ies thailand power sector vision part 2

ALTERNATIVES FOR POWER GENERATION IN THE GREATER MEKONG SUB-REGION

Volume5:

PowerSectorVisionfortheKingdomofThailand

Final

31 March 2016

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IntelligentEnergySystems IESREF:5973 ii

DisclaimerThis report has been prepared by Intelligent Energy Systems Pty Ltd (IES) and

MekongEconomics (MKE) in relation toprovisionofservices toWorldWideFund

forNature(WWF).Thisreportissuppliedingoodfaithandreflectstheknowledge,

expertiseandexperienceof IESandMKE. Inconducting theresearchandanalysis

for this report IESandMKEhasendeavoured tousewhat it considers is thebest

information available at the date of publication. IES and MKE make no

representationsorwarrantiesastotheaccuracyoftheassumptionsorestimateson

whichtheforecastsandcalculationsarebased.

IESandMKEmakenorepresentationorwarrantythatanycalculation,projection,

assumption or estimate contained in this report should or will be achieved. The

reliance that the Recipient places upon the calculations and projections in this

reportisamatterfortheRecipient’sowncommercialjudgementandIESacceptsno

responsibilitywhatsoeverforanylossoccasionedbyanypersonactingorrefraining

fromactionasaresultofrelianceonthisreport.

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IntelligentEnergySystems IESREF:5973 iii

AcronymsAD AnaerobicDigestion

ADB AsianDevelopmentBank

AEDP AlternativeEnergyDevelopmentPlan

ASEAN AssociationofSoutheastAsianNations

ASES AdvancedSustainableEnergySector

BAU BusinessAsUsual

BCM/Bcm BillionCubicMetres

BNEF BloombergNewEnergyFinance

BTU/Btu BritishThermalUnit

BP BritishPetroleum

CAGR CompoundAnnualGrowthRate

CAPEX CapitalExpenditure

CCGT CombinedCycleGasTurbine

CCS CarbonCaptureandStorage

COD CommercialOperationsDate

CSP ConcentratedSolarPanel

DEDE DepartmentofAlternativeEnergyDevelopmentand

Efficiency

DNI DirectNormalIrradiation

DTU TechnicalUniversityofDenmark

EE EnergyEfficiency

EEDP EnergyEfficiencyDevelopmentPlan

EGAT ElectricityGenerationAuthorityofThailand

EIA EnergyInformationAdministration

ENCO EnergyConservationPromotionFund

EPPO EnergyPolicyandPlanningOffice

ERC EnergyRegulatoryCommission

ESB EnhancedSingleBuyerModel

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IntelligentEnergySystems IESREF:5973 iv

ESCO EnergyServiceCompany

FIT Feed-inTariff

FOB FreeonBoard

FOM FixedOperatingandMaintenance

GDP GrossDomesticProduct

GHI GlobalHorizontalIrradiance

GMS GreaterMekongSubregion

GSP GasSubcooledProcess

GT GasTurbine

HV HighVoltage

HVDC HighVoltageDirectCurrent

IAEA InternationalAtomicEnergyAgency

IEA InternationalEnergyAgency

IES IntelligentEnergySystemsPtyLtd

INIR IntergradedNuclearInfrastructureReview

IPP IndependentPowerProducer

IRENA InternationalRenewableEnergyAgency

LCOE OverallLevelisedCostofElectricity

LNG LiquefiedNaturalGas

MEA MetropolitanElectricityAuthorityMEA

MKE MekongEconomics

MOU MemorandumofUnderstanding

MTPA MillionTonsperAnnum

MV MediumVoltage

NASA NationalAeronauticsandSpaceAdministration(the

UnitedStates)

NGV NaturalGasVehicle

NPV NetPresentValue

NREL NationalRenewableEnergyLaboratory(theUnitedStates)

OECD OrganisationforEconomicCo-operationandDevelopment

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IntelligentEnergySystems IESREF:5973 v

OPEC OrganisationofthePetroleumExportingCountries

OPEX OperationalExpenditure

PDP PowerDevelopmentPlan

PDR People’sDemocraticRepublic(ofLaos)

PEA ProvincialElectricityAuthority

PPA PowerPurchaseAgreement

PRC People’sRepublicofChina

PTT PetroleumAuthorityofThailand

PTTEP PTTExplorationandProduction

PV Photovoltaic

RE RenewableEnergy

ROR RunofRiver

RPR ReservestoProductionRatio

SES SustainableEnergySector

SPP SmallIndependentPowerProducer

SWERA SolarandWindEnergyResourceAssessment

SWH SolarWaterHeating

TCF/Tcf TrillionCubicFeet

TNB TenagaNasionalBerhad(Malaysia)

UN UnitedNations

USD UnitedStatesDollar

VOM VariableOperatingandMaintenance

VSPP VerySmallIndependentPowerProducers

WEO WorldEnergyOutlook

WWF WorldWideFundforNature

WWF-

GMPO

WWF–GreaterMekongProgrammeOffice

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IntelligentEnergySystems IESREF:5973 vi

TableofContents1 Introduction 8

1.1 ReportStructure 8

2 Background:Thailand’sElectricitySector 10

2.1 Overview 10

2.2 PowerSystem 11

2.3 InstalledCapacity 13

2.4 ElectricityDemand 14

2.5 GenerationSupply 16

2.6 ImportsandExports 17

3 DevelopmentOptionsforThailand’sElectricitySector 21

3.1 Overview 21

3.2 NaturalGas 22

3.3 CoalResources 26

3.4 NuclearPower 32

3.5 HydroPower 32

3.6 WindPower 33

3.7 SolarPower 38

3.8 GeothermalEnergy 43

3.9 Biomass 43

3.10BiogasandWaste 44

3.11OceanEnergy 45

3.12AlternativeEnergyDevelopmentPlan2015 45

3.13RenewableEnergyPotentialandDiversification 46

4 ThailandDevelopmentScenarios 48

4.1 Scenarios 48

4.2 TechnologyCostAssumptions 52

4.3 FuelPricingOutlook 54

4.4 ThailandRealGDPGrowthOutlook 55

4.5 PopulationGrowth 57

4.6 CommittedGenerationProjectsinBAU,SESandASESScenarios 57

4.7 RegionalTransmissionSystemIntegration 59

4.8 ImportsandExports 60

4.9 TechnicalEconomicPowerSystemModelling 61

5 BusinessasUsualScenario 63

5.1 BusinessasUsualScenario 63

5.2 ProjectedDemandGrowth 63

5.3 ProjectedInstalledCapacityDevelopment 65

5.4 ProjectedGenerationMix 68

5.5 GridtoGridPowerFlows 71

5.6 ProjectedGenerationFleetStructure 71

5.7 ReserveMarginandGenerationTrends 74

5.8 ElectrificationandOff-Grid 76

6 SustainableEnergySectorScenario 77

6.1 SustainableEnergySectorScenario 77


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IntelligentEnergySystems IESREF:5973 vii







7 AdvancedSustainableEnergySectorScenario 90

7.1 AdvancedSustainableEnergySectorScenario 90








8 AnalysisofScenarios 103

8.1 EnergyandPeakDemand 103

8.2 Energyintensity 105

8.3 GenerationMixComparison 106

8.4 CarbonEmissions 108

8.5 HydroPowerDevelopments 109

8.6 AnalysisofBioenergy 110

8.7 SecurityofSupplyIndicators 112

8.8 InterregionalPowerFlows 115

9 EconomicImplications 117

9.1 OverallLevelisedCostofElectricity(LCOE) 117

9.2 LCOEComposition 118

9.3 CumulativeCapitalInvestment 120

9.4 OperatingCosts,AmortisedCapitalCostsandEnergyEfficiencyCosts 125

9.5 FuelPriceSensitivity 130

9.6 ImpactofaCarbonPrice 131

9.7 RenewableTechnologyCostSensitivity 132

9.8 JobsCreation 133

10 Conclusions 137

10.1ComparisonofScenarios 138

10.2EconomicImplications 139

10.3IdentifiedBarriersfortheSESandASESforRenewableEnergy 140

10.4IdentifiedBarriersfortheSESandASESforEnergyEfficiency 142

10.5Recommendations 143

AppendixA TechnologyCosts 146

AppendixB FuelPrices 150

AppendixC MethodologyforJobsCreation 151

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IntelligentEnergySystems IESREF:5973 8

1 Introduction

Intelligent Energy Systems Pty Ltd (“IES”) and Mekong Economics (“MKE”) were

retained by WWF – Greater Mekong Programme Office (“WWF-GMPO”) to

undertakeaprojectcalled“Produceacomprehensivereportoutliningalternatives

for power generation in the Greater Mekong Sub-region”. This was to develop

scenarios for the countries of the GreaterMekong Sub-region (GMS) that are as

consistentaspossiblewiththeWWF’sGlobalEnergyVisiontothePowerSectorsof

all GreaterMekong Subregion countries. The objectives ofWWF’s vision are: (i)

contributetoreductionofglobalgreenhouseemissions(cutby>80%of1990levels

by2050);(ii)reducedependencyonunsustainablehydroandnuclear;(iii)enhance

energyaccess; (iv) takeadvantageofnewtechnologiesandsolutions; (v)enhance

power sector planning frameworks for the region:multi-stakeholder participatory

process;and(vi)developenhancementsforenergypolicyframeworks.

Thepurposeofthisreportistoprovidedetailedcountry-leveldescriptionsofthree

scenariosforthepowersectorofThailand:

• BusinessasUsual (BAU)powergenerationdevelopmentpathwhich isbased

oncurrentpowerplanningpractices,currentpolicyobjectives;

• Sustainable Energy Sector (SES) scenario, where measures are taken to

maximally deploy renewable energy1and energy efficiency measures to

achieveanear-100%renewableenergypowersector;and

• Advanced Sustainable Energy Sector (ASES) scenario,which assumes amore

rapid advancement and deployment of new and renewable technologies as

comparedtotheSES.

The scenarios were based on public data, independent assessments of resource

potentials, information obtained from published reports and power system

modellingoftheGMSregionfortheperiod2015to2050.

1.1 ReportStructure

Thisreporthasbeenorganisedinthefollowingway:

• Section2setsoutrecentoutcomesforThailand’selectricityindustry;

• Section3summarisesthemaindevelopmentoptionscoveringbothrenewable

energyandfossilfuels;

• Section4providesabriefsummaryofthescenariosthatweremodelledanda

summaryoftheassumptionsincommon;

• Section5setsoutthekeyresultsforthebusinessasusualscenario;

1Proposedbutnotcommittedfossilfuelbasedprojectsarenotdeveloped.Committedandexistingfossilfuel

basedprojectsareretiredattheendoftheirlifetimeandnotreplacedwithotherfossilfuelprojects.Aleastcost

combinationofrenewableenergygenerationisdevelopedtomeetdemand.

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• Section6setsoutthekeyresultsforthesustainableenergysectorscenario;

• Section7 sets out the key results for an advanced sustainable energy sector

scenario;

• Section 8 provides comparative analysis of the three scenarios basedon the

computationofanumberofsimplemetricsthatfacilitatecomparison;

• Section9providesanalysisoftheeconomicimplicationsofthescenarios;and

• Section10providesthemainconclusionsfromthemodelling.

Thefollowingappendicesprovidesomeadditionalinformationforthescenarios:

• AppendixAcontainsthetechnologycostassumptionsthatwereused;

• AppendixBprovidesthefuelpriceprojectionsthatwereused;and

• AppendixC setsout informationused toestimate jobscreationpotential for

eachscenario.

Note that unless otherwise noted, all currency in the report is Real 2014 United

StatesDollars(USD).

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2 Background:Thailand’sElectricitySector

2.1 Overview

Thailand’s electricity industry is managed under the so-called “Enhanced Single

BuyerModel(ESB)”.ThestructureoftheESBisprovidedinFigure1below.

Figure1 ThailandElectricityIndustryStructure

Source:ReplicatedbyConsultantbasedonERCData

Under the ESBmodel, the government-owned Electricity Generating Authority of

Thailand(EGAT) isthesinglebuyer,purchasingbulkelectricityfromprivatepower

producers and neighbouring countries and sells wholesale electric energy to two

distributingauthoritiesandasmallnumberofdirectindustrialcustomersaswellas

neighbouring utilities2. EGAT itself is the largest power producer owning and

operatingplantswithatotal installedcapacityover15,000MW3,orabout46%of

theentiregenerationsystem. Inaddition,EGATownsandoperatestheThailand’s

highvoltagetransmissionnetwork.

Private power producers in Thailand are comprised of Independent Power

Producers (IPPS) sellingelectricity toEGATatcapacitygreater than90MW,Small

IndependentPowerProducers(SPPPs)withcapacitysoldtoEGATequalorlessthan

2http://www.egat.co.th/en/index.php

3AsofJanuary2016,EGAT’sinstalledcapacitywas16,376MW.

IPPs(39%)

EGATGenerators

(46%)

SPPs(8%)

VSPPs(<1%)

Import/Exchange(7%)

TransmissionSystemOwner

NetworkSystemOperator&SingleBuyer

EGATDirectCustomers

(2%)Retail

SupplierDistributor

PEA(68%)

RetailSupplierDistributor

MEA(30%)

Customers Customers

EGAT(100%)

Gene

ratio

nTransm

ission

Policiesa

ndRegulations

Distrib

ution&Retail

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90MWandVerySmallIndependentPowerProducers(VSPPs)withcapacitysoldto

EGATequalorlessthan10MW.

The twodistribution authorities in Thailand areMetropolitan ElectricityAuthority

(MEA) responsible for power supply to Bangkok, Nonthaburi and Samut Prakarn,

andProvincialElectricityAuthority(PEA)isresponsibleforpowersupplytotherest

ofthecountry.ThemarketsharesoftheseentitiesareasatDecember2012.Note

thatnon-firmSPPsandVSPPscansellelectricitydirectlytothedistributionutilities.

Thailand’selectricitysystemisamediumsizesystemhavingtotalinstalledcapacity

of34,681MWasattheendof2014.Ithasamoderatedemandgrowthrate,with

electricityconsumptionincreasingfrom100.1TWhto168.2TWhatthecompound

annualgrowthrate(CAGR)of4.44%overtheperiodfrom2002to2014.

EnergyRegulatoryCommission(ERC)wasestablishedin2008toperformtheroleof

the regulator in electricity pricing and in ensuring sufficient supply of energy and

qualityoftheenergyservicessupplied.

2.2 PowerSystem

ArepresentationofThailand’spowersystemisillustratedinFigure2.Thediagram

highlights thepresent statehoodof the country's national system in termsof the

maingenerationresourcesand230/500kVtransmission linesthatareusedinthe

powersystemandtheirlocationswithinthecountry.Wehavealsohighlightedthe

maindemandcentreswithinthecountry.

Thailand’s electricity system is of medium size. As of December 2014, the total

installed capacitywas 34,681MW including generation from EGAT power plants,

IPPs,SPPsandpowerimportsfromneighbouringLaoPDRandMalaysia.EGATand

IPPsarethemajorgenerationsuppliersaccountingforaround45%and40%ofthe

total electricity demand respectively. The major primary resource used for

electricityproductioninThailandarenaturalgas,whichsharesabouttwothirdsof

the fuel mix. Thailand imports electricity from Lao PDR via 230 kV and 500 kV

transmissionlinesofcapacityupto1,800MWthroughtheNortheastregionofthe

country. Thailand exchanges power in the south with Malaysia via a HVDC

transmissionsystemwithcapacityof300MW.

ElectricityGeneratingAuthorityofThailand(EGAT)ownsandoperatesthefully

integratednationaltransmissionnetworkwhichincludestransmissionlinesand

substationsofvarioushighvoltage levels throughoutthecountry.Thehighest,

500kVtransmissionlinescarrybulkelectricityfromgenerationsourceslocated

in the North, East and West to the major demand centres in the Bangkok

metropolitanandcentralareas.The230kVlinesaredistributedthroughoutthe

country. Northern region and Central region are the source while Bangkok

metropolitanandthevicinityarethemajor loadrelyingonpower importfrom

otherregions.

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Figure2 ThailandPowerGenerationSystem(2013)

Source:EGATPowerSystemDispatchingunderRapidlyChangingElectricityDemand,2013

MajorLoad

Centres

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2.3 InstalledCapacity

Figure 3 shows the installed capacity and peak demand on a national level by

ownership; the reservemargin (basedonnameplate capacity) is also shown. This

illustratesthatthesystemreservemarginintherecentpasthasbeenwithina20-

25%range. It shouldbeacknowledged thatdue to thepredominanceofgas fired

generatingcapacity,supplyanddemandbalanceinthepowersystemiscriticalon

naturalgassupply.

Figure 4 illustrates the capacitymix inMWandpercentage. By endof 2014, the

system’s combined grid-connected installed capacity is 34,870MW comprising of

23,919 MW gas-fired capacity, 4,776 MW coal-fired capacity, 3,444 MW

hydropowercapacity,317MWnon-hydroREcapacityand2,405MWimportpower.

This in showing that natural gas is the main power production technology

accounting for 68.69% of the total grid-connected capacity, followed by coal at

13.7%.

Figure3 InstalledCapacityandSystem-wideReserveMargin(2000-14)

Source:EPPOStatistics(2015)

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Figure4 ThailandCapacityMixbyTypeofGeneration(2014)4

Source:CompiledbyConsultant

2.4 ElectricityDemand

Figure 5 shows Thailand’s final electricity consumption by the enduse categories

from2002to2014.Overthisperiod,electricityconsumptionincreasedfrom100.1

TWh to 168.2 TWh, with a CAGR of 4.44%. The industrial sector makes up the

largestportion, consuming some73.8TWh,or43.8%of the total consumption in

2014.Thisisfollowedbytheresidentialsector(23.1%),commercialsector(18.6%)

andsmallgeneralservices(11.2%).Thechangesinelectricitydemandcomposition

shown in Figure 6 indicate that the industry share in the total consumption has

been slightly decreasing as opposed to gradual increases in percentage for

consumptionbytheothersectors.

4ThelegendshowstheinstalledMWofeachtechnologyandthepercentageoftheinstalledcapacityforthat

technology.

Oil/Diesel

9,0.03%

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Figure5 ElectricityDemandbyCategory(2002-14)


Figure6 ElectricityDemandSharesbyCategoryforSelectedYears


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2.5 GenerationSupply

Figure 7 shows generation by fuel type over the last 15 years, illustrating how

natural gas increasingly dominates the Thailand fuel mix. In 2014, the total

productionof electricitywas180,945GWh, 120,315GWhor 66.5%ofwhichwas

generated fromnatural gas. Thenextmajor typeof fuel is coal, 120,314GWhor

20.8% of the 2014 generation mix. The contribution of imports and other fuel

sourceshasbecomemoresignificant,increasingfrom3,461GWh(3.5%)in2010to

16,252GWh (9.0%) in 2014. Generation proportions of all fuel types in 2014 are

showninFigure8.

Figure7 GenerationbyFuelType(2000-2014)

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Figure8 GenerationMixProportionbyFuelType(2014)


2.6 ImportsandExports

Thailand hasMOUswith four neighbouring countries (China,Myanmar, Laos and

Cambodia) for importing electricity. Thailand is also exchanging power with

Malaysia.Figure9showsthegeneralstatusofpowerimportsintothecountry.

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Figure9 PowerPurchasefromNeighbouringCountries

Source:ERC/EGAT

IntheGMSThailand’stransmissionsystemhasinterconnectionswithLaosPeople’s

DemocraticRepublic(LaosPDR)via230kVand500kVtransmissionlinesofcapacity

upto1,800MWthroughtheNortheastregionofthecountry.

In the south Thailand exchanges power with Malaysia via a HVDC transmission

systemwithcapacityof300MW.TheMOUswithChina,MyanmarandCambodia

havenotbeenimplementedyetbutthenewPowerDevelopmentPlan(PDP2015)

indicates that electricity will be imported from Lao PDR and China’s Yunnan

province5.

Figure 10 illustrates the trendof annual electricity imports from2000 to 2014. It

shows that the volumes of imported power have increased significantly over the

lastfiveyears,from2,460GWhin2009toover12,000GWhin2013/14.

Table1providesthelistofallexisting,confirmed(withsignedPPA)andlongerterm

prospectiveprojects forelectricity imports inThailand. Note that the table limits

thecapacityoftheHongSaprojectjusttowhatisavailableforexporttoThailand.

