE scenario requires a total of 456.0 MW of

new capacity over the planning period, made up predominately of natural gas and

HFO burning reciprocating engines. Landfill gas, biomass, anaerobic digestion,

solar, wind and waste to energy technologies also feature in the plan and account

for 19.8% of the energy generated in 2036. The cost of this plan is $5.186billion.

In the Liquid + Natural Gas Restricted + RE forced scenario, all renewable

technologies with the exception of wind with storage are included in order to attain


the target of 29% of energy generated by renewables by 2029. The total new

capacity required over the planning horizon is 454.9 MW. The net present value of

this plan is $5.365 billion.

In the liquid +RE forced scenario, 448.2 MW of new capacity is required over the

planning period. All of the candidate renewable technologies are included in order to

attain the target of 29% of energy generated by renewables by 2029. The net

present value of this plan is $6.096 billion.

Further details of the results of the scenarios in the high demand world are included

in Appendix J.

5.1.3 Low Demand World

In the low world, electricity demand is forecasted to decrease at an average of 0.4%,

per annum, over the planning horizon.

In the liquid +RE scenario, 215.4 MW of new capacity is required over the planning

period. Wind, solar and landfill gas technologies feature in the plan from 2016, while

biomass features in the plan from 2018. In 2036, RE technologies account for 27.4%

of the energy generated. The net present value of this plan is $4.112 billion.

Over the planning horizon, the Liquid +NatGas + RE scenario requires the addition

of 191.1 MW of capacity. This plan requires the installation of two 20 MW OCGT

units in 2016 along with three 17.0 MW medium speed units all utilizing natural gas.

No other plant is required in this plan until 2027. The only renewable energy

technology included in this plan is one 1.5 MW landfill gas generator being selected

in 2035. This represents 2.3% of the energy generated in 2036. The net present

value of this plan is $3.905 billion.


Over the planning horizon, the Liquid + Natural Gas Restricted + RE scenario

requires a total of 193.9 MW of new capacity to be added to the system. One

hundred and five megawatts of reciprocating natural gas burning capacity is added

to the system in 2017 with a further 17.0 MW in 2027 and 17.0 MW in 2028. Fifty-

four megawatts of reciprocating capacity is the final addition to the system in 2036.

RE technologies do not feature in this plan. The cost of this plan is $3.942 billion.

In the Liquid + Natural Gas Restricted + RE forced scenario, biomass, landfill gas,

anaerobic digestion, wind and wind with storage technologies are included in the

plan in order to attain the target of 29% of energy generated by renewables by 2029.

The total new capacity required over the planning horizon is 217.8 MW. The net

present value of this plan is $4.081 billion.

In the Liquid + RE forced scenario, biomass, landfill gas, anaerobic digestion and

wind technologies are included in the plan in order to attain the target of 29% of

energy generated by renewables by 2029. The total new capacity required over the

planning horizon is 214.9 MW. The net present value of this plan is $4.114 billion.

Further details of the results of the scenarios in the base demand world are included

in Appendix K.

5.2 Sensitivities

After determining the optimal plan using the base assumptions for each scenario,

sensitivities were performed on the optimal plans. Figure 16 shows the results of the

NPV sensitivity tests performed on the optimal plans for each scenario, in relation to

fuel price, capital price and discount rate. Further details are included in Appendix L.


Figure 16: NPV Sensitivities on Optimal Plans for each Scenario

5.3 Analysis

The net present value results (NPV) presented in Table 31, all represent least-cost

plans for the respective scenarios. The scenario which results in the lowest NPV

over the planning horizon is Scenario 2, in which the model was permitted to select

freely between all conventional and renewable generating technologies. Additionally,

as shown in Figure 16, this scenario remained the lowest across all demand worlds

(low, base and high) and sensitivity test runs (discount rates, capital and fuel costs).

The NPV ranking of the scenarios also remain fixed for all sensitivity tests. However,

these NPV results on their own are insufficient for decision making, as they do not

capture all of the risks associated with each scenario.

1,500,000

2,500,000

3,500,000

4,500,000

5,500,000

6,500,000

7,500,000

8,500,000

Scen

. 1: L

Q +

RE

Scen

. 2: L

Q +

RE

+ N

G

Scen

. 3: L

Q +

RE

+ N

Gr

Scen

. 4: L

Q +

REf

+ N

Gr

Scen

. 5: L

Q +

Ref

Scen

. 1: L

Q +

RE

Scen

. 2: L

Q +

RE

+ N

G

Scen

. 3: L

Q +

RE

+ N

Gr

Scen

. 4: L

Q +

REf

+ N

Gr

Scen

. 5: L

Q +

Ref

Scen

. 1: L

Q +

RE

Scen

. 2: L

Q +

RE

+ N

G

Scen

. 3: L

Q +

RE

+ N

Gr

Scen

. 4: L

Q +

REf

+ N

Gr

Scen

. 5: L

Q +

Ref

BASE HIGH LOW

NP

V (

$0

00

)

Base

Fuel - High

Fuel - Low

Capital - High

Capital - Low

Discount - High

Discount - Low


The primary risks associated with the five scenarios are the timing and availability of

imported natural gas and biomass.