Themine-mouthHongSacoalproject,poweredonreservesoflignitecoal,hadits

first unit come online in 2015with an additional two units expected to follow in

2016.Notethat80%(1,473MW)ofthetotalinstalledcapacityof1,878MWfrom

projectisunderaPPAwithEGATforimportstoThailand.

5http://www.chiangraitimes.com/thailands-new-power-development-plan-death-sentence-for-mekong.html

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It was announced in August 2015 by proponent Impact Energy Asia Co that a

windfarmtobedevelopedinsouthernLaoPDRwithanintentiontoexportpower

to neighbouring countries The planned a 600 MW wind project is designed to

leverage monsoonal wind patterns. Under an agreement signed by the Lao

governmentandtheThairenewablesfirm,thewindfarmwouldbelocatednearthe

Mekong River across from Ubon Ratchathani, and is expected to commence

operation for 2019. Around 95% of the power output from the windfarm is

expected to be sold to countries bordering the Mekong, with Thailand likely to

offtakesome90%ofitsoutput.

Figure10 ThailandElectricityImports(2000-2014)


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Table1 ElectricityImportProjectsforThailand

No ProjectNameCapacity,

MWFuelType

Countryof

ExportCOD

6

INOPERATION

1 NamTheun-Hinboun

Hydropower

434 Hydro LaoPDR 1998,

2012

2 HuoiHoaHydropower 126 Hydro LaoPDR 1999

3 NamTheun2 948 Hydro LaoPDR 2010

4 NamNgum2 597 Hydro LaoPDR 2011

5 HongsaThermal#1 491 Coal LaoPDR 2015

6 KhlongNgae-Gurun

Interconnection

300 EGAT-TNBHVDC

Interconnection

Malaysia 2005

PPASIGNED

7 Su-ngaiKolok-Rantau-Panjang 100 EGAT-TNB132kV

Interconnection

Malaysia 2015

8 ImpactEnergyWindFarm7 540 Wind LaoPDR 2019

9 HongsaThermal#2,3 2x491 Coal LaoPDR 2016

10 Xe-pianXe-Namnoi 354 Hydro LaoPDR 2019

11 NamNgeip1 269 Hydro LaoPDR 2019

12 Xayaburi 1,220 Hydro LaoPDR 2019

LONGERTERMPROSPECTS*

13 Dawei 1,800 Hydro Myanmar 2018

14 JingHong(Yunnan) 3,000 Hydro China 2019

15 XeKong4-5 570 Hydro LaoPDR 2021

16 Coalfired 800 Coal Malaysia 2021

17 NamKong1 75 Hydro LaoPDR 2022

18 Semakan 660 Hydro LaoPDR -

19 DonSahong 240 Hydro LaoPDR 2023

20 PakBeng 912 Hydro LaoPDR -

21 Hutgi 1,190 Hydro Myanmar 2023

22 MaiKhot 390 Coal Myanmar -

23 MongTon 6,300 Hydro Myanmar 2026

6NotethatCODsof2016andbeyondaretheearliestexpectedyearsofexpectedcommercialoperation.

7Basedonthefollowingreference,thePPAforthisprojecthasbeensigned:

http://renewables.seenews.com/news/thai-company-to-build-600-mw-wind-farm-in-laos-report-487806.

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3 DevelopmentOptionsforThailand’sElectricitySector

3.1 Overview

ComparedtootherGMScountries,thedevelopmentoftraditionalprimaryenergy

resources in Thailand for electricity generation face a number of challenges.

Thailand’s proven offshore gas reserves in the Gulf of Thailand and Thailand-

MalaysiaJointDevelopmentArea(JTA)arebeingutilisedwithcontractedgasfrom

these reservesexpected tobedepletedby2030. Liquefiednaturalgas (LNG)has

been available since 2011 as a stop-gapmeasurewith terminal sized at an initial

capacity of 5MTPA8and an option to double capacity to 10MTPA. Reserves of

domestic coal consist mainly of lignite to sub-bituminous grade concentrated

aroundtwomainreserves:MaeMohinthenorthandKrabiinthesouth,withthe

formerbeingexploited,andthelatterbeingconsideredforexploitation.

TherehasbeenafocusondevelopinganoptionforNuclearPowerwitheffortsover

the lastdecadetakenbyThailandtoenhanceknowledgeandcapability toenable

nuclear power to be a long-term option should it be needed to address power

supplyshortages.NuclearPowerhas,however,facedpublicoppositionparticularly

inthewakeoftheFukushimacrisis. Nevertheless,nuclearpowerhasappearedin

allrecentpowerdevelopmentplansalthoughingeneralthecommercialoperating

date for the first nuclear power plant has occurred later in time in each power

developmentplan,withPDP2015havingthefirstplantscheduledfor2035.

In contrast to the fossil fuel situation, Thailand has substantial potential for the

development of hydro and other sources of renewable energy; most notably,

biomass, solar, and wind. Large scale hydro power potential in Thailand is

estimated to be around 15 GW. However, the environmental externalities

associatedwith exploiting hydro beyond the current 3.5GWof large scale hydro

alreadydevelopedisregardedtobeunsustainableandthereisstrongresistanceto

further developments. The government has therefore focused on and promoted

smallhydropowerprojects.TheAEDP2012proposedatargetof1,608MWofsmall

hydro by 2021, although, thiswas revised in theAEDP2015 to 376MWby 2036.

There has in the past been the development of pumped storage hydro,with the

1000MW Lam Ta Khong hydro project having pumped storage capability of 500

MW added in 2001 and Srinagarind having some 360 MW of pumped storage

capabilityofitsratedcapacityof720MW.

Thailand has an annual average wind speed of 4-5 meters per-second at an

elevation of 90 meters above sea level. Higher wind speeds of 6-7 meters per

secondcanbefoundinmountainrangesinthesouthandthenortheastduringthe

periodofthemonsoons.Thereispotentialforthedeploymentofwindturbinesfor

powergenerationthroughoutthecountry,particularlyalongtheseashoresandon

8MillionTonsperAnnum

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islandseitherintheGulfofThailandorAndamanSea.Underthe2015Alternative

Energy Development Plan (AEDP2015), Thailand targets some 3,002MWofwind

farminstalledcapacityby2036.

Beinglocatedneartotheequatorarea,Thailandhassubstantialpotentialforsolar

photovoltaicdevelopment.AreasinThailandthathavebeenidentifiedtohavethe

greatestpotentialincludethesouthernandnorthernpartsoftheNortheastregion

oftheUdonThaniprovinceandsubstantialpotentialhasbeenidentifiedacrossthe

Centralregion.Intherecentpastanumberofinitiallargescalesolardevelopments

havebeenput inoperationandexpectationsarethatthistrendwillcontinueinto

thenear-term.TheAEDP2015hassetatargetfor6000MWofsolarphotovoltaics

by2036.

Thailand,havinganumberoflargeareaswithDirectNormalIrradiation(DNI)inthe

range of 1600 to as high as 1950 kWh/m^2/year, located mostly in the north

western part of the country shows some promise for Concentrated Solar Power

(CSP). In general, the literature suggests that the minimum level for CSP to be

feasibleisaround1700to1800kWh/m^2/yearbutpreferablyhigher;inthisstudy

wehaveassumedthatthetechnologicalchallengesofareaswithDNIlevelsthatare

notsignificantlybeyondthisrangeforatechnologythat iscurrently in its infancy,

willbeovercomewithina10to15yeartimeframe.

As an agricultural country, Thailand’s potential for biomass in the form of

agricultural residues is significant. With the abundance of industrial waste and

livestock manure, Thailand also has significant biogas potential. The AEDP2015

suggests installed capacity targets for 2036 of 5,600 MW of biomass with

agricultural residues as the primary feedstock, 600MWof biogas resources, and

500MWofmunicipalwaste.Basedonvariousstudies,thepotentialforgeothermal

and ocean energy appears to be limited for Thailand. The AEDP2015 has set

modesttargetsforthesetechnologiesastheyareunlikelytobedeployedonalarge

scale.

3.2 NaturalGas

Thailand is estimated to have some 285 Bcm (10.1 Tcf) of proved reserves, or

around 6.8% of the total proved natural gas reserves of the GMS. Table 2 and

Figure11summariseprovednaturalgasreservesfortheGMScountries.Thefigure

alsoshowsthereservestoproductionratio(RPR).ThailandhasalowRPRnumber,

meaningthatthemajorityoffieldswithprovenreserveshavealreadybeenputinto

production.

Table2 ProvedNaturalGasReservesinGMSCountries

ProvedReserves RPR

Bcm Tcf Years

Myanmar 283.2 10.0 22

Thailand 284.9 10.1 7

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VietNam 617.1 21.8 63

Source:BPStatistics2014

Figure11 ProvedGasReservesofGMSCountries

Source:BPStatistics2014

3.2.1 NaturalGasProductionandImports

Upstreamoil and gas activities aredominatedbyPTT Exploration andProduction

(PTTEP),asubsidiaryofPTTPublicCompanyLimited(PTT).ThePTTGroup,whose

business areas range from supply procurement, transportation, distribution, gas

processing, investment in natural gas vehicle (NGV) service stations, and

investmentsinrelatedbusinessesthroughtheGroup’ssubsidiaries.Eighty-fiveper

centofThailand’spetroleumreservesare locatedintheGulfofThailand,which is

characterisedbyclustersof smallwells in shallowwaterandover300platforms9.

AnillustrationofThailand’sgasinfrastructureisprovidedinFigure12.

9Austrade,2015:http://www.austrade.gov.au/Export/Export-Markets/Countries/Thailand/Industries/Oil-and-

gas#.VWaIrfmqpBd

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Figure12 Thailand’sGasFieldsandInfrastructure(2014)

Source:T.Parkinson,“NaturalGasandLNGMarketinThailand”,2014

Figure13showsthetrendingasproductionandimportsinThailand.In2014,the

total natural gas production in Thailandwas 42.1 billion cubicmetres,whichwas

nearlytwiceasmuchthe2003productionvolumeof21.5Bcm.Despiteincreasesin

production,ThailandisrelyingongasimportsfromMyanmartomeetthedomestic

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demand. In 2014, it imported 10.6 Bcm of natural gas in LNG purchases and via

pipelines from Yadana, Yetakun and Zawtika gas fields in Myanmar. Current

imported volumes account for around 20% of the total natural gas supply. It is

evident that future gas demand growth will have to be met by increased gas

imports,andparticularlyLNG,asdomesticsuppliesprogressivelydeplete10.

Figure13 GasProductioninThailand(2003-2014)

Source:BPStatistics(2014)andEPPOStatistics(2015)

3.2.2 LiquefiedNaturalGasinThailand

ThailandhasMapTaPhutLNGfacilityintheeasternprovinceofRayongbutithas

beenoperatingonlyatapartialoutputasdomesticdemandisbeingmetprimarily

byimportedsupplies.AccordingtoPTT,itsimportsofLNGreachedaround2million

tonnes over the last year and it is planning tomore than double this volume for

2015,partly tohelp replacepotentialdeclines inpipeline imports fromMyanmar.

CurrentLNGsuppliersforThailandincludeQatarLiquefiedGasCompanyLimited;it

isalsoreportedtobeintalkswithothersuppliersfromMozambique,UnitedStates,

AustraliaandRussiatosecureadditionallongtermsupplycontracts.

Theexisting import terminalhasa capacityof5million tonnesa year, andPTT is

constructingasecondLNGterminalatthesamelocationandofthesamecapacity,

withcompletionexpectedin2017.InpreparationforfallingimportsfromMyanmar

anddecliningdomesticoutputfromtheGulfofThailand,PTT isalsoconsideringa

10Enerdata,2014:http://www.enerdata.net/enerdatauk/press-and-publication/energy-news-001/thailand-natural-

gas-conundrum_29249.html

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plantobuildanLNGreceivingterminaladjacenttoagaspipelinelinkedtogasfields

inMyanmar. PTT’s argumenthasbeen that such a site on the coast ofMyanmar

wouldofferamoreconvenientdeliverypointforLNGfromMiddleEastsuppliers.

3.2.3 NaturalGasUseinElectricityGeneration

Figure14showsthegasconsumptiontrendingeneralandintheelectricitysector

fortheperiod2003to2014aspublishedbyEPPO.Thetotalconsumptionin2014

was some 48.4 Bcm, of which 28.5 Bcm was used for electricity generation.

Althoughgasconsumptionbythepowersectorhas increasedonethird involume

overthegivenperiod,itsshareinthetotalconsumptiondeclined,from77%in2003

to59%in2014.Thisindicatesthatuseofnaturalgasbytheothersectorsincluding

industry,GSPandNGVhasbeengrowingatfasterrates.

Figure14 GasConsumptioninThailand(2003-2014)


3.3 CoalResources

3.3.1 CoalReservesandSupplyAccording to BP Statistics, Thailand proven coal reserves at end of 2013 were

estimatedat1,239milliontons,consistingof ligniteandsub-bituminousgradesof

coal. The country’smajor coal sites include theMaeMoh basin operated by the

Electricity Generating Authority of Thailand (EGAT), the Krabi basin, the Saba Yoi

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andSinPunbasinsinthesouthernarea,andtheWiangHaeng,NgaoandMaeThan

basinsinthenorth.

Figure15showsthelocationofsomelargestrategiccoalminesanddeposits.These

includeMaeMoh(thelargestbasin),MaeThanandLiinthenorth,andKrabiinthe

south.Table3providesdataonThailandcoalreservesasof2010accordingtothe

MinistryofEnergy’sstatistics.Figure16showstheannualvolumesofcoalsupplyin

Thailand for the period 2013-14. This indicates that the production of domestic

lignitewasstableataround18milliontonsperyear,whereasthecoalimportshave

substantially increased, from 7 million tons in 2003 to 20.9 million in 2014,

surpassingthedomesticsupply.AccordingtoEPPOstatistics,mostofthedomestic

lignitesupply(17.1outof18milliontonsin2014)isproducedbyEGATownedand

operatedMaeMohMine,whichthen is fullyconsumedbyEGATcoal firedpower

plants.

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Figure15 LocationofThailandStrategicCoalDeposits

Source:EPPOandEGAT

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Table3 ThailandCoalReserves(2010)

BasinLocation Reserve

CoalRank Age Concessionaire

District ProvinceProduced

Remaining

NorthernRegion

NaHong MaeChaem ChiangMai 2.5 -Lignitetosub-bituminous Tertiary Nonactive

BoLuang Hod ChiangMai 1.8 -Lignitetosub-bituminous Tertiary Nonactive

MaeTeep Ngao Lampang 2.2 - Lignitetobituminous Tertiary ActiveMaeThan SopPrap Lampang 35.5 0.5LignitetoBituminous Tertiary Active

MaeMoh MaeMoh Lampang 338.0 1,050Lignitetosub-bituminous Tertiary EGAT,Active

Li Li Lamphun 39.7 - LignitetoBituminous Tertiary ActiveChiangMuan ChiangMuan Phayao 4.5 - LignitetoBituminous Tertiary SuspendedMaeTun MaeRamat Tak 0.4 0.8 LignitetoBituminous Tertiary NonactiveMaeLamao MaeSod Tak 1.2 - Lignitetobituminous Tertiary NonactiveCentralRegion

NongYaPlongNongYaPlong Phetchaburi 1.2 0.5 Lignitetobituminous Tertiary Nonactive

SouthernRegion

Krabi Muang Krabi 8.7 111.3Lignitetosub-bituminous Tertiary

EGAT,suspended

Kantang Kantang Trang 0.01 - Lignite Tertiary NonactiveNortheasternRegion

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NaDuang NaDuang Loei 0.2 - Anthracite Pre-tertiary Nonactive

NaKlang NaKlangNongBualumphu 0.07 - Anthracite Pre-

tertiary NonactiveTotals 436 1,164

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Figure16 CoalSupplyinThailand(2003-2014)


3.3.2 ExistingCoalConsumption

Figure 17 shows the yearly consumption of coal in Thailand and for powergenerationinparticular,fortheperiod2013-2014.Thisindicatesthataroundtwothirdsofthetotalconsumptionisattributedtoelectricitygeneration.

Figure17 CoalConsumptioninThailand(2003-2014)


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3.4 NuclearPower

NuclearpowerwasincludedintheThailand’sPowerDevelopmentPlan2007-2021(PDP2007). This planned to have 2,000MWof nuclear capacity in operation by2020 and another 2,000 MW the following year. The PDP has been revised anumberoftimesduetothechangeintheelectricitydemand,allrevisedPDPshaveconsiderednuclearpower11.

Thailandhadcarriedouttheself-evaluationonIntergradedNuclearInfrastructureReview (INIR) and submitted a report to the International Atomic Energy Agency(IAEA) in October 2010. IAEA experts conducted a mission to Thailand duringDecember2010toconcludethat“Thailandcanmakeaknowledgeabledecisionontheintroductionofnuclearpower”.

AccordingtothePDP2010–Revision3, thefirstNPPprojectwaspostponedfor6yearsuntil2026topromotegreaterpublicunderstandingofNPPandfillmajorgapsidentifiedbyIntergradedNuclearInfrastructureReview(INIR)mission.Apre-projectphaseisnowunderwaywiththefollowingongoingactivities:

• Preparationoflawsandregulationsfornuclearpower;• Technicalandsafetyreviews;• Site selection reviews (to meet Emergency Preparedness and Response

requirements);• Publiccommunication,educationandparticipation;and• Humanresourcedevelopment.

Nevertheless, the latestPDP2015hasnuclearpowergeneratorsoccurringat laterperiodsoftime,withthefirstunitin2035andthesecondin2036.

3.5 HydroPower

ThepotentialofhydropowerinThailandisestimatedat15,155MW12.Hydropowerhas been developed for power generation since 1964 with the construction ofseveral largehydropowerprojects throughout thecountry.AsofDecember2014,hydro installed capacity was 3,444 MW, accounting for 10% the total systemcapacity.Itisnotedthattheannualvolumeofelectricitygenerationfromhydrohasnot changedmuch since decades ago. In 2014, the hydropower generated 5,163GWh, accounting for fewer than 3% of the total generation of 180,945 GWh,comparedtoaround20%backin198613.Hydropowerresourcesaredifficult toexploitduetotheenvironmental impactonthe resource areas a power project would entail. Future development ofhydropower resources in Thailand is limited to a small number of small-scaleprojectswhichareconsideredtobeeconomical.11IAEA,2013:https://www.iaea.org/NuclearPower/Downloadable/Meetings/2014/2014-03-17-03-21-WS-INIG/DAY3/COUNTRY/Thailand_v1.pdf12GreenlineEnergy:http://www.greenlineenergy.com.au/index-4.html13EPPO2015Statistics:http://www.eppo.go.th/info/5electricity_stat.htm

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Thegovernmenthasbeensponsoringdevelopmentprojectsofsmallhydropowerplants for a new planned capacity of 350 MW. The Department of AlternativeEnergyDevelopmentandEfficiency (DEDE)and theProvincialElectricityAuthority(PEA)arethemain institutions involvedwithmini-andmicro-hydropowerplants.DEDE has also installed many village-level hydropower plants, and there isconsiderable potential for village-scale small hydro in east and central Thailand.According to the 2012 Alternative and Renewable Energy Development Plan(AEDP2012),Thailandplannedtoincreasesmallhydropowercapacityfrom102MWin2012to1,608MWby202114.Nevertheless,thelatestAEDP2015hasreducedthistargetto376MWfor2036.

3.6 WindPower

Thailand has an annual average wind speed of 4-5 meters per second at anelevation of 90 meters above sea level. Higher wind speeds of 6-7 meters persecondcanbefoundinmountainrangesinthesouthandthenortheastduringtheperiodofthemonsoons.Thereispotentialforutilisationofwindturbinesforpowergenerationthroughoutthecountry,particularlyalongtheseashoresandonislandseither intheGulfofThailandorAndamanSea.Low-speedwindturbinescanstartrotating at wind speeds of 2.5 meters per second and generate a full load ofelectricityat9metersper-second.Windspeed inThailand ismainly influencedbythe northeastmonsoon, the southwestmonsoon and local topography. The totalonshorewindpotentialinThailandisestimatedatupto30,000MWand7,000MWforoffshorewindaroundtheGulfofThailand15.

Figure 18 shows average monthly wind speed measurements for Thailand asreportedbyNASAAtmosphereScienceDataCentreforthelocationsthathavethehighest averagewind speeds throughout the year. This shows that a number oflocationsinThailandrecordshighwindspeedsduringtheperiodsofJunetoAugustandNovember toDecember. When these locations are shadedover themapofThailand,as illustrated inFigure19,wecanseethat inthemainthe locationsarealong the country’s southern and central regions which are close to themetropolitan load centre. There are also some locations with significant windpotentialfurthertothenorth.

KeyactivitiesregardingwindpowerpotentialsurveyinThailandoverthepastyearsincludetheconductofamap in2001thatdemonstratedwindpowerpotential inThailand, based on DEDE’s wind speed statistics at the 10-meter height windmeasurementpostsandfromotherdatasources.Thesurveyfoundthatpotentialwind power sources located in the Gulf of Thailand-from Nakornsritammarat,Songkla, to Pattany, aswell as someareas in Petchburi andDoi Intanon,with anaveragewindspeedof6.4meterspersecondat50-meterheight.14ThailandAlternativeEnergyIndustry:http://www.slideshare.net/boinyc/thailands-alternative-energy-industry15WindEnergyResourceAtlasofSoutheastAsia(TrueWindSolutions,2001),RenewableEnergyDevelopmentsintheGreaterMekongSubregion(ADB,2015),OffshorewindpowerpotentialoftheGulfofThailand(Waewsak,Landry,Gagnon,2015)

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TheThaigovernmentsupportsinvestorswithspecialincentivesforinvestinginwindenergy. In addition, theDEDE has initiated theDemonstration Project on (Micro)Wind Power Generation at a Community Level, since 2007, by supporting theinstallation of micro wind turbine sets for one kilowatt power generation. Thetargetedareasare60communitiesnationwide.Thiseffort is intendedtopromoteproductionofwindturbinesandincreaseduseofwindenergyinthefuture.WindEnergy Holding Co., Ltd, a wind project developer, has already finished installingwindfarmprojectscalled“WestHuayBong3”and“WestHuayBong2”.Bothwindfarmprojects,locatedinNakhonRatchasima,havecapacityof103.5MWeachandstarted commercial operation since November 2012 and February 2013,respectively.Additionally, the companyhas a long-term investmentplan forwindfarmswithatotalinstalledcapacityof1,000MWby2017.

Underthe2015AlternativeEnergyDevelopmentPlan(AEDP2015),Thailandtargetssome3002MWofwindfarminstalledcapacityby2036.

Figure18 MonthlyWindSpeedsforSelectedLocationsinThailand

Source:NASAAtmosphereScienceDataCentre,obtainedviatheSWERAGeospatialToolkit

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Figure19 LocationsinThailandwithHighestWindPotential

Figure 20 shows the DTU GlobalWind Atlas16onshore and 30 km offshore windclimatedatasetwhichaccountsforhighresolutionterraineffectsfor100maboveground level. Accordingtothe IRENAglobalatlasdescription:“thiswasproducedusingmicroscalemodellingintheWindAtlasAnalysisandApplicationProgramandcapture small scale spatial variability of winds speeds due to high resolutionorography (terrain elevation), surface roughness and surface roughness changeeffects.ThelayerssharedthroughtheIRENAGlobalAtlasareservedat1kmspatial16See:http://globalwindatlas.com/.

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resolution.Thisisquiteconsistentwiththelowerresolutionassessmentofpotentialpresented inFigure19,and ithighlightsoffshorepotentialexists toboth theeastand west coastlines of the Thailand’s peninsular in the south. Another chart toshow the onshore dispersion ofwind potential charted in Figure 21. This shows3TIER’s GlobalWind Dataset17, which provides average annual wind speed at 80metersabovegroundlevel.

Figure20 AverageWindSpeed1kmat100mAGLDTU(2015)

Source:IRENAGlobalAtlasandGlobalWindAtlas(2015)

17Source:3TIERdatasetwasaccessedviatheIRENAGlobalAtlasServer:http://irena.masdar.ac.ae/.

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Figure21 3TIER’sGlobalWindDataset5kmonshorewindspeedat80mheight18

Source:3TIER’sGlobalWindDataset(accessedviaIRENAGlobalAtlas)

18Averageforperiodfrom1980to2011.

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3.7 SolarPower

Locatedinthetropics,Thailandhasexcellentpotentialforlargescaleintegrationofsolar resources. Thailand is estimated to have solar PV potential greater than50,000MW19.Theannualaverageof totaldaily solar radiation inThailand is5.06kWh/m2or18.2MJ/m2.MostofthecountryreceivesthemaximumsolarradiationduringApril/May,rangingfrom5.56to6.67kWh/m2perday.TheNorth-easternand central regions are among those locations that have greater solar powerpotential.Figure22plotsthemonthlyaveragedirectnormalirradiation(DNI)levelsfor selected sightswith the highest annual average irradiation levels in Thailand.ThisshowsthemonthlyvariationthroughouttheyearforsolarirradiationandthatNovemberthroughtoAprilhaveexcellentsolarconditions.ThechartalsoshowsmonthlyDNIlevelsforvarioussitesinThailand.Siteswiththehighest DNI levels average 5.3kWh/m^2/day (with a deviation of approximately1kWh/m^2/day)acrosstheyear.Ingeneral,DNImeasurementsinexcessofabout4.95 kWh/m^2/day aredeemedappropriate for thedeploymentof concentratingsolarpower(CSP).Figure23showsamapofThailandshadingthelocationswheresolarpotentialisatitshighest.Thishighlightsthatthegreatestpotentialforsolarliesinthecentralandeasternregionofthecountry.Figure24plotsmeasurementsof Global Horizontal Irradiance (GHI) based on the 3TIER high resolution datasetaccessed via the IRENA Global Atlas. This map shows that the GHI potential issignificantthroughouttheentirecountryaswell.AccordingtotheAEDP2015data,asofend2014,Thailandhad1,299MWofsolarpower production capacity installed. The plan has set a target for solar energycapacityof6,000MWby2036,withthetechnologyconsideredtobephotovoltaics.

Figure22 MonthlyDNIforSelectedLocationsinThailand

Source:NASAAtmosphereScienceDataCentre,obtainedviatheSWERAGeospatialToolkit

19SeeSection3.13.

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Figure23 MainLocationswithSolarPowerPotentialbasedonDNIinThailand

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Figure24 3TIER’sGlobalSolarDataset(3kminW/m^2)forGHI

Source:3TIER’sGlobalSolarDataset(accessedviaIRENAGlobalAtlas)

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3.7.1 ConcentratedSolarPower

Table4providesalistofcountries(includingThailand)thathaveCSPinstallations.ThistableshowstheinstalledcapacityofCSPandplannedcapacitiesasofabout2014,andthecorrespondingDNIforthecountry.ThedataisalsorepresentedvisuallyinFigure25,includingThailand.Thechartplotsthecountrieswithmorethan100MWofCSPinredtohighlightthosewhereitcanbearguedtohavebeensuccessfullydeployed.ItcanbeseenthatThailand’saverageDNIforthelocationsthatwehaveidentified(andshadedinFigure21)whileonthelowersideoftherangecomparedtocountriesthathavealreadydeployedCSPisstillwithintherangethatwouldallowCSPdeployment.ThissuggeststhatCSPinThailandwouldbeatechnologythatwouldfacesometechnicalbarriers,butcouldbefeasible.OthersurveysofDNIonagloballevelsuggestthatinlocationsinThailand,theDNImayvaryintherangeof1600-1800kWh/m^2/year(or4.4to4.9kWh/m^2/day).Inparticular,theDNIheatmapsareillustratedinFigure26andFigure27,whichshowthesamegraphbuthaszoomedintotheGMSregion.

Figure25 DNIofCountrieswithCSPInstallationsincludingThailand

0

1

2

3

4

5

6

7

8

DNI(kW

h/m^2/day)

<100CSP >=100MWofCSP Thailand

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Table4 ListofCountrieswithCSPProjectsorPlanningCSPProjectsandDNI20

Country StartYear

InstalledCapacity(MW)

UnderConstruction

(MW)

DNIValue(kWh/m^2/yr)

DNIValue(kWh/m^2/d)

Algeria 2011 25 - 2,700 7.4Australia 2011 12 44 2,600 7.1Chile 2015 - 360 2,900 7.9China 2012 2 50 2,050 5.6Egypt 2011 20 - 2,431 6.7Germany 2008 2 - 902 2.5India 2011 3 425 2,200 6.0Italy 2010 5 - 1,936 5.3Mexico 2013 - 14 2,178 6.0Morocco 2010 2 164 2,500 6.8SouthAfrica 2014 - 200 2,700 7.4Spain 2007 2,057 250 2,121 5.8Thailand 2012 5 - 1,935 5.3UAE 2013 100 - 1,934 5.3USA 1984 650 3,202 2,681 7.3

Figure26 WorldMapofDNI21

20R.Affandi,C.K.Gan,andM.R.A.Ghani,“ProspectiveofImplementingConcentratingSolarPower(CSP)inMalaysiaEnvironment”,WorldAppliedSciencesJournal32(8):pp.1690-1697,2014.21Thismapwassourcedfrom:http://meteonorm.com/images/uploads/demo_uploads/dni_v715_hr.png.

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Figure27 DNIintheGMS

Source:Meteonorm(2015)

3.8 GeothermalEnergy

Thereareapproximately64geothermalresourcesinThailand,butmajoronesareinthenorthof the country, especially the geyser field at FangDistrict in ChiangmaiProvince. Survey on the potential of geothermal energy development at FangDistrictcommencedin1978,withtechnicalassistanceandexpertsfromFrancelaterin1981.Currently,EGATisoperatinga300kWbinarycyclegeothermalpowerplantat Fang District, generating electricity at about 1.2 million kWh per year, whichhelpsreduceoilandcoalconsumptionforpowergeneration.Inaddition,otherbenefitscanbederivedfromthewasteheatofhotwaterusedinthepowerplant.Thetemperatureofhotwater,afterbeingusedinthepowerplant,willdecreasefrom130°Cto77°C,whichcanbeusedfordryingagriculturalproductsandfeedingthecoolingsystemforEGAT'ssite-officespace.Someothernon-energyusesofhotwaterfromgeothermalsourcesareforphysicaltherapyandtourism.Thailand’s AEDP2012 set a target of 1 MW of geothermal and 2 MW of tidalcapacitybuiltby2021.Nevertheless,thistargethasbeenremovedfromAEDP2015.

3.9 Biomass

Thailand is an agricultural country with a huge agricultural output, such as rice,sugarcane,rubbersheets,palmoilandcassava.Partoftheharvestisexportedeachyear, generating billions of baht revenues for the country. In processing theseagricultural products, a large amount of residues are generated which can beexploitedasa feedstock togenerateelectricity. Forexample,paddyhusks canbe

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burned to produce steam for turbine operation in rice mills; bagasse and palmresidues are used to produce steam and electricity for on-site manufacturingprocess; and rubber wood chips are burned to produce hot air for rubber woodseasoning. Moreover, the remaining biomass can be used for power generation,withthefollowingpotential12:• Paddyhusks,biomassfromricemills:eachtonofpaddyrequires30-60kWhof

energyforallstagesofprocessing,yieldingabout650-700kilogramsofriceandresidue, that is, about 220 kilograms of paddy husks which can be used togenerate90-125kWhofenergy.

• Bagasse,biomassfromsugarmills:eachtonofsugarcanerequires25-30kWhofenergyand0.4tonofsteamforallstagesofprocessing,yieldingabout100-121kilogramsof sugarand residue, that is, about290kilogramsofbagassewhichcanbeusedtogenerateabout100kWhofenergy.

• Palm outer-covering fibre, shells and empty bunches, biomass from palm oilextractingplants:eachtonofpalmrequires20-25kWhofenergyand0.73tonofsteamforallstagesofprocessing,yieldingabout140-200kilogramsofpalmoilandresidues, that is,about190kilogramsofpalmouter-covering fibreandshells and 230 kilograms of emptied palm bunches which can be used togenerate about 120 kWh of energy. In addition, therewill be about 20 cubicmeters of wastewater from the processing which can be used for biogasgeneration.

• Woodchips, biomass from sawmills: one cubicmeter of wood requires 34-45kWh of energy for all stages of processing, yielding about 0.5 cubicmeter ofprocessedwoodandresidue,thatis,about0.5cubicmeterofwoodchipswhichcanbeusedtogenerateabout80kWhofenergy.

As of end 2014, Thailand is estimated to have some 400MW of biomass powerproductioncapacity installed.TheAEDP2015hasput inplaceatarget forbiomasspowercapacityof5,570MWby2036.IES projected estimates based on the ADB study “Renewable EnergyDevelopmentsandPotentialintheGreaterMekongSubregion”suggestanenergypotentialofaround120,000GWh/yrorupto17,000MW.

3.10 BiogasandWaste

In Thailand, there has been development of the biogas technology using biogasgeneratedfromanimalmanure,especially thatofpigsandcows,as fuel inpowergeneration and in cooking. Development has also been undertaken on powergeneration from landfill biogas. The major financial resource is the EnergyConservation Promotion Fund (ENCON Fund) of the government. Several biogasprojectshavebeensupportedbytheENCONFund,suchasthebiogasfromanimalmanureforpowergenerationinlivestockfarms,researchanddevelopmentonthefeasibility of biogas generation from wastewater treatment systems in factories,andthedevelopmentofabiogasmapprovidinginformationonpigfarmsanddairy

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farms nationwide in order to facilitate the planning of biogas utilization in thefuture.

Biogas power has high potential in Thailand due to the abundant availability ofindustrial waste and livestock manure. According to AEDP2015, the installedcapacityofThaibiogassourceswas312MWatendof2014andhassetatargetof600 MW by 2036. This could be supplemented by some 500 MW of installedcapacity that would be based on power generation from municipal waste. IESprojected estimates based on the ADB study suggest an energy potential ofaround10,500GWh/yrorupto1,500MW.

3.11 OceanEnergy

Earlier studies on Thailand’s ocean energy potential concluded no exploitablepotential,however, furtherstudiesandresearch is inprogressontheeasternandupper side of the Gulf of Thailand. A paper on ocean energy in Southeast Asiareported up to 0.001 ktoe and 0.5 ktoe of tidal and wave energy available inThailand22. As such, our modelling has not factored in any ocean/marine energypotentialinThailand.

3.12 AlternativeEnergyDevelopmentPlan2015

The Alternative Energy Development Plan 2012-2021 has been revised andincorporated as part of the new Power Development Plan (PDP 2015). The newAEDPtargetsaninstalledcapacityofalternativeenergyat19,635MWin2036from7,279MWin2014.ThetargetforeachtypeofrenewableenergyisshowninTable5.

Table5 RenewableEnergyTargetsby203623

Type Waste Biomass Biogas Hydro Wind Solar Energycrops

Total(MW)

2014Capacity 48 2,199 226 3,016 220 1,570 - 7,279

2036Targets 501 5,570 600 3,283 3,022 6,000 680 19,635

ThisAEDP2015wasupdatedaccordingtothefollowingprinciples:

• Focusonpowergenerationfromwaste,biomassandbiogasaspriority.• Allocationofrenewableenergygenerationcapacityaccordingtothedemand

andpotentialinregions/provinces.

22OceanrenewableenergyinSoutheastAsia:Areview(Quirapas,Lin,Abundo,Brahim,Santos,2014)23http://www.thai-german-cooperation.info/download/20150520_pdp_re_%20policy%20factsheet.pdf

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• Solar and wind power to be promoted at a later stage “once the cost iscompetitivewiththepowergenerationfromLiquefiedNaturalGas(LNG)”.

• CompetitivebiddingwillbeemployedasaselectionprocessforFITapplicationinsteadoffirst-comefirst-serve.

• Communityenergyproductionwillbeencouragedtoreducefossilfuelusage;and

• REconsumptionwill increasefrom8%to20%offinalenergyconsumption in2036.

3.13 RenewableEnergyPotentialandDiversification

In summary, the renewableenergypotentials that areestimated for Thailandareprovided inTable6.Thenumberspresentedherehavebeendrawnfrommultiplesources and informed by analysis of IRENAGlobal Atlas data. Figure 28plots theseasonalvariationofrenewableenergygenerationprofilesinThailandforsolarandwind.Thisshowsthatthereisverygoodseasonaldiversificationacrossthesetwoformsofrenewableenergy.TheannualmaximumsolarirradiationisinJanuaryandtheminimum in July to August. Wind fluctuations are not as predictable but asillustrated, generation fromwind reaches itsmaximumbetween JuneandAugustandcomplementssolarresourcesverywell.

Figure28 SeasonalRenewableEnergyGenerationProfiles

Table6 SummaryofEstimatedRenewableEnergyPotential(CompiledfromVariousSourcesandAnalysis)

Resource Potential(MW)

Sourceandcomments

ThailandWetSeason(basedonmonthswithhighest

rainfall)

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Resource Potential(MW)

Sourceandcomments

Hydro(Large)

15,155 K.AroonatandS.Wongwises,“CurrentstatusandpotentialofhydroenergyinThailand:aReview”,RenewableandSustainableEnergyReviews,Vol.36,June2016,pp.70-78.GreenlineEnergy:http://www.greenlineenergy.com.au/index-4.html

Hydro(Small)

- Lackofdata

PumpStorage

10,807 TheSmallHydropowerProjectastheImportantRenewableEnergyResourceinThailand(Chamamahattana,Kongtahworn,Pan-aram,2005)

Solar Morethan50,000

Seeresourcemapsanddetailedanalysisofsolardensitydata,Figure24.

WindOnshore

Upto30,000

Potentialresourceabove6m/s.WindEnergyResourceAtlasofSoutheastAsia(TrueWindSolutions,2001),RenewableEnergyDevelopmentsintheGreaterMekongSubregion(ADB,2015).ItisunderstoodthattherearedifficultiesinThailandintermsofmountainousandremoteareasforthelocationsthathavehighwindpotential,buthaveassumedthatthesearenotinsurmountableintheSESandASES.

WindOffshore

7,000 OffshorewindpowerpotentialoftheGulfofThailand(Waewsak,Landry,Gagnon,2015)

Biomass 17,032 IESprojectionsbasedondatafromRenewableEnergyDevelopmentsandPotentialintheGreaterMekongSubregion(ADB,2015)

Biogas 1,507 IESprojectionsbasedondatafromRenewableEnergyDevelopmentsandPotentialintheGreaterMekongSubregion(ADB,2015)

Geothermal - Notsignificantenough,withGeothermaltargetsremovedfromAEDP2015

Ocean - Lackofstudiesavailable

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4 ThailandDevelopmentScenariosIn this section,wedefine the three scenarios for Thailand’selectricity sector thatwe havemodelled: the Business as Usual (BAU), Sustainable Energy Sector (SES),and Advanced SES (ASES) scenarios. We also set out the assumptionsmade fortechnology costs (section 4.2) and fuel prices (section 4.3). Before providing thedetails foranumberofThailand-specificassumptions– inparticular;ourassumedeconomic outlook, generation projects that we consider as committed 24 andcommentson the statusofpower importprojects. Further assumptions that arespecifictoeachscenariosareprovidedinsections5,6and7.

4.1 Scenarios

Thethreedevelopmentscenarios(BAU,SESandASES)forThailandareconceptuallyillustratedininFigure29.

Figure29 GMSPowerSectorScenarios

TheBAU scenario is characterisedbyelectricity industrydevelopments consistentwiththecurrentstateofplanningwithintheGMScountriesandreflectiveofgrowthrates in electricity demand consistent with an IES view of base development,existing renewable energy targets, where relevant, aspirational targets forelectrificationrates,andenergyefficiencygainsthatarelargelyconsistentwiththepoliciesseenintheregion.

24Thatis,constructionisalreadyinprogress,theprojectisneartocommissioningoritisinanirreversible/advancedstateoftheplanningprocess.

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Incontrast,theSESseekstotransitionelectricitydemandtowardsthebestpracticebenchmarksofotherdevelopedcountries in termsofenergyefficiency,maximisetherenewableenergydevelopment,ceasethedevelopmentoffossilfuelresources,and make sustainable and prudent use of undeveloped conventional hydroresources.Whererelevant,itleveragesadvancesinoff-gridtechnologiestoprovideaccesstoelectricity toremotecommunities. TheSEStakesadvantageofexisting,technicallyprovenandcommerciallyviablerenewableenergytechnologies.