5.3.1 Natural Gas Availability & Interruption Risk

Scenarios 2, 3 and 4 all assume that imported natural gas is available in the future

for power generation. At present there are small volumes of locally produced natural

gas available on the island, but this is used by domestic and small commercial

customers and none is available for power generation. A source of imported natural

gas will therefore be required to support Scenarios 2 to 4. The Government of

Barbados has been pursuing a number of options for the importation of natural gas

from Trinidad & Tobago over the past several years. At the time of writing,

discussions on a potential subsea gas pipeline were the most advanced, but

investigations into compressed natural gas (CNG) and micro liquefied natural gas

(micro-LNG) were also ongoing.

Given the uncertainty in timing of these natural gas supply options and the supply

interruption risks, made that much more acute by the likely dependence on a single

supplier and transportation method, any gas burning generating capacity that is

installed in Scenarios 2 to 4 must be capable of operating on an alternative fuel. For

combustion turbines the alternative fuel would be either diesel or Jet A1; for

reciprocating engines the alternative fuel would be heavy fuel oil. The risk of delays

in the natural gas supply, or gas never becoming available over the planning

horizon, can therefore be measured in two ways: firstly, by the impact that operating

on the alternative fuel for the duration of the delay has on the NPV of the least-cost

plan in each scenario and secondly by the increase in generating cost that results

from the delay. Additionally, the impact on electricity rates due to a sudden increase

in the fuel clause adjustment if the natural gas supply is interrupted must also be

considered.


One key distinguishing feature between the liquid fuel and restricted gas plans (i.e.

Scenarios 1, 3, 4 & 5) and the unrestricted gas plan (Scenario 2) is the mix of

combustion turbines and reciprocating engines in each. In the unrestricted gas plan

(Scenario 2), a significantly higher proportion of combustion turbines make up the

overall generation mix when compared to the liquid fuel and restricted gas plans.

Consequently, Scenario 2 experiences the greatest increases in fuel operating costs

when gas is delayed or interrupted in the model. Figure 17 shows the proportion of

generation technologies installed over the planning period in Scenarios 1, 2 and 3.

The specific impact of natural gas supply delays on the NPV of Scenario 2 and 3 is

shown in Figure 18. The fuel cost in Scenario 1 is independent of gas and therefore

remains fixed for gas interruptions. Scenario 2 remains the least-cost option for

delays in natural gas supply up to around the year 2024, and Scenario 3 is least-cost

for delays beyond 2024 up to around 2030. However as the chart shows, the NPV of

Scenario 2 and 3 are 12.6% and 5.3% higher than that of Scenario 1 over the entire

planning period if gas is unavailable.

Figure 17: Proportion of Installed Generating Technologies in scenarios 1, 2 & 3

Proportion of Installed Generating Technologies in Scenarios 1, 2 & 3

Renewable Reciprocating Engines Combustion Turbines

20%

18% 62%

Scenario 1 Liquid Fuel

97%

3%

Scenario 2 Natural Gas

1%

99%

Scenario 3 Natural Gas Restricted


Figure 18: Impact of Delayed in Natural Gas Availability on NPV

Figure 19 illustrates the impact of natural gas supply delays on the overall electricity

generating cost between 2017 and 2025. Operation of the combustion turbine units

installed under Scenario 2 when gas is delayed, results in annual generating costs

that are between 14% and 23% higher than those in Scenario 1.

Figure 19: Impact of Delayed Natural Gas Availability on Total Generation Cost

3,000,000

3,500,000

4,000,000

4,500,000

5,000,000

5,500,000

Gas availablefrom 2017

Gas delayeduntil 2020

Gas delayeduntil 2025

Gasunavailable

NP

V (

20

12

BB

D$

00

0)

Impact of Delayed Natural Gas Availability:NPV Comparison of Liquid Fuel & Natural Gas Scenarios

Scenario 1 NPV (Liquid Fuel)Scenario 2 NPV (Natural Gas)Scenario 3 NPV (Natural Gas Restricted)

0.20

0.25

0.30

0.35

0.40

0.45

2017 2018 2019 2020 2021 2022 2023 2024 2025

Ge

ne

rati

ng

Co

st (

BB

D$

/kW

h)

Impact of Delayed Natural Gas Availability on theAnnual Generating Cost of Liq. Fuel & Nat. Gas Scenarios

Scenario 2 Generating Cost (Gas Delayed)Scenario 2 Generating Cost (Gas Available)Scenario 1 Generating Cost (Liquid Fuel)


The impact of natural gas interruptions on the fuel cost of Scenarios 2 and 3 are

shown in Figure 20. The fuel cost in Scenario 1 is independent of gas and therefore

remains fixed for gas interruptions. There is a significant fixed cost associated with

the importation of natural gas, which is expected to be reflected in a ‘take-or-pay’

component of the gas supply contract. The generating plant would not be expected

to pay this fixed cost for supply interruptions caused by the gas supplier and/or

transporter; however it would apply in circumstances where the generator is at fault

– for example, a failure in gas handling equipment on the generator’s side of the

custody transfer point. The impact of both gas interruption cases are therefore

shown in Figure 20.