Finally theASES assumes that thepower sector is able tomore rapidly transitiontowards a 100% renewable energy technology mix under an assumption thatrenewableenergyisdeployedmorethanintheSESscenariowithrenewableenergytechnology costs decliningmore rapidly compared to BAU and SES scenarios. AbriefsummaryofthemaindifferencesbetweenthethreescenariosaresummarisedinTable7.

Table7 BriefSummaryofDifferencesbetweenBAU,SESandASES

Scenario Demand SupplyBAU Demandisforecasttogrowin

linewithhistoricalelectricityconsumptiontrendsandprojectedGDPgrowthratesinawaysimilartowhatisoftendoneingovernmentplans.Electricvehicleuptakewasassumedtoreach25%acrossallcarsandmotorcyclesby2050.

Generatornewentryfollowsthatofpowerdevelopmentplansforthecountryincludinglimitedlevelsofrenewableenergybutnotamaximaldeploymentofrenewableentry.

SES • AssumesatransitiontowardsenergyefficiencybenchmarkfortheindustrialsectorofHongKong25andofSingaporeforthecommercialsectorbyyear2050.

• Fortheresidentialsector,itwasassumedthaturbanresidentialdemandperelectrifiedcapitagrowstoalmost1,000kWhpaby2050,45%lessthanintheBAU.

• Assumesnofurthercoalandgasnewentrybeyondwhatisalreadyunderstoodtobecommitted.

• Amodestamountoflargescalehydro(between4,000to5,000MW)isdeployedinLaoandMyanmaraboveandbeyondwhatisunderstoodtobecommittedhydrodevelopmentsinthesecountries27.

• Supplywasdevelopedbasedonaleastcostcombinationofrenewablegenerationsources

25BasedonouranalysisofcomparatorsinAsia,HongKonghadthelowestenergytoGDPintensityforindustrialsectorwhileSingaporehadthelowestforthecommercialsector.27ThisisimportanttoallcountriesbecausetheGMSismodelledasaninterconnectedregion.

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Scenario Demand Supply• Demand-responsemeasures

assumedtobephasedinfrom2021withsome15%ofdemandbeingflexible26by2050.

• SlowerelectrificationratesforthenationalgridsinCambodiaandMyanmarcomparedtotheBAU,butdeploymentofoff-gridsolutionsthatachievesimilarlevelsofelectricityaccess.

• Mini-grids(off-gridnetworks)areassumedtoconnecttothenationalsysteminthelonger-term.

• ElectricvehicleuptakeaspertheBAU.

limitedbyestimatesofpotentialratesofdeploymentandjudgmentsinonwhentechnologieswouldbefeasibleforimplementationtodeliverapowersystemwiththesamelevelofreliabilityastheBAU.

• Technologiesusedinclude:solarphotovoltaics,biomass,biogasandmunicipalwasteplants,CSPwithstorage,onshoreandoffshorewind,utilityscalebatteries,geothermalandoceanenergy.

• TransmissionlimitsbetweenregionswereupgradedasrequiredtosupportpowersectordevelopmentintheGMSasanintegratedwhole,andthetransmissionplanallowedtobedifferentcomparedtothetransmissionplanoftheBAU.

ASES TheASESdemandassumptionsaredoneasasensitivitytotheSES:• Anadditional10%energyefficiencyappliedtotheSESdemands(excludingtransport).

• Flexibledemandassumedtoreach25%by2050.

• Uptakeofelectricvehiclesdoubledby2050.

ASESsupplyassumptionsarealsoimplementedasasensitivitytotheSES,withthefollowingthemaindifferences:• AllowratesofrenewableenergydeploymenttobemorerapidascomparedtotheBAUandSES.

• Technologycostreductionsareacceleratedforrenewableenergytechnologies.

• Implementamorerapidprogrammeofretirementsforfossilfuelbasedpowerstations.

• Energypolicytargetsof70%renewablegenerationby2030,90%by2040and100%by2050acrosstheregionareinplace.

• Assumethattechnical/26Flexibledemandisdemandthatcanberescheduledatshortnoticeandwouldbeimplementedbyavarietyofsmartgridanddemandresponsetechnologies.

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Scenario Demand Supplyoperationalissueswithpowersystemoperationandcontrolforaveryhighlevelofrenewableenergyareaddressed28.

28Inparticular:(1)sufficientreal-timemonitoringforbothsupplyanddemandsideoftheindustry,(2)appropriateforecastingforsolarandwindandcentralisedreal-timecontrolsystemsinplacetomanageamoredistributedsupplyside,storagesandflexibledemandresources,and(3)powersystemsdesignedtobeabletomanagevoltage,frequencyandstabilityissuesthatmayarisefromhavingapowersystemthatisdominatedbyasynchronoustechnologies.

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4.2 TechnologyCostAssumptions

Technology capital cost estimates from a variety of sources were collected andnormalised tobeonaconsistentanduniformbasis29. Mid-pointswere taken foreachtechnologythatisrelevanttotheGMSregion.Thedatapointscollatedreflectovernight, turnkey engineering procurement construction capital costs and areexclusive of fixed operating and maintenance costs, variable operating andmaintenancecostsandfuelcosts. Thecapitalcostsbytechnologyassumedinthestudy are presented in Figure 30 for the BAU and SES scenarios. For the ASESscenario,weassumedthatthetechnologycostsofrenewabletechnologiesdeclinemorerapidly.ThesetechnologycostassumptionsarelistedinFigure31.Notethatthetechnologycapitalcostshavenot includedlandcosts,transmissionequipmentcosts,nordecommissioningcostsandarequotedonaRealUSD2014basis.

CommentsonthevarioustechnologiesarediscussedbelowinrelationtotheBAUandSEStechnologycosts:

• Conventional thermal technology costs areassumed todecreaseat a rateof0.05%pa citingmaturation of the technologieswith no significant scope forcostimprovement.

• Onshorewindcostswerebasedon thecurrent installedpricesseen inChinaand Indiawith future costs decreasing at a rate of 0.6% pa. Future offshorewind costs were developed by applying the current percentage differencebetweencurrentonshoreandoffshorecapitalcostsforallfutureyears.

• Largeandsmall-scalehydrocostsareassumedtoincreaseovertimereflectingeasyandmorecost-efficienthydroopportunitiesbeingdeveloped inthefirstinstance. IRENA reported no cost improvements for hydro over the periodfrom 2010 to 2014. Adjustments are made in the case of Lao PDR andMyanmarwheresignificanthydroresourcesaredevelopedintheBAUcase30.

• Solar PV costs are based on the more mature crystalline silicon technologywhich accounts for up to 90% of solar PV installations (IRENA, 2015), andforecasttocontinuetodrop(2.3%pa)albeitataslowerpacethaninpreviousyears.

• Utility scalebattery costsarequotedona$/kWhbasis, andcostprojectionsbasedon a report byDeutscheBank (2015)which took into account severalforecastsfromBNEF,EIAandNavigant.

• Solarthermal(CSP)capitalcostsareprojectedtofallat2.8%paonthebasisofthe IRENA 2015 CSP LCOE projections. While globally there are many CSPinstallations in place, the technology has not taken off and the cost of CSPtechnology over the past 5 years has not been observed to have fallen asrapidlyassolarPV.

29WestandardisedonReal2014USDwithalltechnologiescostsnormalisedtoreflectturnkeycapitalcosts.30Capitalcostsforlargescalehydroprojectsareassumedtoincreaseto$3,000/kWby2050consistentwithhavingthemosteconomicallyfeasiblehydroresourcesdevelopedaheadoflesseconomicallyfeasibleresources.

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• BiomasscapitalcostsarebasedoncostsobservedintheAsiaregionwhicharesignificantly less than those observed in OECD countries. Capital costs wereassumed to fall at 0.1% pa. Biogas capital costs were based on anaerobicdigestionandassumedtodeclineatthesamerateasbiomass.

• Ocean energy (wave and tidal) technologieswere based on learning rates inthe ‘Ocean Energy: Cost of Energy and Cost Reduction Opportunities’ (SIOcean,2013)reportassumingglobalinstallationcapacitiesincreaseto20GWby205031.

• Capitalcostswerediscountedat8%paacrossalltechnologiesovertheprojectlifetimes.Decommissioningcostswerenotfactoredintothestudy.

• Fortechnologiesthatrunonimportedcoalandnaturalgas,wehavefactoredin the additional capital cost of developing import / fuel managementinfrastructureinthemodelling.

For reference, Appendix A tabulates the technology cost assumptions that wehaveusedinthemodelling.

Figure30 ProjectedCapitalCostsbyTechnologyforBAUandSES

*BatterycostsarequotedonaReal2014USD$/kWhbasis.

31Waveandtidalcostswereaveraged.

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Figure31 ProjectedCapitalCostsbyTechnologyforASES

*BatterycostsarequotedonaReal2014USD$/kWhbasis.

4.3 FuelPricingOutlook

IES has developed a global fuel price outlook which are based on short-termcontracts traded on global commodity exchanges before reverting towards long-term price global fuel price forecasts based on the IEA’s World Energy Outlook(WEO)2015450scenario32andasetof relationshipsbetweendifferent fuels thathave been inferred from historical relations between different types of fuels. Asummaryof the fuelpricesexpressedonanenergy-equivalentbasis ($US/MMBtuHHV)ispresentedinFigure32below.

The30%fallfrom2014to2015forthevariousfuelswastheresultofacontinuedweakening of global energy demand combined with increased stockpiling ofreserves. Brent crude prices fell from $155/bbl in mid-2014 to $50/bbl in early2015.OPECat theNovember2014meetingdidnot reduceproductioncausingoilpricestoslump.However,fuelpricesarethenassumedtoreturnfromthecurrentlowlevelstoformerlyobservedlevelswithina10yeartimeframebasedonthetimerequired for there to be a correction in present oversupply conditions to satisfysofteneddemandforoilandgas33.

To understand the implications of a lower and higher global fuel prices we alsoperformfuelpricesensitivityanalysis.Oneofthescenariosisbasedona50%fuel

32TheIEA’s450scenarioisanenergypathwayconsistentwiththegoaloflimitingglobalincreaseintemperatureto2°Cbylimitingtheconcentrationofgreenhousegasesintheatmosphereto450partspermillionCO2;furtherinformationavailablehere:https://www.iea.org/media/weowebsite/energymodel/Methodology_450_Scenario.pdf.33Reference:FactsGlobalEnergy/AustralianInstituteofEnergy,F.Fesharaki,“ANewWorldOilOrderEmergingin2016andBeyond?”,February2016,suggestareboundinpriceslevelsovera5to7yearperiodasthemost“probable”scenario.

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cost increase34to put the study’s fuel prices in the range of the IEA’s CurrentPolicies scenario35which could be argued to be closer to the fuel pricing outlookthatcouldbeanticipatedinaBAUoutlook,whiletheSESandASESscenarioscouldbe argued to have fuel prices more consistent with the IEA’s 450 scenario. Wediscuss the implications of fuel pricing on theBAU and SESwithin the context ofelectricitypricinginsection9.5.

Forreference,weprovidethefuelpricingoutlookforeachyearthatwasusedinthe fuelpricemodelling inAppendixB. These fuelpriceswereheld constant intheBAU,SESandASESscenarios.

Figure32 IESBaseCaseFuelPriceProjectionsto2050

4.4 ThailandRealGDPGrowthOutlook

Real GDP growth is assumed to maintain a 4% pa GDP growth rate to 2040consistentwithhistoricalaveragegrowth36.Towards2050,GDPgrowthisassumedtodecline towards theworldaverageof 1.96%37pa seen in Figure33. The trenddown was assumed to reflect the economic development outlook of thegovernment to2035,before there is a transition towards theworld averageGDPgrowth rate. GDP assumptions were kept constant between BAU, SES and ASESscenarios.

34Includingbiomassprices.35TheIEA’scurrentpoliciesscenarioassumesnochangesinpolicyfromtheyearofWEOpublication.363.6%pafrom2005-2014.371.96%reflectstheprevious5yearGDPgrowthofthetop10GDPcountriesintheworldexcludingBrazil,ChinaandRussia.

0

5

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15

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25

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2028

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Price

($Re

al201

4US

D/MMBtu)

CrudeOil DatedBrent FuelOil DieselOil ImportedCoal AsianLNG Uranium

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Figure33 ThailandGDPProjection

The GDP composition of Thailand is weighted towards industry in line with thestrategic aspirations of each country. The industry share of GDP in Thailand isassumed to increase from 35% in 2014 to 60% in 2030. The GDP composition isplottedinFigure34.Notethatthisassumptionisheldconstantinallcases.

Figure34 ThailandGDPComposition

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

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4.5%2015

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2027

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2039

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2049

GDPGrowth(real)

27.0%

13.0%

10.0%

35.4%

60.0%

60.0%

37.6%

27.0%

30.0%

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

2014

2030

2050

Agriculture Industry Services

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4.5 PopulationGrowth

PopulationwasassumedtogrowinlinewiththeUNMediumFertilityscenarioandisheldconstantacrossallscenarios38.

4.6 CommittedGenerationProjectsinBAU,SESandASESScenarios

Committed generation projects are the ones that are under construction or at astage of development that is sufficiently advanced for decision for the project tocome online to not be reversed. Table 6 lists committed generation projects inadditiontotheexistingfleetofgenerationprojects39.Thisisbasedoninformationfrom the PDP2015 as well as other research on the current status of variousprojects.Thetableshowstheproject’sname,itsunderstoodcapacityandthedateitisexpectedtobecommissionedby.

Table8 ThailandCommittedGenerationProjects

No. Project Capacity(MW)

GenerationType COD40

1 GulfJPUT 800 Gas 20152 RatchaburiWorldCogenerationCo.Ltd.(project2) 90 Gas 20153 B.GrimmPower 90 Gas 20154 KwaeNoiDam#1-2 30 Hydro 20155 SakaeSolarCell 5 Solar 20156 PrakarnchonDam 10 Hydro 20157 ChulabhornHydropower 10 Hydro 20158 OtherHydro 6.7 Hydro 20159 MaeHydro 12 Hydro 201510 VerySmallPowerProducers(VSPPs) 271 Gas 201611 BangLangDam(upgrade) 12 Hydro 201612 SirindhornDamSolarCell 0.3 Solar 201613 EGATSolarProject 10 Solar 201614 OtherVSPPs 283 Gas 201715 Hydropower 5.5 Hydro 201716 LamtakongPhase2 24 Wind 201717 GulfJPUTCo.,Ltd.#1-2(Jun,Dec) 1600 Gas 201818 OtherVSPPs 288 Gas 201819 LamtakongPumpStorage#3-4 500 Hydro 201820 Maw#4-7Replacement 600 Coal 2018

38UNDepartmentofEconomicandSocialAffairs,WorldPopulationProspects:The2012Revision.39ThailandexportprojectsinLaoPDR,HongSaCoal,Xayabouly(Xayaburi),Sepian-XenamnoyandNamNgiep1arenotincludedinthetable.40Commercialoperationdate.

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21 TronDamHydropower 2.5 Hydro 201822 ChulabhornDamHydropower 1.3 Hydro 201823 EGATBiomass 4 Bio 201824 EGATBiogas 5 Bio 2018

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4.7 RegionalTransmissionSystemIntegration

ThemodellingpresentedinthisreportassumestransmissionintheGMSbecomesmoretightlyintegratedthanatpresent.Giventhemodellingperiodisfor35years,weuseaverysimplemodelfortheinterconnectionsasillustratedinFigure35.ThefigureshowstheassumedtopologyoftheGMSaswellastocountriesoutsidetheregion(PRCandMalaysia). Initially,notalltransmissionconnectionsshowninthediagram are in place. However, over the modelling period the transmissionconnectionsareexpandedasrequiredtoallowpowerexchangebetweenregionstominimise costs and take advantage of diversity in demand and resourceavailabilities. Each scenario therefore effectively has a different high-leveltransmissiondevelopmentplan41.

The main differences in the assumptions behind the transmission systemenhancementsineachscenariowere:

• IntheBAU,itwasassumedthattransmissiondevelopmentsoccurslowlyandatightly integratedregionalpowersystemis inplacefromabout2030,butthepower sectors are developed so that there is only a limited level ofdependencyon imports fromneighbouringcountries. This is consistentwithpower sector planning that seeks to not be overly dependent on powerimportsfromneighbouringcountries.

• IntheSESandASES,thetransmissionsystemevolvesfrom2025andweallowthetransmissionsystem(basedonasimplifiedmodeloftheregion)toexpandasneeded tooptimise theuseof a geographicallydisperse setof renewableenergy resources. A consequence of this is that some countries becomesignificantexportersofpowerwhileothers takeadvantageofpower importsfrom neighbouring countries. In particular Myanmar and Lao PDR becomemajorpowerexporterswiththebeneficiariesbeingtheotherGMScountries.

41Weonlyconsiderahigh-leveltransmissiondevelopmentplanbasedontheregionalmodelshowninordertogaininsightoninterregionalpowerflows.

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Figure35 SimpleTransmissionSystemModel

4.8 ImportsandExports

ThailandisconnectedtotheCambodianandMalaysianpowergridsandthereareanumberofprojectsunderdevelopment inneighbouringcountries thatwill exportmost if not all of their power output to Thailand. In section 2.6, we providedcommentaryonthecurrentstateofexisting,andplanned importprojectsandwehave assumed the construction of the projects listed in Table 9. The capacitiesshown inthetablehavebeende-ratedbasedonthepowerpurchaseagreementsthatThailandhaswiththehostcountryfortheseprojects.

Table9 ThailandCommittedImportProjects

No. Unit Country Capacity(MW) Type COD

1 Su-ngaiKolok-Rantau-Panjang

Malaysia(TNB)–Thailand(EGAT)132kVInterconnection 100 Grid-to-

Grid 2015

2 HongsaThermal#1-2 LaoPDR(powerpurchasedfromLaoPDR) 982 Coal 2015

3 HongsaThermal#3 LaoPDR(powerpurchasedfromLaoPDR) 491 Coal 2016

4 ImpactEnergyWindFarm Mostofthewindfarm’soutputwillbepurchasedbyThailand 540 Wind 2019

THAILAND

MYANMAR

CAMBODIA

VIETNAM

LAOPDR

HanoiLuangPrabang

Vientiane

Mandalay

Yangon

HoChiMinhCity

PhnomPenh

Bangkok Angkor

SiemReap

Vientiane

ChiangMaiMM

TH

LAO

CAM

VN-S

VN-C

VN-N

PRC

MAL

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4.9 TechnicalEconomicPowerSystemModelling

TechnicalandeconomicmodellingoftheGMSwasdoneinthePROPHETelectricityplanningandsimulationmodels.Itdevelopsaleastcostgenerationbasedplanandwas used to simulate the operation of the GMS region as an integrated powersystem.

Abriefoverviewofthevariousaspectsisprovidedbelow:

• PlanningModule: The PlanningModule of Prophet allows for intertemporalconstraintssuchasenergy limits tobepreservedwhensimulatingthepowersystemanddevelopments.Italsodevelopsaleastcostsetofnewentrantstosatisfydemandoverthe35-yearmodellinghorizon.

• Transmission:ThepowersystemwasmodelledbasedontheconfigurationasperFigure35withfixed/scheduledflows(redlines)topowersystemsoutsidetheGMSnotbeingexplicitlymodelledwhilepowertransferswithintheGMScountrieswereoptimisedasneededtoallowsupplyanddemandtobalance.Thisisimportantwithrespecttomodellingdiversityindemandinthedifferentregionsandgeographical variation ingenerationpatterns fromsupply-drivenrenewableenergy (solarandwind)andseasonalvariationof inflows into thehydrostorages(seesection3.13).

• Economics:Capitalandoperatingcostsrelatingtogenerationplantsaspertheassumptions covered in this report allow the Planning Module to modelgenerationand transmissiondevelopment ina leastcostmanner. On topofthis,resourceconstraintshadtobeformulatedtoreflectactuallimitssuchasthemaximum renewable resource and development rates available to eachcountry.

• Demand:Demand profiles were constructed from energy and peak demandforecasts for electricitybasedon regressionmodels thatweredeveloped foreach sector of the electricity industry (commercial, industrial, residential,agricultural and transport). The monthly and intraday construction of theprofileswereperformed in Prophet basedonhistorical data and/or externaldatasourcesindicatingtheseasonalprofileofdemandforeachcountry.