Figure 20: Impact of 1-Year Gas Interruption in 2018 on Fuel Cost

The calculations have been done for a one-year interruption in the year 2019, but

would also be representative of the average monthly fuel cost impact for a one-

month interruption during the year. In Scenario 2, an interruption is expected to

increase fuel costs by 34.5% excluding the fixed ‘take-or-pay’ price for gas and

61.6% if the fixed price is included. In Scenario 3, the impact of gas interruptions are

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

Gas Available Gas Interrupted(excl. fixed cost)

Gas Interrupted(incl. fixed cost)

Fue

l Co

st (

20

12

BB

D$

/kW

h)

Impact of a 1-Year Natural Gas Interruption in 2019on Fuel Cost

Scenario 1 FCA (Liquid Fuel)Scenario 2 FCA (Natural Gas)Scenario 3 FCA (Natural Gas Restricted)


significantly lower since the reciprocating generators in that plan switch to heavy fuel

oil rather than the diesel alternative used by gas turbines in Scenario 2.

The calculations and data used to create the charts shown in Figures 18, 19 and 20

are tabulated in Appendix N. Scenarios 4 and 5 are higher-cost ‘forced RE’

variations of Scenarios 3 and 1 respectively, and were therefore not included on the

charts. However, similar results for these scenarios are also tabulated in Appendix

N.

Government’s efforts to secure an imported supply of natural gas for the island have

been on-going for well over ten years. At the time of writing, the Government of

Barbados was in discussion with a number of potential developers for the supply of

natural gas by pipeline, LNG or CNG, but no firm proposals or quotations had been

received and no agreements reached. It is therefore very difficult to judge the likely

timing of natural gas becoming available and the possibility exists that it will not be

available during the planning period. In the current circumstances, the least cost

plan for Scenario 1, in which only liquid fuels and renewable energy options are

available, is the preferred option. This scenario allows for migration to Scenario 3 in

the event that gas becomes available, by switching the reciprocating units to gas.

Scenario 3 has a higher NPV than Scenario 2, but is the preferred gas scenarios,

since it mitigates the significant rate shock associated with a gas supply interruption

in Scenario 2.

5.3.2 Biomass Availability & Risks

The developer of the proposed 25MW biomass plant, the Barbados Cane Industry

Corporation, has indicated that they are targeting a commissioning date of 2016 for

the plant. Based on a review of the schedule and feedback from stakeholders

received during public consultations, BL&P is of the view that 2018 is a more

realistic in-service date given the current status of the project and the requirement

for conducting trials to validate assumptions made for the proposed alternative


biomass fuel Leucaena. The earliest installed date for the biomass plant was

therefore set at 2018 in the production cost simulation model. If the biomass plant

does become available in 2016, there would be an overall decrease in the NPV of

$24.755 million or 0.50% for the liquid + Re scenario in the base world. This is

0.03% higher than the optimized plan if the model were allowed to select it for

installation in 2016 (provided in Appendix M). However, given the relatively low

likelihood of this occurring and the low NPV impact, this risk is considered

acceptable.

If the plans for biomass do not materialize within the study planning period,

reciprocating engines are the likely least-cost replacement. This will be evaluated in

a subsequent IRP update if the biomass project does not proceed.

5.3.3 Renewable Energy Policy Indicative Target

The Government of Barbados has issued a draft National Sustainable Energy Policy

(NSEP) for Barbados in March 2012with the stated objectives of reducing energy

costs, improving energy security and enhancing environmental sustainability. The

draft NSEP identifies “an indicative target of about 29% of all electricity consumption

to be generated by renewable sources by 2029”. Although identified as indicative,

Scenarios 4 and 5 were created to determine the least-cost plans for achieving this

target. In a liquid fuel future, forcing the model to achieve the policy target (i.e.

Scenario 5) results in an increase in NPV of 1.0% over the optimum plan in Scenario

1.In a natural gas future, forcing the model to achieve the policy target (i.e. Scenario

4) results in an increase in NPV of 5.1% over the optimum plan in Scenario 3.

5.3.4 Proposed Waste to Energy Facility

The Government of Barbados has announced plans to develop up to 60 MW of

waste-to-energy (WTE) capacity. WTE was not selected as a least-cost option in the

five initial scenarios modeled in the IRP, however Government has advised that it

will form part of the island’s waste management strategy going forward. At the time


of writing, firm details on the cost, capacity and operating characteristics of the WTE

plant under consideration were not available from Government. However, BL&P was

advised that plasma arc gasification technology was proposed and the plant could

be in service by 2018. In the absence of further information from project proponents,

plant assumptions for this technology were drawn from references which were found

for a similar plant under construction in the UK (Westinghouse Plasma Corporation,

2012) and are presented in Table 38.