• Flexible demand:wasmodelledasMWandGWh/monthquantities that canbe scheduled as necessary to reduce system costs. Thismeans that demandtendstobeshiftedfromperiodswhensupplyanddemandwouldotherwisebetighttoothertimes.Thetechnologyforreschedulingdemandwasassumedtobeinplacefrom2020intheSESandASESscenarios.

• Supply: The approach taken for modelling generation supply technologiesvariedaccordingtothetechnologytype.Thisisdiscussedfurtherbelow:- Conventional thermal plant: is modelled as capacity limited plants, with

fuel take-or-pay contracts applied to generators where relevant– forexample,gassupply limitsapplied toLNG facilitiesoroffshoregas fields.Examplesofsuchplantsincludecoal,biomass,gas,anddieselgenerators.

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- Energylimitedplants:suchaslarge-scalehydroswithreservoirs/storagesandCSPhavemonthlyenergy limitscorresponding toseasonalvariationsin energy inflows. The equivalent capacity factors are based on externalreportsforhydroandresourcedataforCSP(seenextpoint).

- Supply-drivengeneration forms: Seasonalprofiles forwind, solarand runofriverhydroswithoutreservoirsweredevelopedonanhourlybasis.Forwind and solar theywere derived frommonthly resource data collectedfrom a variety of sources including NASA, NREL42and accessed via theSolarandWindEnergyResourceAtlas (SWERA)Toolkitand IRENAGlobalAtlas.Resourceamountswerematchedagainstactualgenerationdataforknown plants to develop equivalent monthly capacity factors at varioushigh resource pockets in each country. Several traces were built fromknowngenerationtracestoprovidediversificationbenefits.

- PumpStorageandbatterystorage:thesearemodelledinasimilarwaytoflexibledemandinthatdemandcanbeshiftedwithacapacityandenergylimit but the scheduled demand is stored for generation later with anappropriateenergyconversionefficiency(pumpedstoragesassumedtobe70%andbatterystoragesystemsat85%).

42DNIandWindNASALowResolutionandNRELDIModerateResolutiondata.

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5 BusinessasUsualScenario

5.1 BusinessasUsualScenario

TheBAUscenarioassumesindustrydevelopmentsconsistentwiththecurrentstateof planning in Lao PDR and reflective of growth rates in electricity demandconsistent with an IES view of base development, existing renewable energytargets, where relevant, aspirational targets for electrification rates, and energyefficiencygainsthatarelargelyconsistentwiththepoliciesseenintheregion.

5.2 ProjectedDemandGrowth

Thailand’s on-grid electricity demand (including transmission and distributionlosses43)isplottedinFigure36.Thailand’selectricitydemandisforecasttoincreaseat a rateof3.0%paover the35-yearperiod to2050witha slowdown in growthpost-2040astheeconomytrendstowardslong-termglobalGDPgrowthrates.Theelectricity growth compared to other GMS countries is much lower due to thealready industrialisedeconomy,highelectrification ratesanddecliningpopulationassumptions.

The industrial sector is forecast to grow the fastest at 3.3% pa followed by thecommercialsectorat2.6%,residentialat2.4%andagricultureat1.2%astheGDPcompositionshiftstowardscommerce/servicesandindustry,equallyaccountingforacombined90%ofGDPby2050.Thetransportsectorisforecasttohit28TWhby2050asthenumberofcarsanduptakeofelectriccarsandmotorbikesincreaseto25% penetration. Thailand electricity demand is forecast to reach 532 TWh by2050.PeakdemandisplottedbelowinFigure37andshowspeakdemandgrowingat3.0%pareaching81GWby2050.The loadfactor isassumedtotrendtowards75% by 2040 mainly driven by additional industrial loads impacting the demandbase.

Key drivers for demand growth and the demand projections are summarised inTable10.

43Notethatunlessotherwisestated,allotherdemandchartsandstatisticsincludetransmissionanddistributionlosses.

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Figure36 ThailandProjectedElectricityDemand(2015-2050,BAU)

Figure37 ThailandProjectedpeakDemand(BAU)

0

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200

300

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6002010

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Energy(inclosses,TWh)

Agriculture Industry Commercial Residenwal Transport

BAUProjecwon

0

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Table10 ThailandDemandandDemandDrivers(BAU)

No. Aspect 2015-30 2030-40 2040-501 DemandGrowth(pa) 3.5% 3.2% 2.3%2 GDPGrowth(Real,pa) 4.0% 4.0% 2.9%3 ElectrificationRate(Population) 100.0% 100.0% 100.0%4 PopulationGrowth 0.60% 0.23% -0.04%5 PerCapitaConsumption(kWh) 3,117 4,324 6,0206 ElectricityElasticity* 1.61 1.39 1.397 ElectricityIntensity(kWh/USD) 0.310 0.292 0.303*Electricityelasticityiscalculatedaselectricitydemandgrowthdividedbythepopulationgrowthoverthesameperiod

5.3 ProjectedInstalledCapacityDevelopment

TheBAUinstalledcapacity(MW)forThailandisplottedinFigure38andFigure39bycapacitysharesforselectedyears:2010,2015,2020,2030,2040and2050.Theformershowsinstalledgenerationcapacitybythemaingenerationtypecategories.We provide corresponding statistics in Table 11 and Table 12. Note that theinstalled capacity numbers includes dedicated generation that is effectivelyavailable toThailandas importsandwhereappropriate thishasbeende-rated toreflectsupplyagreements.

Installed capacity in 2014 increases from 37 GW to 116 GW with gas-firedgeneration accounting for 34% of total installed capacity. Gas-fired capacityincreases from 26 GW of 39 GW by 2050 comprised of mainly CCGT. Over thisperiod,significantgasgenerationisretiredandreplacedwithnewgastechnology.New conventional coal technology is built in Thailand (Thailand PDP 2015) as asourceofbaseloadgenerationfrom2026,toreachsome16GW,or14%ofthetotalinstalledcapacity,by2050.Thenotablerampupincoalcapacityfrom2014in2015and 2016 is related to the Hong Sa coal-fired stationswhich is developed in LaoPDR,andtotalsome1,470MW44ofpowerexportsforThailand.

Thailand is assumed to reach 20% renewable electricity generation by 2050withsolarPVrampingupfrom2016andprovidingthebulkofrenewablecapacity(16%oftotalinstalledcapacityby2050).Biogenerationandwindenergyalsocontributetothetargetwith9GWand8GWofinstalledcapacityby2050respectively.Largehydrogrowsto17GWsupportedbyprojectsfromLaoPDR.

44Notethatwehavede-ratedHongSa’scapacitytotheamountofpowerthatisavailabletoThailand.

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Figure38 ThailandInstalledCapacity(BAU,MW)

Figure39 ThailandInstalledCapacityMixPercentages(BAU,%)

0

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CapacityM

W

Coal Hydro Gas Wind Diesel/FO

Nuclear Bio Solar HydroROR PumpStorage

13% 14% 11% 8% 9% 14%

11% 14%12% 15% 17%

15%

76% 70%

61%51% 43% 34%

1%

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7%2%

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10%16% 16% 16%

1% 2% 3% 4%

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cityM

ix

Coal Hydro Gas Wind Diesel/FO

Nuclear Bio Solar HydroROR PumpStorage

BAUProjection

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Table11 ThailandCapacitybyType(BAU,MW)

Resource 2010 2015 2020 2030 2040 2050

Coal 4,428 5,758 5,640 5,276 8,080 16,080

Diesel 0 5 5 5 255 1,755

FuelOil 45 0 0 0 0 0

Gas 25,508 28,902 30,564 32,528 38,928 38,928

Nuclear 0 0 0 0 0 2,000

Hydro 3,747 5,743 6,265 9,858 15,465 17,565

OnshoreWind 0 223 1,052 2,088 4,109 6,572

OffshoreWind 0 0 0 10 239 1,026

Biomass 0 313 1,173 2,673 5,173 8,673

Biogas 0 0 0 0 0 0

Solar 0 100 5,178 10,378 14,778 18,378

CSP 0 0 0 0 0 0

Battery 0 0 0 0 0 0

HydroROR 0 0 300 1,500 2,700 4,200

Geothermal 0 0 0 0 0 0

PumpStorage 0 0 0 0 0 333

Ocean 0 0 0 0 0 0

Table12 ThailandCapacitySharebyType(BAU,%)

Resource 2010 2015 2020 2030 2040 2050Coal 13% 14% 11% 8% 9% 14%

Diesel 0% 0% 0% 0% 0% 2%

FuelOil 0% 0% 0% 0% 0% 0%

Gas 76% 70% 61% 51% 43% 34%

Nuclear 0% 0% 0% 0% 0% 2%

Hydro 11% 14% 12% 15% 17% 15%

OnshoreWind 0% 1% 2% 3% 5% 6%

OffshoreWind 0% 0% 0% 0% 0% 1%

Biomass 0% 1% 2% 4% 6% 8%

Biogas 0% 0% 0% 0% 0% 0%

Solar 0% 0% 10% 16% 16% 16%

CSP 0% 0% 0% 0% 0% 0%

Battery 0% 0% 0% 0% 0% 0%

HydroROR 0% 0% 1% 2% 3% 4%

Geothermal 0% 0% 0% 0% 0% 0%

PumpStorage 0% 0% 0% 0% 0% 0%

Ocean 0% 0% 0% 0% 0% 0%

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5.4 ProjectedGenerationMix

Figure40plotsthegenerationmix(onanasgeneratedbasis45)overtimeintheBAUcase and Figure 41 plots the corresponding percentage shares. Coal-firedgenerationinitiallyincreasesfrom38TWhto46TWhwiththecommissioningoftheHongSacoal-firedpowerstationin2015/16inLaoPDRTable13andTable14showthegenerationsharebysnapshotyearto2050.

Over time thegeneration shareof coaldeclines towards2025 thenpicksupwithplannedcoaldevelopmentstomeetbaseloadrequirementsaccountingfor25%ofsupply by 2050. Large-scale hydro generation increases in line with growinginstalledcapacities(mainlyimports)butmaintainsitsgenerationsharearound10%of total production. The gas generation share decreases from 73% in 2010 toapproximately 35% by 2050 as other technologies are brought into the systemcoinciding with gas supply limitations in Thailand. The two units of nucleargenerationinitiallydisplacegasgenerationandaccountfor3%by2050.

As renewable capacity increases, the generation share slowly picks up fromapproximately1% in2015 toaround24%by2050,whichwasbasedon followingtheAEDP2015 to2036andallowing increases in renewable energybeyond2036.Biomassaccountsfor11%,solarPV6%andwind3%ofthesystemtotalin2050.

45Unlessotherwisestated,allgenerationchartsandstatisticsinthisreportarepresentedonan“asgenerated”basis,meaningthatgenerationtocovergenerator’sauxiliaryconsumptionaccountedfor.

FINAL


Figure40 ThailandGenerationMix(BAU,GWh)

Figure41 ThailandGenerationMixPercentages(BAU,%)

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Table13 ThailandGenerationbyType(BAU,GWh)

Generation 2010 2015 2020 2030 2040 2050

Coal 29,764 46,807 45,864 42,836 65,884 130,554

Diesel 0 0 0 0 0 0

FuelOil 600 0 0 0 0 0

Gas 118,438 115,720 130,810 177,954 212,511 183,068

Nuclear 0 0 0 0 0 16,238

Hydro 13,684 22,137 24,146 37,997 59,608 67,702

OnshoreWind 0 500 2,364 4,731 9,338 14,984

OffshoreWind 0 0 0 24 543 2,338

Biomass 0 2,059 7,730 17,564 34,082 56,984

Biogas 0 0 0 0 0 0

Solar 0 170 8,855 17,723 25,334 31,384

CSP 0 0 0 0 0 0

HydroROR 0 0 0 0 0 0

Geothermal 0 0 1,164 5,782 10,472 16,189


Ocean 0 0 0 0 0 329

Table14 ThailandGenerationsharebyType(BAU,%)

Generation 2010 2015 2020 2030 2040 2050Coal 18% 25% 21% 14% 16% 25%

Diesel 0% 0% 0% 0% 0% 0%

FuelOil 0% 0% 0% 0% 0% 0%

Gas 73% 62% 59% 58% 51% 35%

Nuclear 0% 0% 0% 0% 0% 3%

Hydro 8% 12% 11% 12% 14% 13%

OnshoreWind 0% 0% 1% 2% 2% 3%


Biomass 0% 1% 3% 6% 8% 11%

Biogas 0% 0% 0% 0% 0% 0%

Solar 0% 0% 4% 6% 6% 6%

CSP 0% 0% 0% 0% 0% 0%

HydroROR 0% 0% 0% 0% 0% 0%

Geothermal 0% 0% 1% 2% 3% 3%

PumpStorage 0% 0% 0% 0% 0% 0%

Ocean 0% 0% 0% 0% 0% 0%

FINAL


5.5 GridtoGridPowerFlows

Figure 42 plots the imports and exports in the BAU with the dotted linerepresentingthenetinterchange.OverallflowsintheBAUarerelativelylowupto2029whenimportsfromMyanmarstarttoincreasewithitstransmissioncapabilityaugmentedover timeto3,250MWby2050drivenbydifferences in the levelisedcostofelectricity.OutsideofthededicatedLaoPDRhydroprojects,afurther600-800MWofpowerflowsintoThailandfromLaoPDR.

Figure42 ThailandImportsandExports(BAU,GWh)

5.6 ProjectedGenerationFleetStructure

Figure 43 shows the installed generation capacity by the main categories ofgeneration: thermal, renewableand largescalehydro, inorder toprovidegreaterinsightintothebasicstructureofinstalledcapacityundertheBAU.Thishighlightsthat Thailand’s BAU projection is as anticipated heavily dominated by fossil-fuelbased generation. However, renewable capacity and generation increases overtimetomeetitsrenewableenergytarget.Figure44showstheon-gridcompositionof generation by major categories of generation: thermal, large hydro andrenewable. AscouldbeanticipatedgenerationcloselyreflectstheBAU’s installedcapacitymix.

To facilitate later comparisonwith theSES, Figure45plots installedcapacitywithcapacity being distinguished between the following basic categories: (1)dispatchable capacity, (2) non-dispatchable capacity; and (3) semi-dispatchable

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capacity 46 . This provides some insight into the operational flexibility of thegeneration fleet tomatchdemanduncertainty. Thedispatchablecategoryrelatestogenerationthatcanbecontrolledanddispatchedatshortnoticetorampupordown,non-dispatchablemeansthatthegenerationisnotabletorespondreadilytodispatchinstructionswhilethesemi-dispatchablecategorymeansthattheresourcecanrespondwithinlimits,andinparticulariscapableofbeingbackedoffshouldtheneedarise to forexample, avoidoverloading thenetworkor “spill” energy in theeventthatanovergenerationsituationemerges;solarphotovoltaicsandwindfarmswithappropriatelyinstalledcontrolsystemscanbeclassifiedinthiscategory.IntheBAU,overtime,asrenewablegenerationtrendstowards29%ofthetotalinstalledcapacity by 2050, the dispatchable percentage declines to 74% although stillsuggestsahighlevelofdispatchcontrol.

Figure43 ThailandInstalledCapacitybyGenerationType(BAU,MW)

46Windandsolarisclassifiedassemi-dispatchable,geothermalandhydrorun-of-riverisclassifiedasnon-dispatchableandallothertechnologiesareclassifiedasdispatchable.

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Figure44 ThailandGenerationMixbyGenerationType(BAU,GWh)

Figure45 ThailandInstalledCapacitybyDispatchStatus(BAU,MW)

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5.7 ReserveMarginandGenerationTrends

Figure46plots the reservemarginbasedonnameplatecapacityandannualpeakdemand.TheThailandreservemarginintheBAUincreasespast50%by2021andthendeclines coincidingwith 3,000MWof gas plant retirements before trendingback towards 45% by 2050. From 2025 to 2035, as renewable capacity starts toramp up driving the reservemargin increases consistent with the lower capacityfactorsrelativetoconventionaltechnologies.Thermalcapacitydropsto51%%andhydrocapacityremainsaround14%acrossthehorizon.

Figure46 ThailandReserveMargin(BAU)

To obtain a better understanding of the broad mix of generation capacity andgenerationmix, Figure 47 and Figure 48 show shares in installed capacity and ingeneration grouped by the main categories of generator: thermal, large hydro,renewableenergy(RE)andlargehydroplusrenewableenergy.

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Figure47 ThailandCapacitySharesbyGenerationType(BAU)

Figure48plotsthegenerationsharesbyseveraldifferentcategoriesofgeneration.The thermal generation share declines from 87% in 2015 to 60% by 2050.Renewableenergyincludinglarge-scalehydrograduallyincreasesto40%in2050asmore renewable plants enter the system. The BAU has large-scale hydro beinglargelyexploitedandrenewableenergydeploymentoccurring inawayconsistentwiththeGovernment’splans.

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Figure48 ThailandGenerationSharesbyGenerationType(BAU)

5.8 ElectrificationandOff-Grid

Thailand’s grid-based electrification rate for its urban and rural population isassumedtoreachcloseto100%by2030intheBAU.Duetothelimitedimpactofoff-grid in this scenario it has been decided to only model the central grid-connectedpowersystem.

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6 SustainableEnergySectorScenario

6.1 SustainableEnergySectorScenario

The SES seeks to transition electricity demand towards the best practicebenchmarksofotherdevelopedcountriesintermsofenergyefficiency,maximisethe renewable energy development, cease the development of fossil fuelresources, andmake sustainable and prudent use of undeveloped conventionalhydro resources. The SES takes advantage of existing, technically proven andcommerciallyviablerenewableenergytechnologies.


Figure 49plots Thailand’s forecast energy consumption from2015 to 2050withthe BAU energy trajectory charted as a comparison. The significant savings aredue to additional energy efficiency assumptions relating to the various sectorsachieving energy intensity benchmarks of comparable developed countries inAsia47.TheSESdemandgrowsataslowerrateof2.1%paovertheperiodto2050withthecommercialsectorgrowingat1.9%pa, industrygrowingat2.4%paandtheresidentialsectorgrowingat0.8%pa.Theagriculturalsectorgrowsat1%andtheuptakeofelectrictransportoptionsoccurfrom2025onwardsandgrowsto28TWhaccountingfor5%oftotaldemandby2050or25%ofallvehicles.

Figure 50 plots peak demand of Thailand. The firm blue line represents peakdemand before any flexible demand side resources have been scheduled 48 .Flexibledemandresponseis“dispatched”inthemodelinlinewiththeleastcostdispatchofall resources in thepowersystem. Thedashed line representswhatpeak demand became as a consequence of scheduling (“time-shifting”)commercial,industrialandresidentialloadstominimisesystemcosts.From2020,the amount of flexible demand was assumed to grow to 10% of total demandacrossallsectorsby2050,or15%ifstoragemethodsareincluded.TheloadfactorassociatedwiththeSESwasalsoassumedtoreach80%(comparedto75%underthe BAU case) by 2030 as a further consequence of enhanced demand sidemanagementmeasuresrelativetotheBAU.


47Thailand’sindustrialintensitywastrendedtowardslevelscommensuratewithHongKong(2014)by2050.HongKonghadthelowestintensitybasedonabasketofcomparablecountriesandthedefinedintensitymetric.48Flexibledemandresponseis“dispatched”inthemodelinlinewiththeleastcostdispatchofallresources.Thesolidlinerepresentspeakdemandasputinthemodel,whilethedashedlinerepresentswhatpeakdemandendedupbeingasaconsequenceofshiftingdemandfromoneperiodoftimetoanother.Thisincludesschedulingofloadsassociatedwithbatterystoragedevicesandrescheduling(time-shifting)commercial,industrialandresidentialloads.

FINAL


Figure49 ThailandProjectedElectricityDemand(2015-50,SES)

Figure50 ThailandProjectedElectricityDemand(SES,MW)

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Table15 ThailandDemandandDemandDrivers(SES)

No. Aspect 2015-30 2030-40 2040-501 DemandGrowth(pa) 2.4% 1.7% 1.7%2 GDPGrowth(Real,pa) 4.0% 4.0% 2.9%3 ElectrificationRate(Population) 100.0% 100.0% 100.0%4 PopulationGrowth 0.60% 0.23% -0.04%5 PerCapitaConsumption(kWh) 3,026 3,880 4,6536 ElectricityElasticity* 1.56 1.28 1.207 ElectricityIntensity(kWh/USD) 0.301 0.262 0.234*Electricityelasticityiscalculatedaselectricitydemandgrowthdividedbythepopulationgrowthoverthesameperiod


Figure 51 plots the installed capacity developments under the SES and Figure 52plots the corresponding percentage shares. Table 16 and Table 17 provide thestatisticaldetailsoftheinstalledcapacityandcapacitysharesbytypeincludingtheestimated2010levels.