Table 38: Waste-to-Energy (Plasma Arc) Assumptions

In order to determine the impact that this development would have on short-term

expansion requirements, a derivative of Scenario 1 was created in which 60 MW of

WTE generating capacity was forced into service in 2018, and the expansion model

allowed to re-optimize. The resulting expansion plan for this new scenario (Scenario

6: Liquid Fuel + RE + WTE), is shown in Table 39. The net present value of this plan

is $5.334 billion. This represents the highest net present value of all of the scenarios

modeled. Under this plan 52.8% of energy in 2029 is generated by RE technologies.

WASTE TO

ENERGY -

(PLASMA ARC)

Capacity per unit (MW) 30.0

Firm Capacity (MW) 30.0

No. of units built 2

Build Date 1/1/2018

Lifetime (yrs) 30

Capacity Factor 85.0

Forced Outage Rate (%) 6.0

Average Annual Maintenance (Days) 30

Auxiliary Power Consumption (%) 7.0

Overnight Capital Cost ($/kW) 18,000 - 25,000

Fixed O & M Cost ($/kW/yr) 700 - 1,400

Variable O & M ($/MWh) 15.00 - 20.00


Table 39: Build Schedule for Liquid + WtE Forced Scenario in Base World

In this new scenario, the least-cost plan calls for the installation of 47 MW of

reciprocating capacity in 2017 coincident with the retirement of the steam units in

2017.

The NPV for all six scenarios is summarized in Table 40.


LOLP


2012 239.1 157.4 37.3 0.205

2013 239.1 156.7 37.9 0.205

2014 239.1 157.2 37.4 0.205

2015 239.1 156.9 37.7 0.205

2016 11.5


Wind – 2 x 1 MW

Solar - 8 x 1 MW 250.6 158.6 37.2 0.209

2017 53 51.9

LSD30 – 1 x 30 MW

LSD17 – 1 x 17 MW

L/fill Gas – 1 x 1.5 MW 249.5 160.3 36.8 0.151

2018 86

Biomass - 1x 25 MW

Waste to energy - 2 x 30 MW

Wind – 1 x 1 MW 335.5 161.1 84.5 0.000

2019 51.5 284 164.6 53.8 0.027

2020 284 167.2 51.4 0.031

2021 1 Wind – 1 x 1 MW 285 169.9 49.0 0.047

2022 13 272 172.4 40.5 0.257

2023 272 174.7 38.6 0.344

2024 18.7 LSD17 – 1 x 17 MW 290.7 177.0 47.0 0.054

2025 20 1 Wind – 1 x 1 MW 271.7 179.2 34.2 0.433

2026 271.7 181.5 32.5 0.444

2027 20 31 GT30 – 1 x 30 MW 282.7 184.1 36.5 0.381

2028 20 18.7 LSD17 – 1 x 17 MW 281.4 186.7 33.6 0.391

2029 2.25

Wind – 1 x 1 MW


2030 21 GT20 – 1 x 20 MW 304.65 192.1 41.3 0.139

2031 304.65 194.7 39.4 0.213

2032 1 Wind – 1 x 1 MW 305.65 197.2 37.7 0.284

2033 305.65 199.8 35.9 0.378

2034 305.65 202.5 34.1 0.417

2035 305.65 205.4 32.2 0.478

2036 73.1 70.95

LSD30 – 1 x 38 MW

LSD17 - 1 x 17 MW

Wind – 5 x 1 MW


Wind w/ storage - 5 x 1 MW

Solar - 1 x 1 MW


Retire

Wind – 2 x 1 MW


Solar - 8 x 1 MW 303.5 208.1 32.0 0.680


Capacity AddedYear


Worlds Scenarios Description NPV ($000)

Base






Scenario 6 LQ + RE + WtEf 5,334,102

High







Low







Table 40: NPV Results for the Six Scenarios

5.3.5 Other Policy Considerations

In addition to the NPV analysis, policy makers may wish to consider a broad range

of economic, social and environmental factors associated with the expansion plan.

These might include criteria such as the foreign exchange impact of each scenario,

land, water and CO2 impacts, energy security and fuel import vulnerability. The draft

NSEP indicates that “where a sustainable energy measure could increase energy

security and environmental sustainability, but would also increase costs to the

economy, the Government of Barbados will pursue it when the energy security,

environmental sustainability, and other local economic benefits (including other

positive economic externalities, contribution to the country’s economy and quality of

life) exceed the economic costs”.


While it is possible to attribute costs to criteria such as those listed above and

include these in the NPV optimization, these costs should be based on the economic

value the country places on each criteria as determined by policy makers. For

example, the purchase price of water in Barbados may not accurately reflect its

economic value given the island’s water scarcity. Similarly, international market

prices for CO2 may not be applicable in all scenarios, since ‘additionality’ (a criteria

for eligibility for CO2 financing15) of the generating projects that are least-cost options

may be difficult to prove.

The approach of internalizing external costs, also known as External Cost Analysis

(ECA), is practiced among some electric utility regulators, who for example require

utilities to put a cost on emissions and include these in the NPV calculations, to

determine total societal costs (ECO Northwest, 1993). While there are some benefits

to this approach, which is rooted in welfare economics, it has the following

disadvantages (Hobbs & Meier, 2000):

Some basic principles of welfare economics are not universally accepted, e.g.

net benefits matter with no consideration of distribution among stakeholders.

Fundamental value judgments could become buried in calculations rather

than explicitly considered by decision makers.

Multicriteria Decision methods address some of the deficiencies of ECA methods,

based on their ability to make the tradeoffs between criteria more explicit and the

greater insight and input they provide to stakeholders and decision makers.

Table 41summarizes the performance of each scenario’s least-cost expansion plan

in relation to several criteria in addition to NPV. A sample multicriteria decision

analysis methodology is provided in Appendix Q for the consideration of policy

makers.

15

http://cdmrulebook.org/84

http://cdmrulebook.org/84


Table 41: Characteristics of Least-Cost Plans

5.4 Recommendation

Currently, natural gas is unavailable and the timeline for its availability remains

uncertain. Therefore, amongst Scenarios 1 to 5, Scenario 1 (Liquid + RE), is the

preferred plan with conventional generating technology units being configured to

permit dual-fuel conversion to natural gas when it becomes available. However,

given Government’s stated plans to develop up to 60 MW of WTE capacity, a

derivative of Scenario 1, in which WTE is forced into service in 2018 (i.e. Scenario 6:

liquid fuel + RE + WTE), was modeled. At the time of writing, there was uncertainty

surrounding the specific capacity and technology for the WTE plant that will

eventually be selected by Government. However, in order to mitigate against

potential over-capacity should the WTE generating capacity be commissioned as

planned, short-term expansion should be based on Scenario 6.

Table 42 shows the build schedule for Scenario 6.While the table identifies specific

reciprocating diesel units, it is recommended that the engine type and size to meet

the required reciprocating generating capacity be determined through a tendering

process. The net present value of this plan is $5.334 billion.

Worlds Scenarios NPV ($000)

C02

(million

MT)

Water

(million

Ga)

Land Use

(acres)

Fuel

Diversity

Foreign

Exchange

($000) Achievability

2017 Gas

Interruption

Cost ($000)

Renew %

in 2029

Renew % in

2036

LQ + RE 4,985,051 18,316 2,512 523 35.94% 4,452,779 High 0 20.8% 20.0%

LQ + RE + NG 4,227,676 13,889 769 70 42.78% 3,916,366 Medium 97,864 0.9% 3.3%

LQ + RE + NGr 4,457,170 15,589 430 31 47.58% 4,074,542 Medium 51,947 1.7% 2.3%

LQ + REf + NGr 4,645,222 13,556 2,480 687 71.11% 4,105,925 Low 39,485 29.0% 29.0%

LQ + REf 5,035,424 17,615 2,958 749 42.78% 4,464,125 Medium 0 29.5% 29.0%

LQ + WTEf 5,334,102 13,141 6,485 1,318 71.95% 4,371,522 Low 0 52.8% 49.1%

LQ + RE 5,961,262 23,698 2,587 842 31.35% 5,376,707 High 16.6% 15.0%

LQ + RE + NG 4,937,955 16,672 1,819 708 59.37% 4,499,457 Medium 15.8% 14.6%

LQ + RE + NGr 5,185,558 20,461 1,752 993 64.32% 4,687,628 Medium 14.3% 19.8%

LQ + REf + NGr 5,365,404 17,263 3,264 972 71.28% 4,800,408 Low 19.4% 29.0%

LQ + REf 6,095,605 22,109 3,718 952 43.67% 5,452,355 Medium 29.0% 29.0%

LQ + WTEf 6,310,660 18,531 6,548 1,562 63.26% 5,295,430 Low 40.2% 34.8%

LQ + RE 4,112,078 13,711 2,447 344 41.47% 3,616,876 High 27.8% 27.4%

LQ + RE + NG 3,904,750 11,728 289 17 50.83% 3,625,233 Medium 1.3% 2.3%

LQ + RE + NGr 3,942,138 12,009 304 14 50.78% 3,614,724 Medium 1.3% 1.2%

LQ + REf + NGr 4,080,506 10,865 1,817 281 72.94% 3,302,322 Low 29.0% 29.0%

LQ + REf 4,113,915 13,615 2,471 337 43.56% 3,614,519 Medium 29.0% 29.0%

LQ + WTEf 4,465,421 8,575 2,039 1,078 80.54% 3,389,178 Low 71.2% 70.0%

Base

High

Low


Table 42: Build Schedule for Recommended Plan in Base Demand world

5.5 Avoided Generating Costs

The definition of avoided cost, applicable to our analysis, is adopted from the United

States Public Utility Regulatory Policy Act (PURPA). According to the definition of