Committed and existing plants are assumed to come online as per the BAU butaren’treplacedwhenretired.Plannedandproposedthermalandlarge-scalehydrodevelopments are assumed to not occur, with the exception of replacement gasplants, and all other generation requirements are instead met by renewabletechnologies.Coalandgasfired-generationintheearlieryearsisverysimilartotheBAUduetocommittedprojects.Overtime,thesecapacitiesdropoffduetoplantretirementsandaccountforonly11%oftotalinstalledcapacityby2050comparedto 89% in 2015. Large-hydro penetration also decreaseswith planned large-scalehydroreplacedwithrenewableenergy.

Timing of renewable energy developments are based on the maturity of thetechnology and judgments of when it could be readily deployed in Thailand.Additional demand in the SES is predominantlymet by renewableswith 129GWrequired tomeet 2050 electricity demand froma current capacity base less than1,000 MW (large-scale and grid connected). Solar PV is to account for 58 GW,biomass12GW,CSP8GW,andwindenergy25GWofthetotalby2050.Batterystorage with an equivalent capability of 20 GW is developed to support thesignificantamountofsolarPVandoff-peakload.

FINAL


Figure51 ThailandInstalledCapacitybyType(SES,MW)

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Figure52 ThailandCapacityShares(SES,%)

Table16 ThailandCapacitybyType(SES,MW)

Resource 2010 2015 2020 2030 2040 2050

Coal 4,428 5,758 5,640 2,567 1,221 1,221

Diesel 0 5 5 5 5 5

FuelOil 45 0 0 0 0 0

Gas 25,508 28,902 28,700 22,367 18,000 15,558

Nuclear 0 0 0 0 0 0

Hydro 3,747 5,743 6,265 6,139 5,191 5,191

OnshoreWind 0 223 2,767 10,812 17,073 22,202

OffshoreWind 0 0 0 54 994 3,465

Biomass 0 313 1,673 4,673 8,673 11,246

Biogas 0 0 0 0 0 427

Solar 0 100 7,746 24,546 41,346 58,546

CSP 0 0 0 1,650 4,800 8,250

Battery 0 0 0 0 8,650 20,335

HydroROR 0 0 300 1,500 2,700 4,200

Geothermal 0 0 0 75 150 225


Ocean 0 0 0 0 0 0

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FINAL


Table17 ThailandCapacitySharebyType(SES,%)

Resource 2010 2015 2020 2030 2040 2050

Coal 13% 14% 11% 3% 1% 1%

Diesel 0% 0% 0% 0% 0% 0%

FuelOil 0% 0% 0% 0% 0% 0%

Gas 76% 70% 54% 30% 16% 10%

Nuclear 0% 0% 0% 0% 0% 0%

Hydro 11% 14% 12% 8% 5% 3%

OnshoreWind 0% 1% 5% 15% 16% 15%


Biomass 0% 1% 3% 6% 8% 7%

Biogas 0% 0% 0% 0% 0% 0%

Solar 0% 0% 15% 33% 38% 39%

CSP 0% 0% 0% 2% 4% 5%

Battery 0% 0% 0% 0% 8% 13%

HydroROR 0% 0% 1% 2% 2% 3%

Geothermal 0% 0% 0% 0% 0% 0%

PumpStorage 0% 0% 0% 0% 0% 1%

Ocean 0% 0% 0% 0% 0% 0%


GridgenerationisplottedinFigure53andFigure5449.ThecorrespondingstatisticsforsnapshotyearsareprovidedinTable19andTable20.

Thailand’sgenerationmixintheearlieryearsto2020issimilartotheBAUcaseascommitted new entry are commissioned. Gas-fired generation is assumed to bedevelopedreplacingoldplantskeepingthesysteminstalledgasconsistentwiththecapacity of the recently commissioned LNG facility. Thermal and large hydroprojects outside what is deemed existing or committed is not developed andrenewabletechnologyisusedtomeettheremainingincrementaldemand.Biomassgeneration grows to 92 TWh by 2050 accounting for 23% of the country’sgeneration, CSP contributes 10%, and wind accounts for 15%. By 2050, solar PVaccountsforthehighestgenerationshareat26%oralmost100TWhofgeneration.By2050renewabletechnology(excludinglarge-scalehydro)generates79%(or84%including large-scalehydro)of totalpower requirements in thecountrycoincidingwiththeretirementsofoldergasandcoalplants.

49Batterystorageisnotincludedasstoragetechnologiesaregenerationneutral.

FINAL


Figure53 ThailandGenerationMix(SES,GWh)

Figure54 ThailandGenerationShare(SES,%)

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Table18 ThailandGenerationbyFuel(SES,GWh)

Generation 2010 2015 2020 2030 2040 2050Coal 29,764 46,807 45,864 20,841 9,547 5,622Diesel 0 0 0 0 10 0FuelOil 600 0 0 0 0 0Gas 118,438 113,791 99,824 108,582 69,103 55,910Nuclear 0 0 0 0 0 0Hydro 13,684 22,137 24,906 23,795 18,779 20,259OnshoreWind 0 500 6,219 24,505 38,803 50,617OffshoreWind 0 0 0 123 2,258 7,900Biomass 0 2,190 11,753 32,745 67,951 89,522Biogas 0 0 0 0 0 3,397Solar 0 170 13,246 41,918 70,881 99,980CSP 0 0 0 5,763 20,749 36,924HydroROR 0 0 1,164 5,782 10,472 16,189Geothermal 0 0 0 491 993 1,480PumpStorage 0 0 0 0 252 835Ocean 0 0 0 0 0 0

Table19 ThailandGenerationSharebyFuel(SES,%)

Generation 2010 2015 2020 2030 2040 2050Coal 18% 25% 23% 8% 3% 1%Diesel 0% 0% 0% 0% 0% 0%FuelOil 0% 0% 0% 0% 0% 0%Gas 73% 61% 49% 41% 22% 14%Nuclear 0% 0% 0% 0% 0% 0%Hydro 8% 12% 12% 9% 6% 5%OnshoreWind 0% 0% 3% 9% 13% 13%OffshoreWind 0% 0% 0% 0% 1% 2%Biomass 0% 1% 6% 12% 22% 23%Biogas 0% 0% 0% 0% 0% 1%Solar 0% 0% 7% 16% 23% 26%CSP 0% 0% 0% 2% 7% 10%HydroROR 0% 0% 1% 2% 3% 4%Geothermal 0% 0% 0% 0% 0% 0%PumpStorage 0% 0% 0% 0% 0% 0%Ocean 0% 0% 0% 0% 0% 0%

FINAL



Figure55plotstheimportsandexportsintheSESwiththedottedlinerepresentingthenet interchange. Thailand importsandexportsmore intheSESthantheBAUduetooptimisinggenerationacrosstheregionratherthanonacountrybycountrybasis. Thailand imports are all from Myanmar with 7,000 MW of transmissiondevelopments. From2025Thailandstarts toexportenergy intoCambodia (up to3,300 MW) and into Lao PDR (up to 5,000 MW) – flows into Lao PDR augmentpowersupplyintoVietnam.Thailandonanetbasisstartsoffasanimporterthenexportssimilarquantitiestowards2050.

Figure55 ThailandImportsandExports(SES)


AsfortheBAU,togaininsightintothenatureofthemixofgenerationtechnologiesdeployedintheSES,wepresentanumberofadditionalcharts.Figure56andFigure57 showThailand’s installed capacity andgenerationby type for the SES– this isclearlyheavilybiased towards renewablegeneration formsand there is agradualreductioninthethermalpowerplants.ForThailand,aconsiderableamountofnon-renewableenergycontinuestofeatureinthegenerationmixandmainlyrelatestotheinvestmentinitsLNGfacilityandgasgenerationplants.

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Figure56 ThailandInstalledCapacitybyGenerationType(SES,MW)

Figure57 ThailandGenerationMixbyGenerationType(SES,GWh)

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Figure 58, shows the dispatchable, semi-dispatchable and non-dispatchablecomponents of installed capacity and it can be seen that semi-dispatchableincreases toaround64%of thetotalsystemcapacitycomparedtoaround22% inthe BAU by 2050. Based on operational simulations with this resource mix, itappearstobeoperationallyfeasible,althoughtherelianceongenerationformsthatprovidestorageandhavingflexibilityinthedemandsideplayimportantroles.Itisclearthatshort-termrenewableenergysolarandwindforecastingsystemswillbeimportant, as will real-time updates on demand that can be controlled.Furthermore, control systems that canallow thedispatchof flexible resourcesonbothsupplyanddemandsidesoftheindustrywillberequired.

Figure58 ThailandInstalledCapacitybyDispatchStatus(SES,MW)


Figure 59 plots the reserve margin under the SES. Figure 60 and Figure 61,respectively, show the installed capacity mix and generation mix for differentcategories of generation in the power system. The reserve margin in the SESincreases to 140%by 2050 as installed renewable capacity increases to 83%. Thehighreservemargin is relatedto the lowcapacity factor technologiesdeployed inthe SES. Conventional reserve margin measures are generally not suited tomeasuringhigh renewable energy systems in the same context used for thermal-basedsystems.Renewabletechnologiesgenerallyhavemuchlowercapacityfactorsand require more capacity to meet the same amount of energy produced fromthermal-basedtechnologies.

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Figure59 ThailandReserveMargin(SES)

Figure60 ThailandInstalledCapacitySharesforSESbyGenerationType

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Figure61 ThailandGenerationSharesforSESbyGenerationType


Most of Thailand is already electrified and as per the BAU in the SES we haveassumedthatthegridremainsacentrallyinterconnectedintothefuture.

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7 AdvancedSustainableEnergySectorScenario

7.1 AdvancedSustainableEnergySectorScenario

TheASESassumesthatthepowersectorisabletomorerapidlytransitiontowardsa 100% renewable energy technologymix under an assumption that renewableenergy is deployed more than in the SES scenario with renewable energytechnologycostsdecliningmorerapidlycomparedtoBAUandSESscenarios.


Figure 62plots Thailand’s forecast energy consumption from2015 to 2050withtheBAUandSESenergytrajectorychartedwithadashedlineforcomparison.TheSESenergysavingsagainsttheBAUareduetoallowingThailand’senergydemandto transition towards energy intensity benchmarks of comparable developedcountriesinAsia.TheASESappliesanadditional10%energyefficiencyagainsttheSES demands which is partially offset with additional transport demandsassociatedwithhigheruptakerates.Electricvehicleuptakeisassumedtodoubleto50%intheASES.

TheSESdemandgrowsataslowerrateof2.2%paovertheperiodfrom2015to2050 with the commercial sector at 1.8% pa, industry growing at 2.2% pa andresidential sectorgrowingat0.8%pa. Demand fromthe transport sector in theASESisdoubledandgrowsto57TWhor14%oftotaldemandby2050.

Figure63plotsthepeakdemandofThailand.Thefirmblue linerepresentspeakdemand without any demand side management impacts. Demand sidemanagement reflectsdemandresponses to tight supplyandnetworkconditions.This is assumed to grow to as much as 17.5% of demand across all sectors by2050, representing the portion of flexible demand that is not met throughtechnologymeans(i.e.batterystorage).TheloadfactorassociatedwiththeASESisalsoassumedtoreach80%(comparedto75%undertheBAUcase)by2030asafurtherconsequenceofenhanceddemandsidemanagementmeasuresrelativetotheBAU.


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Figure62 ThailandProjectedElectricityDemand(2015-50,ASES)

Figure63 ThailandProjectedElectricityDemand(ASES,MW)

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Table20 ThailandDemandandDemandDrivers(ASES)

No. Aspect 2015-30 2030-40 2040-501 DemandGrowth(pa) 2.3% 1.9% 1.9%2 GDPGrowth(Real,pa) 4.0% 4.0% 2.9%3 ElectrificationRate(Population) 100.0% 100.0% 100.0%4 PopulationGrowth 0.60% 0.23% -0.04%5 PerCapitaConsumption(kWh) 2,976 3,812 4,6566 ElectricityElasticity* 1.54 1.28 1.227 ElectricityIntensity(Demand/GDP) 0.296 0.257 0.234*Electricityelasticityiscalculatedaselectricitydemandgrowthdividedbythepopulationgrowthoverthesameperiod


Figure 64 plots the installed capacity developments under the SES and Figure 65plots the corresponding percentage shares. Table 21 and Table 22 provide thestatisticaldetailsoftheinstalledcapacityandcapacitysharesbytypeincludingthe2010levels.

Committed and existing plants are assumed to come online as per the BAU butaren’treplacedwhenretired. Existingthermalplantareretiredearlytomeettheimposedrenewablegenerationtargetsacrosstheregion.Renewabletechnologiesramp up much faster than in the SES to replace retirements of conventionalgenerationtechnologies.By2030lessthan20%oftheinstalledcapacityisbasedonfossilfuelsandisentirelyphasedoutby2050.

By 2050 there is 68 GW (or 39%) of installed solar PV supported by 37 GW ofbattery storage capability mainly to defer generation for off-peak periods.Significant investment in wind, biomass and CSP technologies occur tomeet therising demands, accounting for 15%, 10%, and 6%, respectively, of total installedcapacityby2050.

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Figure64 ThailandInstalledCapacitybyType(ASES,MW)

Figure65 ThailandCapacityShares(ASES,%)

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Table21 ThailandCapacitybyType(ASES,MW)

Resource 2010 2015 2020 2030 2040 2050

Coal 4,428 5,758 5,458 5,098 2,965 0

Diesel 0 5 5 0 0 0

FuelOil 45 0 0 0 0 0

Gas 25,508 28,902 18,171 9,194 5,826 0

Nuclear 0 0 0 0 0 0

Hydro 3,747 5,743 6,265 6,265 6,265 6,265

OnshoreWind 0 223 3,796 14,722 24,566 25,946

OffshoreWind 0 0 0 74 1,430 4,049

Biomass 0 313 2,173 7,673 13,673 16,673

Biogas 0 0 0 0 0 0

Solar 0 100 10,843 35,643 58,043 68,043

CSP 0 0 0 2,100 6,000 10,050

Battery 0 0 0 1,360 24,360 37,013

HydroROR 0 0 300 1,500 2,700 4,200

Geothermal 0 0 0 75 150 225

PumpStorage 0 0 0 0 600 1,800

Ocean 0 0 0 0 0 0

Table22 ThailandCapacitySharebyFuel(ASES)

Resource 2010 2015 2020 2030 2040 2050

Coal 13% 14% 12% 6% 2% 0%

Diesel 0% 0% 0% 0% 0% 0%

FuelOil 0% 0% 0% 0% 0% 0%

Gas 76% 70% 39% 11% 4% 0%

Nuclear 0% 0% 0% 0% 0% 0%

Hydro 11% 14% 13% 7% 4% 4%

OnshoreWind 0% 1% 8% 18% 17% 15%


Biomass 0% 1% 5% 9% 9% 10%

Biogas 0% 0% 0% 0% 0% 0%

Solar 0% 0% 23% 43% 40% 39%

CSP 0% 0% 0% 3% 4% 6%

Battery 0% 0% 0% 2% 17% 21%

HydroROR 0% 0% 1% 2% 2% 2%

Geothermal 0% 0% 0% 0% 0% 0%

PumpStorage 0% 0% 0% 0% 0% 1%

Ocean 0% 0% 0% 0% 0% 0%

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ASESgrid generation is plotted in Figure66andgeneration shares in Figure6750.ThecorrespondingstatisticsforsnapshotyearsareprovidedTable24andTable25.Thailand’sgenerationmixintheearlieryearsto2020issimilartotheBAUcaseascommitted new generation projects are commissioned and this has largely beenkeptthesame.

Of the renewable technologies, by 2050, solar PV contributes the highestgenerationshareof11TWhor31%followedbybiomassat28%.Windcomprisedmainlyofonshoreprojects contribute18%of the totalgeneration shareby2050.Biomass fills the baseload role in the power system as gas and coal plantstechnologies retireearlier than in theSES.By2030,76%ofall generation is fromrenewablesources(includeslarge-scalehydro)andmovestowards100%by2050.

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Figure66 ThailandGenerationMix(ASES,GWh)

Figure67 ThailandGenerationMix(ASES,%)

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Table23 ThailandGenerationbyType(ASES,GWh)

Generation 2010 2015 2020 2030 2040 2050

Coal 29,764 46,807 44,384 39,189 12,109 0

Diesel 0 0 0 0 0 0

FuelOil 600 0 0 0 0 0

Gas 118,438 113,139 92,356 18,682 12,266 0

Nuclear 0 0 0 0 0 0

Hydro 13,684 22,137 24,146 24,146 24,146 24,146

OnshoreWind 0 500 8,532 33,365 55,832 59,154

OffshoreWind 0 0 0 168 3,249 9,232

Biomass 0 2,190 15,267 53,769 67,080 105,652

Biogas 0 0 0 0 0 0

Solar 0 170 18,542 60,868 99,505 116,198

CSP 0 0 0 7,440 25,996 44,974

HydroROR 0 0 1,164 5,782 10,472 16,189

Geothermal 0 0 0 491 993 1,480

PumpStorage 0 0 0 0 712 2,130

Ocean 0 0 0 0 0 0

Table24 ThailandGenerationSharebyType(ASES,%)

Generation 2010 2015 2020 2030 2040 2050

Coal 18% 25% 22% 16% 4% 0%

Diesel 0% 0% 0% 0% 0% 0%

FuelOil 0% 0% 0% 0% 0% 0%

Gas 73% 61% 45% 8% 4% 0%

Nuclear 0% 0% 0% 0% 0% 0%

Hydro 8% 12% 12% 10% 8% 6%

OnshoreWind 0% 0% 4% 14% 18% 16%


Biomass 0% 1% 7% 22% 21% 28%

Biogas 0% 0% 0% 0% 0% 0%

Solar 0% 0% 9% 25% 32% 31%

CSP 0% 0% 0% 3% 8% 12%

HydroROR 0% 0% 1% 2% 3% 4%

Geothermal 0% 0% 0% 0% 0% 0%

PumpStorage 0% 0% 0% 0% 0% 1%

Ocean 0% 0% 0% 0% 0% 0%

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Figure 68 plots the imports and exports in the BAU with the dotted linerepresenting the net interchange. The power flows in the ASES is similar inmagnitudetotheSESwithmostof thepower importedfromMyanmardueto itsvast renewable resources and smaller energy requirement. Across the horizon,Thailand is a net importer with comparatively smaller exports of energy intoCambodiaandLaoPDR.

Figure68 ThailandImportsandExports(ASES)


Togain insight into thenatureof themixof generation technologiesdeployed intheASES,wepresentanumberofadditionalcharts.Figure69andFigure70showThailand’s installedcapacitybygenerationtypefortheSES–this isclearlyheavilybiasedtowardsrenewablegenerationformsandthereisasteadyreductioninthethermal power plants. For Thailand, a considerable amount of non-renewableenergy continues to feature in the generation mix in the earlier years beforedecliningto0by2050.

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Figure69 ThailandInstalledCapacitybyType(ASES)

Figure70 ThailandGenerationMixbyType(ASES)

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Figure 71, shows the dispatchable, semi-dispatchable and non-dispatchablecomponents of installed capacity and it can be seen that semi-dispatchableincreases toaround71%of thetotalsystemcapacitycomparedtoaround22% inthe BAU by 2050. Based on operational simulations with this resource mix, itappearstobeoperationallyfeasible,althoughtherelianceongenerationformsthatprovidestorageandhavingflexibilityinthedemandsideplayimportantroles.Itisclearthatshort-termrenewableenergysolarandwindforecastingsystemswillbeimportant, as will real-time updates on demand that can be controlled.Furthermore, control systems that canallow thedispatchof flexible resourcesonbothsupplyanddemandsidesoftheindustrywillberequired.

Figure71 ThailandInstalledCapacitybyDispatchStatus(ASES)


Figure 72 plots the reserve margin under the ASES. Figure 73 and Figure 74,respectively, show the installed capacity mix and generation mix for differentcategoriesofgenerationinthepowersystem.TheASESreservemargintrendspast100% as conventional baseload technologies are retired early to meet therenewableenergypolicytargetof100%by2050.