LOLP


2012 239.1 157.4 37.3 0.205

2013 239.1 156.7 37.9 0.205

2014 239.1 157.2 37.4 0.205

2015 239.1 156.9 37.7 0.205

2016 11.5


Wind – 2 x 1 MW

Solar - 8 x 1 MW 250.6 158.6 37.2 0.209

2017 53 51.9

LSD30 – 1 x 30 MW

LSD17 – 1 x 17 MW

L/fill Gas – 1 x 1.5 MW 249.5 160.3 36.8 0.151

2018 86

Biomass - 1x 25 MW

Waste to energy - 2 x 30 MW

Wind – 1 x 1 MW 335.5 161.1 84.5 0.000

2019 51.5 284 164.6 53.8 0.027

2020 284 167.2 51.4 0.031

2021 1 Wind – 1 x 1 MW 285 169.9 49.0 0.047

2022 13 272 172.4 40.5 0.257

2023 272 174.7 38.6 0.344

2024 18.7 LSD17 – 1 x 17 MW 290.7 177.0 47.0 0.054

2025 20 1 Wind – 1 x 1 MW 271.7 179.2 34.2 0.433

2026 271.7 181.5 32.5 0.444

2027 20 31 GT30 – 1 x 30 MW 282.7 184.1 36.5 0.381

2028 20 18.7 LSD17 – 1 x 17 MW 281.4 186.7 33.6 0.391

2029 2.25

Wind – 1 x 1 MW


2030 21 GT20 – 1 x 20 MW 304.65 192.1 41.3 0.139

2031 304.65 194.7 39.4 0.213

2032 1 Wind – 1 x 1 MW 305.65 197.2 37.7 0.284

2033 305.65 199.8 35.9 0.378

2034 305.65 202.5 34.1 0.417

2035 305.65 205.4 32.2 0.478

2036 73.1 70.95

LSD30 – 1 x 38 MW

LSD17 - 1 x 17 MW

Wind – 5 x 1 MW


Wind w/ storage - 5 x 1 MW

Solar - 1 x 1 MW


Retire

Wind – 2 x 1 MW


Solar - 8 x 1 MW 303.5 208.1 32.0 0.680


Capacity AddedYear


PURPA, avoided cost is the fixed and running costs of an electric utility system

which can be avoided by obtaining energy or capacity from qualifying facilities. The

avoided cost is the forward looking change in cost, alternatively referred to as

marginal or incremental cost, which occurs as a consequence of installing a

particular generating resource.

Avoided costs for the BL&P electric grid have been defined as the costs to the

electric utility of energy or capacity, or both, which, but for the purchase from the

qualifying facility or qualifying facilities, the utility would generate itself or purchase

from other sources. Avoided costs, therefore, incorporate projections of future year-

by-year BL&P system costs.

The pertinent costs considered for the avoided costs calculations are:

generation fixed costs (capacity costs);

generation variable costs (energy costs).

Generation fixed costs (capacity) include capital costs for new generation capacity to

be installed over the planning period and the fixed operation and maintenance costs

for these facilities. These costs are dependent on the characteristics of the

generation plants. Variable (energy) costs include fuel costs and variable operation

and maintenance costs.

Calculations of generation avoided costs, for BL&P, must be consistent with the IRP

planning methodologies, in order to identify the most cost-efficient resources and to

minimize the cost of providing energy to consumers. To this end, the Plexos Utility

Planning software was employed to simulate the various generation options, based

on potential new technology fuel types, fuel prices and projected demand growth for

the 25-year period.


Avoided costs were calculated for renewable technologies considered in this study.

Scenario 1 (liquid + renewables) was used to calculate the avoided cost for the

technologies. The avoided cost for technologies which contribute firm capacity to the

plan would have a capacity and energy component while technologies which are

non-firm would only possess an energy component.

For the firm technologies, namely biomass, waste to energy, landfill gas and

anaerobic digestion, an optimal plan was first determined without the technology for

which the avoided cost was being calculated. The NPV for fuel, fixed and variable

operating and maintenance cost and capital cost was determined. The technology

under consideration was then added with zero capital, operating and maintenance

cost to the model as a candidate plant. A new optimal plan was generated by the

model. The difference in NPV of the capital and fixed operating and maintenance

cost, divided by the unit capacity and number of years of operation, is the capacity

component of the avoided cost for the technology. The difference in NPV of the fuel

and variable operating and maintenance cost, divided by the NPV of the energy

generated by the unit, is the energy component of the avoided cost for the

technology.

For the non-firm technologies, namely wind and solar, an optimal plan was first

determined without the technology for which the avoided cost was being calculated.

The NPV for fuel and variable operating and maintenance cost was determined. The

technology under consideration was then added with zero capital, operating and

maintenance cost to the model from the year the technology is available without re-

optimization. The difference in NPV of the fuel and variable operating and

maintenance cost, divided by the NPV of the energy generated by the unit, is the

energy component of the avoided cost for the technology.


The avoided costs for the technologies considered in this study are shown in Table

43. Further details on the avoided cost calculations for the technologies are shown in

Appendix P.

Table 43: Avoided Cost of Renewable Technologies

It is important to note, that the avoided generating costs calculated above, are

indicative based on the assumptions used in this study, exclude T&D costs and are

expressed in real 2012 dollars. The avoided cost may not be equivalent to the

avoided revenue requirement, as the avoided revenue requirement includes avoided

energy and capacity costs, as well as other factors (e.g., taxes). Consequently, the

avoided generating costs may not represent the negotiated price from an

Independent Power Producer.

Technology

Capacity

MW

Installation

Year

Capacity Cost

$/kW/yr

Energy C ost

$/MWh

Anearobic Digestion 2.5 2016 43.08 373.29

Biomass 25.0 2018 135.64 272.81

Landfill Gas 3.0 2016 151.48 350.38

Waste to Energy 13.5 2018 81.01 323.44

Solar 1.0 2016 - 429.32

Wind 1.0 2016 - 381.62


6 SUMMARY AND CONCLUSION

System expansion planning at BL&P has traditionally focused on identifying the

least-cost generation expansion plan from a range of generating supply options.

Integrated Resource Planning (IRP) enhances this process by taking into

consideration demand side resource options, as well as additional evaluation criteria

like energy security and environmental impact.

The expansion recommendation is based on an evaluation of the least-cost plans

identified by the production cost model for each demand world and fuel scenario

combination. The recommendation also takes into consideration the risks presented

by potential delays and/or interruptions in the future availability of natural gas and

biomass, and includes Government’s stated plan for a waste-to-energy generating

plant as part of the island’s waste management strategy. Other risks and

uncertainties associated with variables like fuel price and electricity demand growth

were addressed through sensitivity and scenario analyses. A broad range of

additional economic, social and environmental factors associated with each of the

least-cost plans were also calculated. These are presented in Appendix Q, along

with a sample multicriteria decision analysis methodology for the consideration of

policy makers.

The study was conducted in accordance with IRP best practices (Tellus Institute)

and provides a roadmap, outlining the options to be used in meeting future electricity

demands cost effectively and in compliance with regulatory requirements. A

transparent and participatory approach was employed throughout the process. The

recommendations have been informed by broad consultations with stakeholders who

participated in the process by reviewing assumptions and preliminary results and

providing input into the planning decision.

The IRP was developed using models that incorporate the best information at the

time of planning and will be updated periodically or as conditions change materially.


Technologies which are not technically or commercially viable and Transmission and

Distribution (T&D) expansion requirements were excluded from the scope of the

IRP.

6.1 Sustainable Energy Framework for Barbados

In July 2010, the Government of Barbados (GoB) completed a study titled

‘Sustainable Energy Framework for Barbados’ (SEFB). The objective of the study,

which was conducted by Castalia Strategic Advisors and financed by the IDB, was to

identify viable investments in renewables and energy efficiency to reduce Barbados’

dependency on fossil fuels and thus reduce energy costs, improve energy security

and enhance environmental sustainability. These objectives were also captured in a

draft National Sustainable Energy Policy (NSEP) issued by the Government of

Barbados in March 2012.

Both the SEFB report and the draft NSEP identified indicative targets for renewable

energy (RE) and energy efficiency (EE) of 29% and 22% respectively by 2029.

Scenario 1, the preferred plan amongst scenario 1 to 5 as described in section 5.4,

achieves RE levels of 20.8% by 2029 for the base demand forecast world. Forcing

this scenario to achieve 29% RE by 2029 will increase the NPV of the plan by 1%.

The recommendation, based on Scenario 6 which includes Government’s plan to

develop up to 60 MW of WTE, achieves 52.8% RE by 2029, while increasing the

NPV by 7.0% over Scenario 1.The potential impact of EE measures are accounted

for in the low demand forecast world, which allows for up to 28.3% reductions

through EE by 2029.

Also arising out of the SEFB report, were recommendations relating to legislative

and regulatory changes aimed at promoting the development of viable renewable

energy and energy efficiency resources. At the time of writing, the draft energy policy

and legislative changes were under review, but not yet finalized, by the GoB.


However, the IRP study takes the proposed changes into account and follows a

methodology which is consistent with the recommendations of the SEFB report.

6.2 Recommendation

To assess the risks and uncertainties associated with external market conditions, the

IRP study examined five initial scenarios representing plausible future paths relating

to fuel types and technologies used. The specific fuels and technologies represented

by each scenario are summarised in Table 44.

Table 44: Scenario Matrix of Fuels & Technologies

Each of these scenarios were evaluated using three possible electricity demand

growth ‘worlds’, resulting in a total of fifteen plans being evaluated. Sensitivities for

changes in capital costs, fuel costs and discount rates were also conducted on each

of the fifteen plans.

Natural gas is currently unavailable for power generation and the timeline for its

availability remains uncertain. Amongst Scenarios 1 to 5, Scenario 1 is the preferred

scenario as it allows for the migration to the lower NPV Scenario 3 in the event that

gas becomes available in the future, by switching the reciprocating units to gas.