Itisworthnotingconventionalreservemarginmeasuresaregenerallynotsuitedtomeasuringhigh renewable energy systems in the same context used for thermal-

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basedsystems.Renewabletechnologiesgenerallyhavemuchlowercapacityfactorsand require more capacity to meet the same amount of energy produced fromthermal-basedtechnologies.

Figure72 ThailandReserveMargin(ASES)

Figure73 ThailandInstalledCapacitySharesforASESbyGenerationType

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Figure74 ThailandGenerationSharesforASESbyGenerationType


Most of Thailand is already electrified and as per the BAU in the SES we haveassumedthatthegridremainsacentrallyinterconnectedintothefuture.

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8 AnalysisofScenariosSection5,section6andsection7presentedprojectionsofcapacityandgenerationmixfortheBAU,SESandASESscenariosrespectively. InordertounderstandtheimplicationsoftheSESandASESovertheBAU,wehaveformulatedasetofmetricstoassistintheircomparison.

Theseareasfollows:

• Overallenergyconsumptionperyear;• Peakelectricitydemandperyear;• Renewableenergypercentagecomparisons;• Carbonemissionsmeasures;• Hydropowerdevelopments;• Analysisofbioenergysituation;• Anumberofsimplesecurityofsupplymeasures;and• Interregionalpowerflows.

8.1 EnergyandPeakDemand

Figure 75 compares the total electricity consumption of the BAU, SES and ASESwithFigure76plottingthepercentagereductioninelectricityconsumptionoftheSESrelativetotheBAUandASESrelativetotheBAU.Ascanbeseentheenergyconsumption, the SES is lower than the BAU with the main driver beingenhancementsinenergyefficiencyintheSES.ThereductioninenergyintheASESisoffsetbythedoublingoftransportdemand.

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Figure75 ThailandEnergyDemandComparison

Figure76 ThailandPercentageReductioninElectricityDemand

Figure77comparespeakloadandshowsthesamerelativities.Thisisattributabletoimprovementsinloadfactor(80%inSESandASES).OntopofthistheSESandASES has contributions from flexible and controllable demand that allowsreductionsinpeakdemandconsumption(notshownhere).

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Figure77 ThailandPeakDemandComparison

8.2 Energyintensity

Figure 78 plots the per capita electricity consumption per annum across thescenarios. Electricity consumption includes all electricity consumption across thecountry. In the BAU, per capita consumption levels increase at a rate of 2.9% toreach 7,500 kWh pa around Singapore’s current levels. In the ASES and SES, itincreasesmoreslowlyat2.0%patoapproxiamtely5,600kWhpa-theSESandASESassumes higher energy efficiency savings keeping it below Hong Kong’s currentlevels.ItshouldbenotedthatGDPgrowthassumptionsremainconstantacrossallscenarioswiththedifferenceintheASESandSESbeingmeasurestakentoimproveenergyefficiency.

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Figure78 ThailandPerCapitaConsumptionComparison(kWhpa)

8.3 GenerationMixComparison

Figure79andFigure80below shows the renewable capacity andgenerationmixbetween the two scenarios. Renewable capacity (including large-scale hydro)reaches49%intheBAUwhichisequivalenttoa36%generationsharecomparedtothecapacityreaching87% in theSEScontributing83%. TheASEShasrenewables(including large-scalehydro)accounting for100%of totalcapacityandgenerationby2050.

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Figure79 ThailandRenewableInstalledCapacityMix

Figure80 ThailandRenewableGenerationMixComparison

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8.4 CarbonEmissions

Figure81andFigure82showthecarbonintensityofThailand’spowersystemandthe total per annum carbon emissions respectively. The BAU trajectory intensitydeclinesinitiallyto2040asadditionalgasandrenewablegenerationenterthemixbelowbefore reversing the trend as additional coal generation is developed. TheintensitytrajectoryintheSESreaches0.07t-CO2e/MWhby2050.Intermsoftotalcarbonemissions,theshifttowardstheSESandASESsavesupto157and184mt-CO2e,respectively,ortheequivalenttoa85%and100%savingfromtheBAU.

Figure81 ThailandCarbonIntensityComparison

Figure82 ThailandCarbonEmissionsComparison

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8.5 HydroPowerDevelopments

Table 22 lists the hydro generation projects and commissioning year under the 3scenarios. Hydro projects are assumed to be refurbish as required to maintainoperationsthroughoutthemodellinghorizon.Asdiscussedearlier,projectssuchasNamNgiep 1 located in other countries but dedicated to exports are included asprojectsintheexportmarkets(withcapacitiesadjustedaccordingly).

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Table25 HydroPowerDevelopments(BAU,SESandASES)

HydroProjectInstalledCapacity(MW)

YearCommissioned

BAU SES ASES

KwaeNoiDam#1-2 30 2015 2015 2015PrakarnchonDam 10 2015 2015 2015ChulabhornHydropower 10 2015 2015 2015MaeHydro 12 2015 2015 2015BangLangDam(upgrade) 12 2016 2016 2016LamtakongPumpStorage#3-4 500 2018 2018 2018TronDamHydropower 2.5 2018 2018 2018Xe-PianXe-Namoi 354 2025

ProjectsnotdevelopedintheSESandASES

NamNgiep1 269 2021Xayaburi 1220 2026PhaDam 14 2028LamtakongDam 1.5 2029LamPaoDam 1 2032YasothonHydropower 4 2032PranburiDam 1.5 2033MahaSarakhamHydropower 3 2033ManPhayaHydropower 2 2034NoidaHydropower 2 2034LamtapearnHydropower 1.2 2034VillageHydropower 1.5 2035ChulabhornPumpStorage 800 2035ThapSalaoDam 1.5 2035SriNakarinPumpStorage 801 2036FaiLamDomeYaiHydropower 2 2037KamalasaiHydropower 1 2037SamongDam 1 2037DamHydropower 16 2037LuangDamHydropower 1 2038

8.6 AnalysisofBioenergy

Figure 83 shows aprojectionof thebiomass available for theGMS (converted toGWh)andthetotalbiomassgenerationforeachscenariofortheGMS.Theshaded

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pink area represents the projected total technical biomass resource availability51while the solid lines show the biomass consumption used by each scenario. Theprojectedavailablebiomasswasbasedonforecastgrowthratesintheagriculturalsectors of each country. It was assumed that no more than 75% of the totalprojected available biomass resourcewas used. The remainder of the bioenergyrequirements for each scenario was then assumed to be satisfied by biogastechnologies.

Figure84showsasimilarcharttofortheGMSexceptforbiogas.Thegreenshadedareainthischartrepresentstheamountofbiogasavailable(againinunitsofGWh)and the corresponding generation frombiogas in each scenario. This shows thattheSESandASESaredependentonbiogaswhiletheBAUisassumedtonotdeploythis technology. Based on the projections the biomass and biogas resourcesavailable to the region can be seen to be sufficient to support the amount ofbiomassandbiogasgenerationto2050.

Figure83 ProjectedBiomassAvailabilityandConsumptionintheBAU,SESandASESscenariosfortheGMSasawhole

51ProjectionsofbiomassavailabilitydevelopedbyIESbasedonbaselinesestablishedfrominformationonbiomassandbiogaspotentialreportedin‘RenewableEnergyDevelopmentsandPotentialintheGreaterMekongSubregion’,ADB(2015)report.

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Figure84 ProjectedGMSBiogasRequirements

8.7 SecurityofSupplyIndicators

Figure85plotstheenergyreservemargincalculatedasthedifferencebetweenthemaximumannual production from all plants accounting for energy limits and theannual electricity demands. For importing countries like Thailand, gross importlimits have also been included. The figure below shows similar energy reservemargins with the ASES having lower margins in the earlier years due to theretirementofgasplants.

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Figure85 ThailandSecurityofSupplyMeasure:EnergyReserve

Figure86chartsthepercentageofelectricitygeneratedusingdomesticresources.The percentage generated using domestic fuel sources start above 75% anddecline over time to around 36% by 2050 in the BAU as more gas and coal isimported.ThesecuritylevelintheSESandASEScaseremainsrelativelyhigh.TheASEShasthehighestsecurityofsupplyfrom2030butdoesnotreach100%duetopowerimportsfromMyanmar.TheSESsecurityindexislowerthantheASESduetogasplantsstillinthegenerationmixto2050andimportsalso.

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Figure86 ThailandSecurityofSupplyMeasure:PercentageofElectricityGeneratedbyDomesticResources

Figure87belowplotsthehighestshareofgenerationfromaparticularfuelsource.IntheBAU,thedominanceisheldbygasfiredgenerationthroughoutthehorizon.TheSESisdominatedbygasupuntil2040beforesolarPVcaptures23%and26%in2040 and 2050. The ASES follows the same trend as the SES except solar PVdominatesthegenerationmixfrom2030.AcrossallscenariositisclearthattheSESandASESgenerationmixesarealotmorediversifiedthanintheBAU.

Figure87 ThailandSecurityofSupplyMeasure:MaximumDominanceofaTechnologyinGenerationMix

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Figure88plotsthedependenceoncoalinallscenarios.TheAESandSEStrajectoriesdeclineasexpectedwhereastheBAUdropsto15%in2030butincreasesto25%by2050as14,000MWof additional coal isbrought into themix tomeet increasingdemands.

Figure88 ThailandSecurityofSupplyMeasure:CoalShare

8.8 InterregionalPowerFlows

Figure89comparesthenet flows inandoutofThailand.TheBAUhasthe lowestamount of imports due to the way BAU generation developments occur andThailand is a net importer initially in the SES before exporting into Lao PDR andCambodia towards 2050. In the ASES, Thailand is a net exporter throughout thehorizon,importingupto10%ofitspowerrequirements.

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Figure89 ThailandImports(positive)andExports(negative)(GWh)

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9 EconomicImplicationsIn this sectionwe consider the economic implications of the three scenarios andexamineinparticular:(1)thelevelisedcostofelectricity(LCOE)generationfortheentire system, (2) investment costs, (3) total operating and capital expenditureincluding the cost of energy efficiency and (4) implications for job creation. Itshouldbenotedthattheanalysispresentedinthissectionisdoneforthepurposeof comparison,and that thepricesandcostsprovidedaredependenton the fuelpriceprojectionsandtechnologycostassumptionsthatwereusedinthescenariosandhavebeenlistedinAppendixAandAppendixB.TheanalysisinthissectionisalsosupportedbysensitivityanalysistoexaminehowchangesinfuelpricesimpacttheLCOEandtoexaminehowacarbonpricewouldaffectelectricitycosts.

9.1 OverallLevelisedCostofElectricity(LCOE)

ThecomparisonoftheLCOE(onlyincludesgenerationcosts)isshowninFigure90.TheLCOEfortheBAUstartstoincreaseinitiallyasaresultof increasingfuelcostsreturning to long-term averages then steadily declines to $112/MWhas coal andgascostsstayflatandlowercostrenewablegeneration isaddedintothecapacitymix.

TheASES and SES initially decline then rise fromaround2030onwardsdrivenbymoreinvestmentinhighercostrenewabletechnologiesandbatterystoragewhichincreases the overall LCOE. The ASES LCOE is significantly lower than the otherscenarios due to the accelerated cost reductions assumed. By 2050 the SES andASES reaches$105/MWhand$99/MWhrespectively.This LCOEanalysisdoesnotincludethecostofexternalities52.

52Adetailedstudyonthecostofexternalitiesispresentedinthefollowingreference:MarkZ.Jacobsonetal.,“100%CleanandRenewableWind,Water,andSunlight(WWS)AllSectorEnergyRoadmapsfor139CountriesoftheWorld”,13December2015,available:https://web.stanford.edu/group/efmh/jacobson/Articles/I/CountriesWWS.pdf.

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Figure90 ThailandLCOEforGeneration

9.2 LCOEComposition

Highintegrationlevelsofrenewableenergyallowfortheavoidanceoffuelcosts.InordertounderstandthestructureoftheLCOEfromtheprevioussectionweprovidedecomposedversionsof theLCOE inFigure90 for theBAU,Figure91 for theSESandFigure92fortheASES.Thisrevealsanimportanttrendinthestructureofthecostofelectricity:athermal-dominatedsystemhasahighportionofitscostsasfuelcosts while a renewable energy dominated power system ismore heavily biasedtowardscapitalcosts.AsisshownintheSEScase,thefuelcostcomponentsteadilydecreasesfromearlyinthemodelling53.

TheSESandASEScapitalcostsona$/MWhbasisincreasesgraduallyduetogreaterinvestmentsinbatterystorage,offshorewindandCSP.

53Itdoesnotgotozeroduetobiogeneration.

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Figure91 ThailandLCOECompositioninBAU

Figure92 ThailandLCOECompositioninSES

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Figure93 ThailandLCOECompositioninASES

9.3 CumulativeCapitalInvestment

Thefollowingsectiondetails the investmentcostsofmeetingdemand inThailandandalso takes intoaccount import costs (at theLCOEofneighbouring countries).Conversely, the investment costs of net exporting countries will be reducedaccordingtothepercentageofpowerthatisexported.

Figure 94 shows the cumulative investment in generation CAPEX and energyefficiencyinmillionsofReal2014USD.AlthoughtheearlierobservationoftheSESand ASES having lower demand owing to energy efficiency gains should berecognised. Figure94showstheBAUrequiring lesscapital investmentacross themodellinghorizonprimarilydrivenby investment ingasplants tomeet increasingdemands.TheSESandASESincludesinvestmentinenergyefficiencymeasuresandgreater investments in CSP, offshore wind and battery storage to defer solar PVgenerationwhichrampsuppost-2035.

Thebreakdownof costsbygeneration typearepresented in Figure95, Figure96andFigure97.

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Figure94 ThailandCumulativeInvestment(Real2014USD)

Figure95 ThailandCumulativeInvestmentbyType(BAU,Real2014USD)

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Figure96 ThailandCumulativeInvestmentbyType(SES,Real2014USD)

Figure97 ThailandCumulativeInvestmentbyType(ASES,Real2014USD)

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Figure98,Figure99andFigure100plotthecumulativeinvestmentsplitforimportsandexports. TheBAU investmentcost isprimarily for itsownelectricitydemandwithonlysmallamountsofpowerimportedfromMyanmar.By2050,$176billionisrequired todevelop theBAUgeneration requirements. In theSES,$250billion isrequiredtodevelopgenerationprojects(andenergyefficiency)inThailand,withafurther$34billiononprojectsoutsideThailand,or$108billionmorethantheBAUby2050.TheASESaddsanadditional$39billionbringing the total investment to$323billionby2050,or$147billionmorethantheBAUat2050.

Figure98 ThailandCumulativeInvestmentofBAU(Real2014USD)

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Figure99 ThailandCumulativeInvestmentofSES(Real2014USD)

Figure100 ThailandCumulativeInvestmentofASES(Real2014USD)

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9.4 OperatingCosts,AmortisedCapitalCostsandEnergyEfficiencyCosts

Figure101plotsthetotalCAPEX,OPEXandenergyefficiencycostsasaproportionof total forecastGDP.Capitalexpenditurehasbeenamortisedover the lifeof theproject toderiveannualcapexfigures.TheBAUrisestoalmost6%ofGDPmainlydriven by the rampup in fuel costs before declining as the LCOE drops andGDPcontinues to increase. The SES and ASES costs are very similar with the ASESrequiring less investmentthantheSESdueto lowerdependenceon fossil fuels inthemedium to long term. Figure 102, Figure 103 and Figure 104 plots the totalannualsystemcostforeachofthescenarios.

Figure101 TotalCAPEX,OPEXandEnergyEfficiencyoverGDP

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Figure102 TotalSystemCostbyType(BAU)

Figure103 TotalSystemCostbyType(SES)

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Figure104 TotalSystemCostbyType(ASES)

Figure 105 and Figure 106 plots the difference in amortised CAPEX, OPEX andenergyefficiencycostsbetweentheSESandBAU,andASESandBAUrespectively.The costs have also been adjusted for exports and imports. Positive amountsrepresentanadditionalinvestmentrequiredineithertheSESorASESandnegativeamountscorrespondtocostsavings.

For the SES against BAU case, the fuel savings are immediate as renewabledevelopmentsdisplacetraditional fossil fuels increasingtowards$20billionayearin fuel savings by 2050 (noting demand differences between the two scenarios).Capex remainsmoreexpensive in theSESdespitenuclear investment in theBAU.Energyefficiencyisassumedtocostupto$3billionayearby2050.Acrossallthreecategories,thenetresultisacostsavingofupto$15billionayearby2050.

The ASES follows similar trends with a higher capex investment than in the SESdespitecost reductions inCAPEX. This isdrivenbytheaddedrenewablecapacityrequired to replace conventional gas and coal from 2020 onwards. The higherCAPEXalsoproduceshigherOPEXsavingsofupto$26billionayearby2050.TheASEShasnetsavingsofupto$17billionayearby2050.

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Figure105 DifferenceinCAPEX,OPEXandEnergyEfficiencyCosts(SESandBAU)

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Figure106 DifferenceinCAPEX,OPEXandEnergyEfficiencyCosts(ASESandBAU)

Figure107 NPVofSystemCostsover2015-2050period

Figure107charts thenetpresentvalueof thepowersystemcostsbycomponentusingan8%and15%discount rate.Figuresare tabulated inTable26.TheBAU iscomprisedofahigherpercentageof fuelcosts,whereas theASEShas thehighest

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percentagerelatingtocapitalcosts.ThetotalNPVdifferencebetweentheBAUandASESisapproximately$83billionunderan8%discountrate

Table26 NPVofSystemCosts(RealUSD2014)

NPV($m’s) BAU@8% SES@8% ASES@8% BAU@15% SES@15% ASES@15%FuelCost 249,456 166,564 120,307 119,374 90,639 73,292CapitalCost 91,884 114,334 130,111 44,091 52,969 57,293FOM 10,014 11,979 13,232 4,916 5,644 5,869VOM 15,666 14,404 13,857 7,782 7,317 7,071EnergyEfficiency 0 5,540 6,808 0 1,511 1,966Total 367,019 312,821 284,315 176,163 158,080 145,492

9.5 FuelPriceSensitivity

Figure108plotstheLCOEoftheBAU,SESandASESasdiscussedinsection9.2.Inaddition,itplotstheLCOEfora50%increasetothefuelprices,whichreflectsthedifferencebetweenIEA’scrudeoilpricingunderthe450ScenarioandtheCurrentPoliciesScenario($95/bbland$150/bblrespectively).ItcanbeseenthattheLCOEof theBAU risesmore (up to$40/MWh) against a fuel price increase comparedwith the SES and ASES ($25/MWh and $15/MWh respectively), as would beanticipatedasadirectconsequenceofhavingahigherthermalgenerationsharein the BAU compared to renewable energy in the SES and ASES. The SESincreases, and the ASES to a smaller extent, as a consequence of bioenergygeneration,butascanbeseenitisfarlesssensitivetofuelpriceshocksthantheBAU.

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Figure108 ThailandFuelPriceSensitivity($/MWh)

9.6 ImpactofaCarbonPrice

Inasimilarwaytotheprevioussection,Figure109plotstheLCOEundertheBAU,SES and ASES and the LCOE under a carbon price scenario. The carbon scenarioputsa$20/t-CO2impostthroughouttheentiremodelledperiod.ThisisintendedtoshowthesensitivityoftheBAU,SESandASEStothecarbonprices.Inasimilarwayto the previous section, this shows that LCOE in the SES is relatively insensitive($4/MWh),andtheASESinsensitive,tocarbonpricesby2050whilefortheBAU,itaddsanadditional$8Real2014USD/MWhtotheLCOE.

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Figure109 ThailandCarbonSensitivities($/MWh)

9.7 RenewableTechnologyCostSensitivity

Figure 110 shows the LCOE sensitivity to 20% and 40% decreases in renewabletechnology costs.Asexpected theASES followedby theSES is themost sensitivewithpotentialdeclinesofupto$25/MWh.TheSESandASESLCOEisalreadywellbelowtheBAUbecauseofgasfuelpriceassumptions.