Scenario 3 has a higher NPV than Scenario 2, but is the preferred gas scenario,

since it mitigates the significant rate shock associated with a gas supply interruption

in Scenario 2.

Scenario 1:

LF+RE

Scenario 2:

LF+RE+NG

Scenario 3:

LF+RE+NGr

Scenario 4:

LF+REf+NGr 1

Scenario 5:

LF+Ref 1

Liquid Fuel (LF)

Natural Gas (NG) x x

Renewable Energy (RE)

Gas Turbines 2

x x

Notes

1. The model is forced to install 29% RE by 2029 in scenarios 4 & 5.

2. Gas turbines excluded in scenarios 3 & 4 due to high gas interruption cost


Scenario 6 was introduced given Government’s stated plans to develop up to 60 MW

of WTE capacity. Scenario 6 is a derivative of Scenario 1 in which WTE is forced

into service in 2018 (i.e. Scenario 6: liquid fuel + RE + WTE). At the time of writing,

there was uncertainty surrounding the specific capacity and technology for the WTE

plant that will eventually be selected by Government. However, in order to mitigate

against potential over-capacity should the WTE generating capacity be

commissioned as planned, short-term expansion should be based on Scenario 6.

The first ten years of the resulting least-cost plan for Scenario 6 are displayed in

Table 45.

If Government’s plans for the WTE plant are cancelled or modified from the

assumptions used in the IRP, this scenario will have to be remodeled and revised

accordingly.

Year Demand

GWh

Supply-side Resources Demand-side Resources

Retire New Capacity

2012 981

2013 980

2014 979

2015 984

2016 993 L/fill Gas –1.5 MW

Solar – 8 MW

Wind – 2 MW

2017 1005 S1, S2 – 40 MW

GT02 – 13 MW

Reciprocating Engines – 47 MW

L/fill Gas –1.5 MW

2018 1018 Biomass –25 MW

Waste to Energy – 60 MW

Wind – 1 MW

2019 1036 D10, D11, D12,

D13 – 50 MW

WH01 – 1.5 MW

2020 1054

2021 1074 Wind – 1 MW

Table 45: Scenario 6: Least-cost Integrated Resource Plan

Future DSM


The model assumes that all plant retirements take place at 00:00hrs on January 1st

of the years identified in the table. In practice, an overlap of around six (6) months

may be required between retired and replacement capacity to ensure a reliable

transition and allow for any teething problems with the new plant to be addressed.

Figure 21 shows the contribution to total generation by generating technology for the

recommended plan over the planning period. The annual generation for the

recommended plan is shown in Figure 27 of Appendix O.

Figure 21: Generation by Energy Source for Recommended Plan

The IRP recommendations are contingent on the following:

Acquiring land access for the development of wind energy and/or successful

negotiation of Power Purchase Agreements with Independent Power

Producers (IPPs) for wind energy.

0

200

400

600

800

1000

1200

1400

1600

20

12

20

13

20

14

201

5

20

16

20

17

20

18

20

19

20

20

20

21

20

22

20

23

20

24

202

5

20

26

20

27

20

28

20

29

20

30

20

31

20

32

20

33

20

34

203

5

20

36

Ene

rgy

(GW

h)

Year

Solar

Anearobic Digestion

Landfill Gas

Wind

Biomass

Waste to Energy

New Gas Turbines

New LSD & MSD

Gas Turbine

Cogen

LSD

Steam


Access to a secure supply of biomass, municipal solid waste and landfill gas

at the prices used in the IRP.

The generating capacity and timing of waste-to-energy and biomass is

achieved. If there are variations in the scope and timing of these projects, the

retirement schedule of existing units could be affected.

Extension of BL&P’s franchise which currently expires in 2028.

Compliance with legislative requirements.

The plan laid out in Table 1 provides a roadmap of expansion options to be used in

meeting future electricity demands cost effectively, given the constraints and

assumptions used in Scenario 6. Investment plans by the utility and potential

Independent Power Producers should be guided by the IRP, while taking into

consideration licensing, land availability and location specific development costs.

Two key issues were identified during the IRP process which will require additional

work:

As identified in the IRP Terms of Reference, Demand Side Management

(DSM) options evaluated in the IRP study were to be derived from the energy

efficiency recommendations made in the SEFB study conducted by IDB for

the Government of Barbados. However, based on subsequent feedback

received from the consultants who conducted the SEFB study, the energy

efficiency measures were found to be insufficiently well defined for modeling

in the IRP. A DSM study will be completed in 2014 to identify specific DSM

measures for implementation. It is important to note however, that the short-

term expansion recommendations (2013 to 2018) remain unchanged in the

low demand forecast world and is therefore compatible with the indicative EE

targets identified in the SEFB.

Based on a preliminary review of system impacts and practices in other island

grids, an intermittent Renewable Energy (RE) limit of 10% of peak demand

has been used in the study. An Intermittent RE Penetration study will be


completed in 2014 to further evaluate the issues associated with intermittent

RE and allowable limits.


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