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Figure110 ThailandRenewableTechnologyCostSensitivities($/MWh)

9.8 JobsCreation

To assess the implications for Job Creation for each scenario we applied themethodology used by the Climate Institute of Australia. The methodology issummarisedinAppendixC.Thenumbersofjobscreatedforeachofthescenariosare shown in Figure 111, Figure 112 and Figure 113. The job categories showninclude:manufacturing,construction,operationsandmaintenanceandfuelsupplymanagement.Figure114providesacomparisonoftotaljobscreatedforBAU,SESandASES.Thekeyobservationsare:

• Acrossall scenarios,manufacturingandconstructionaccount formostof thejobswithamuchsmallershareattributabletoO&Mandfuelsupply.

• TheBAU job creationprofilepeaks at around145,000 jobs compared to SESjobcreationpeakingtowards320,000ormorethantwotimesthatintheBAU.This is entirely drivenby renewable energy developments that requiremorejobs in the manufacturing and construction phases. See Appendix C forassumptions.

• TheASESjobcreationpeaksat500,000jobs,morethanthreetimesthatoftheBAU driven by evenmore renewable energy projects required as the regionmovestowardsa100%renewablegenerationtargetby2050.

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• Different skills are required between the scenarios, BAUhas peopleworkingonconventionalcoalandhydro,whereastheSESandASEShaspeoplemainlyworkingonsolar&batterystoragesystems.

• Note that themanufacturing and fuel supply jobs shown to be createdmaynot be created within Thailand with manufacturing of equipment and fuelmanagement(forimportedfuels)occurringinothercountries.

Figure111 JobCreationbyCategory(BAU)

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Figure112 JobCreationbyCategory(SES)

Figure113 JobCreationbyCategory(ASES)

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Figure114 TotalJobCreationComparisonBAU,SESandASES

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10 ConclusionsComparedtootherGMScountries,thedevelopmentoftraditionalprimaryenergyresources in Thailand for electricity generation face a number of challenges.Thailand’s proven offshore gas reserves in the Gulf of Thailand and Thailand-MalaysiaJointDevelopmentArea(JTA)arebeingutilisedwithcontractedgasfromthese reservesexpected tobedepletedby2030. Liquefiednaturalgas (LNG)hasbeen available since 2011 as a stop-gapmeasurewith terminal sized at an initialcapacity of 5MTPA54and anoption to double capacity to 10MTPA. Reserves ofdomestic coal consist mainly of lignite to sub-bituminous grade concentratedaroundtwomainreserves:MaeMohinthenorthandKrabiinthesouth,withtheformerbeingexploited,andthelatterbeingconsideredforexploitation.TherehasalsobeenafocusondevelopinganoptionforNuclearPowerwitheffortsoverthelast decade taken by Thailand to enhance knowledge and capability to enablenuclear power to be a long-term option should it be needed to address powersupplyshortages.

In contrast to the fossil fuel situation, Thailand has substantial potential for thedevelopmentofrenewableenergy;mostnotably,biomass,solar,andwind. Largescale hydro power potential in Thailand is estimated to be around 15 GW.However,theenvironmentalexternalitiesassociatedwithexploitinghydrobeyondthe current 3.5 GW of large scale hydro already developed is regarded to beunsustainableandthereisstrongresistancetofurtherdevelopments.Withareasofthe country experiencing average wind speeds of 6-7 m/s, most notably in themountainrangesinthesouthandthenortheastduringtheperiodofthemonsoons,there is significant potential for the deployment of wind turbines for powergenerationthroughoutthecountry,particularlyalongtheseashoresandonislandseither intheGulfofThailandorAndamanSea. Beinglocatedneartotheequatorarea,Thailandhassubstantialpotentialforsolarphotovoltaicdevelopment.HavinganumberoflargeareaswithDirectNormalIrradiation(DNI)intherangeof1600toas high as 1950 kWh/m^2/year, locatedmostly in the northwestern part of thecountry is evidence for potential for deployment of Concentrated Solar Power(CSP). Asanagriculturalcountry,Thailand’spotential forbiomass intheformtheformofagriculturalresiduesissignificant.Withtheabundanceofindustrialwasteandlivestockmanure,Thailandalsohassignificantbiogaspotential.

InthisreportwehavedevelopedaBusinessasUsual(BAU)andSustainableEnergySector (SES) outlook for Thailand. The BAU outlook assumed that future powersector developments would be based on a gas, coal, large scale hydro andeventuallynuclearinthefuture.Thesehavebeendevelopedbasedoninformationprovided in the PDP2015. We have incorporated the AEDP2015 as well andadoptedgainsinenergyefficiencythatareconsistentwithourunderstandingofthe

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EEDP2015.Incontrast,theSESandASESweredevelopedtoexplorewhathappenswhenmeasures are taken todeploy amaximal amountof renewable energy andputinplacesignificantenergyefficiencymeasures.Inthisway,wehavedevelopedsomealternativescenariosforthecountry’spowersector.TheSESandASESbothalso assume a more rapid program of cross-border interconnection in the GMS,which allows the region to more fully exploit diversity in demand as well asgeographicallydispersedareaswithhighrenewableenergypotential.

10.1 ComparisonofScenarios

The following are the key conclusions that have been drawn from the analysispresentedinthisreport:

• TheSESdeliversanenergyefficiencygainbeyondtheBAUcaseofabout27%comparedtotheBAU.TheASESdeliversefficiencygainsof25%afterdoublingtransportelectricitydemand;

• The SES is able to achieve a power system that delivers 84% of generationfrom renewable energy resources (including large-scale hydro) by 2050, andtheASES is able to achieve100%. In contrast, 37%of the generation in theBAUisprovidedbyrenewableenergyresourcesby205055;

• By 2050, the SES and ASES avoids around 157 and 184 million tons ofgreenhousegasemissionsper year compared to theBAU. TheSES intensitydeclinesto0.07t-CO2/MWhby2050vs.0.135t-CO2/MWhfortheBAUcase.TheBAUcaseachievesahigheremissionsintensitylevelbecauseofincreasedcoalgenerationreliancewhiletheSESdeliveralowemissionsintensityduetowidespread deployment of solar and wind technologies. The ASES reaches100%renewablegenerationby2050.

• Basedonsomesimplemeasuresforenergysecurity:- Under the ASES and SES, Thailand benefits from a more diverse mix of

technologiesandisnotasdependentonasinglesourceofprimaryenergyas theBAU; forexample, theBAU ishighlydependenton importedcoal,while the SES diversifies supply across a range of renewable energytechnologieswithnogenerationtypeaccountingformorethan30%ofthegenerationshare;

- The ASES and SES has around 92% and 81% of its electricity beinggeneratedfromdomesticallycontrolledandmanagedresources,whiletheBAUneedstoimportprimaryenergyresourcesintheformofgasandcoal,which drives down the level of domestic control and management ofprimaryenergyresources–by2050this level reachesaround36%intheBAU. Under the ASES and SES generation developments are optimisedacross the regionandThailand importsup to10%of its requirementsby2050;and

55Large-scalehydroisincluded

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- TheASESandSESachievesareliablepowersystemthroughcoordinationonboth the supplyanddemandsideof the industry,with similarenergyreserve margins as the BAU. Though as a measure of energy supplystorage and flexibility the ASES and SES overall is lower than the BAU,whichmeansthattheBAUwouldbemoreresilientagainstextremeeventsbut isslightlyoffsetbyamore integratedregionalpowersystemthroughcross-bordertrading.WhilemodellinghasshownthattheASESandSESisoperationallyfeasible(evenwithlessdirectlydispatchableresourcesintheSES compared to the BAU), stress testing of both the BAU and SESscenarios againstmore significant threats to the operation of the powersystemwould likelynotbehandledaswell compared to theBAU. Morework to understand and develop appropriate mitigation measures isrequired.

10.2 EconomicImplications

10.2.1 ElectricityCostsBased on the outcomes ofmodelling the BAU, SES and ASES scenarios,we alsoexaminedthefollowing issues inrelationtoelectricitycosts: (1) levelisedcostofelectricity,(2) investmentrequirements,(3)sensitivityofelectricitypricestofuelpriceshocks,and(4)theimplicationsofapriceoncarbonequivalentemissionsforelectricityprices.Basedonthisanalysiswedrawthefollowingconclusions:

• The BAU requires lower levels of capital investment than the SES and ASES,and in relation to generation costs, the SES and ASES across the modellingperioddeliversaloweroverallshort-runmarginalcostofelectricityandLCOEtoThailand;

• UndertheSESandASESsignificantbenefitsaregainedintheformofavoidedfuel costs and this contributes to achieving a lower overall dollar cost forThailand. The observation ismade that the composition of LCOE under theSES and ASES is largely driven by investment costs, hence exposure to fuelshocksissignificantlyreduced;and

• TheLCOEundertheSESandASESisalsolargelyinsensitivetoacarbonprice,as could be reasonably anticipated for a power system that is entirelydominatedbyrenewableenergy.

10.2.2 InvestmentImplications

From2015to2050,theoverallinvestmentforislowerintheBAUthantheSESandASES:$176billionintheBAUcomparedto$284billionintheSESand$323billioninthe ASES (Real 2014 USD). However, the important difference is that thecomposition of the investments are quite different. The BAU directs mostinvestment(55%)tocoalandhydroprojects,whileintheSES(andASES)some38%(41%) is directed to solar and battery system technologies,with other significant

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investments in energy efficiencymeasures, bioenergy,wind andoff-grid. Clearly,compared to the BAU, the SES and ASES will require investments across amorediverse range of technologies and such technologies will tend to be smaller anddistributedratherthanbeinglargeinscale.

10.2.3 JobCreationThe SES and ASES scenarios both result in quite different technology mixes forThailand compared to the BAU. Each has quite different implications for theworkforcethatwouldberequiredtosupporteachscenario. Basedonanalysisoftherequiredjobsweestimatethat56:

• TheBAU from2015 to2050wouldbeaccompaniedby thecreationof some3.7millionjobsyears57(25%manufacturing,52%construction,15%operationsandmaintenance,and3%fuelsupply);

• The SES would involve the creation of some 7.4 million job years (28% inmanufacturing,59% inconstruction,11% inoperationsandmaintenanceand2%infuelsupply);and

• The ASES would involve the creation of 3.8 million job years (27% inmanufacturing,60% inconstruction,12% inoperationsandmaintenanceand1%infuelsupply).

FortheSES,Thailandwillneedtodevelopaskilledworkforcecapacityofsupportingsome 25 GW of solar technologies by 2030 and 59 GW by 2050. Enhancing thecapability and quality of existing solar PV enterprises will be crucial in order toincreasethelikelihoodofthenewpermanentjobsbeingoccupiedbylocalworkers.Engagingwithlowskilledtomediumskilledlabourersandcraftsmaninabottomupapproach is strongly recommended in order to absorb existing labour and futurelabourthatwillbeinneedofemployment.

10.3 IdentifiedBarriersfortheSESandASESforRenewableEnergy

Thailand has the most developed renewable energy policy among the ASEANcountries, with many incentives implemented in recent years. Despite thissuccess, renewable energy investment in Thailand still faces a number ofeconomicandnon-economicbarriers.Thesearesummarisedasfollows.

10.3.1 EconomicBarriers

The lack of interest and experience of banks in investing in new renewabletechnologieswasoneofthebarrierstosecuringfinanceinthepast.However,theENCON revolving fund has demonstrated the potential of renewable energyprojects to the banks. As a result, banks are now more willing to invest in

56BasedontheemploymentfactorspresentedinAppendixC.57Ajobyearisonejobforonepersonforoneyear.Weusethismeasuretomakecomparisonseasieracrosseachscenarioasthenumberofjobscreatedfluctuatesfromyeartoyear.

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renewable energy projects. The Thai government is no longer supporting thebankswithzero-interestloansasinthepast.

Theadderprogramfirstintroducedin2007wasconsideredbyinvestorstobethemost attractive and effective support instrument for investment in renewableenergyinThailandduetoitshighrates,especiallyforsolarPVprojects.Moreover,the rate structure is simple and easy for investors to integrate into investmentplans.Undertheadderprogram,renewableinvestorsreceivedadderratesontopof based electricity prices for a period of 7 or 10 years depending on thetechnology type. The adder program has been very successful in driving thegrowth of renewable energy in Thailand to such an extent that the initialrenewabletargetshavehadtoberevisedfromtheinitial5.6GWby2021to16.7GWby2036.

However, the adder program has also created some burdens which affectconsumerelectricitybillssincetheadderisdirectlypassedthroughtoconsumers.Under the adder program, renewable energy investors initially benefited fromhightariffsattheexpenseofconsumerelectricitybills.Duetoconcernsoverthelong-term impact on electricity bills, the adder program has subsequently beenreplacedbytheFeed-inTariff(FiT)schemewiththeintentionofmovingtowardsanewcompetitivebiddingmethodincomingyears.TheFiTschemeis intendedtobetterreflecttheactualcostsofrenewableenergyaswellasreducingtheimpactonratepayers.WiththenewFiTscheme,renewableinvestorsarepaidfixed-priceFiT rather than depending on the based electricity prices which fluctuate overtime. The fixed FiT rates are considerably lower than the adder rates but thecontractedperiodiseither20or25years,whichismuchlongerthanthatofferedundertheadderprogram.Althoughthechangesareexpectedtoprovidegreaterfinancialcertaintyovera longerperiodtorenewable investors, itstill remainstobe seenwhether theFiT schemecan stillprovide sufficient incentives to furtherdrive investment in renewable energy in Thailand. Moreover, there are stillconsiderableuncertaintiesover futurerenewablepolicysincetheGovernment isstillexploringoptionstominimisetheimpactofFiTonelectricitybillsthroughtheintroductionofacompetitivebiddingprocess.

10.3.2 Non-economicBarriers

Non-economic barriers include both regulations and technical barriers. Theaccessibility of transmission-line information still remains a risk factor forrenewable-energy investors.Acoordinatedapproachbetweenelectricityutilitieswould help to address some of this uncertainty. The limited capacity oftransmission lines, coupledwith the high cost of investment and an increase inrenewableenergyprojectsinremoteareaswithlowelectricitydemand,createsachallenge for thesector.Transmissionconstraintsareabottleneckwhichshouldbeaddressedbygovernment inorder to support thedevelopmentof Thailand’sabundant renewable energy resources in the future. The variability and partly

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dispatchablenatureofwindandsolargenerationalso increasethechallenge forpowersystemoperationandthewayinwhichthermalpowerplantsareoperated.

InordertoencouragesustainablerenewableenergyinvestmentinThailand,boththeThaigovernmentandprivatesectorneedtoworktogethertolearnfromthefailuresofthepastandtoimproveimplementationbytacklingeconomicandnon-economicbarriers.Thetechnicalbarrierscouldpotentiallybeaddressedthroughanumber of measures including transmission network augmentations, theimplementationofsmartgridsandimprovedwindandsolarforecastingtopredicttheir generation outputs more accurately. Incentives with a clear and unifiedpolicy, as well as appropriate regulations that result in attractive - but notexcessive-priceswouldbethebestsolutiontosupportinvestmentinrenewableenergyThailand.

10.4 IdentifiedBarriersfortheSESandASESforEnergyEfficiency

The key success factors to achieve the target of energy efficiency for Thailanddependonhow theenergy-savingplans andpolicies couldbe implementedandmanagedeffectivelyrathertheplansthemselves.AlthoughtheEEDPhassetforthdetailed plans and targets for driving energy efficiency, implementation is themostdifficultpartastherearemanybarriersandchallenges58.

10.4.1 InstitutionalBarriersInstitutionalfactorisoneofthelargestbarriersinimplementingenergyefficiency.This barrier is found in government agencies which usually work in verticalhierarchy of management and lack of coordination between different agencies.Ontheotherhand,implementingenergyefficiencyoftenrequiresaworkingteamconsistingofexperts/representativesacrossgovernmentagencies,andsometimeevenfromprivatesectors.Forexample,MinistryofEnergymaylaunchanenergybuilding code to improve energy efficiency in commercial buildings, butDepartment of PublicWorks and Town& Country Planning is the onewho hasauthoritytoenforcesuchcode.Therefore,lackofcoordinationandcollaborationamong different public agencies posting a challenge to implementing energyefficiency.

10.4.2 FinancialBarriersAfinancial incentive isan important tool toovercomebarriersandchallenges inimplementing energy efficiency. Thailand has had many financial tools forpromoting energy efficiency such as Energy Efficiency Revolving Fund whichconsidered as a successful case that encouraged commercial banks to invest inenergyefficiencyprojects.However,onemayargue that such financial supportsarenotyetwellknownamongsmallentrepreneursandSMEs.Inaddition,asolid

58http://www.jgsee.kmutt.ac.th/jgsee1/NewsEvents/2014/feb2014/2014-02-10/1.%20EE%20template%20(edited).pdf

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technicalknowledgeisalsonecessaryforpreparingasoundproposalforgettingafinancial support. Unfortunately, such common wisdom and expertise aregenerallyunfoundinmostsmallentrepreneursandSMEsinThailand.

Implementing energy efficiency should be market oriented and should includeprivate sector. Both producer and end user should be taken as a leading role.However, to let the market developed by itself may take a long time, sogovernment intervention in the beginning is crucial. For example, governmentagencies should promote green procurement to lift up those regulationspreventing energy efficiency improvement. Implementing energy efficiency ingovernment buildings has a large untapped market potential. This can helpprofessional like energy service company (ESCO) to develop their business plan,experienceand reputation.However, least costprocurement regulationusedbygovernment agency does not allow adopting those new innovative energyefficiencytechnologieswhichoftenhavehighinitialcostseventhoughtheymakemoreeconomicalsenseinlongrun.

10.4.3 TechnicalBarrierThailand still lacksofmeasurements, reportingandverification (MRV) system tofollowupenergyconservedbymeasures.Withoutaclear resultonhowmuchameasureoraprojectcanconserveenergy,itisunlikelythatplannerscanconserveenergy and improve efficiency effectively in order tomeet the target in a longterm. IncaseofESCO, lacking inmeasurementandverification(M&V),aprocessofquantifyingenergyconservation,mayleadtounclearresultandcontractbeingvoid.

10.4.4 LackofaWell-FunctioningDatabase

Althoughenergyintensityisoneofthemainindicatorsforenergyefficiency,moreindicators by sector is needed to be simplified for ease of implementing energyefficiency and to analyse barriers. This is crucial since energy intensity does notshow energy efficiency in details for each sector, and different sectors needdifferentenergyefficiency indicators inorder toeffectively implementmeasuresandfollowup.

10.5 Recommendations

The followingarekeyrecommendations toreducethebarriersand“enable” theSESandASES:

• Thailandhasinplaceenergypoliciesthatcreateanenvironmentthataimstobe conducive for investment in renewable energy technologies. However,experience to date suggests that there remain barriers ranging from projectdevelopersexperiencingdifficultiesinsecuringfinance,presenceofregulatoryuncertaintyandtechnicalbarriersintheformofproblemsrelatedtolicensing

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and grid connection. This suggests that efforts to improve regulatoryframeworksandtechnicalcodesmaybewarranted.

• Formation of electricity pricing policies and mechanisms that encourageefficient behavior and investment in generation technologies, transmissionanddistributionequipmentandenduseenergyconsumption.

• Continueefforts toperformmoredetailedassessmentsof renewableenergypotential and make the results publicly available to enable prospectiveinvestors to understand the potential, identify the best opportunities andsubsequentlytakestepstoexploreinvestmentanddeployment.

• Knowledge transfer and capability building in the renewable energytechnologies and energy efficiency for policy makers, staff working in theenergyindustry,aswellaswithineducationinstitutionstoensurethehumancapacityisbeingdevelopedtosupportanationalpowersystemthathasahighshareofgenerationfromrenewableenergy.

• Investments in ICTsystemstoenhancereal-timepowersystemoperationsofboth supplyanddemandsidesof the industry suchas smart-grid technologyand integration of renewable energy forecasting systems and tools intopresentsystemsforcentralizedreal-timesystemoperations. Thiswillenableefficient real-timedispatchandcontrolofall resources inThailand’snationalpower system and will create an environment more conducive for themanagement of high levels of renewable energy and flexible (dispatchable)demand.

• Take measures to encourage a coordinated approach to enhancing cross-border power trade in the region since this works to the advantage ofexploiting diversity in renewable energy resource potential and diversity inelectricity demand. Thiswould require a shift from investment indedicatedimport projects in neighboring countries, towards a platform that is able tosupportmultilateralpowertrade.Somefeaturesoftherecommendedapproachare:- Develop an overarching transmission plan that has been informed by

detailedassessmentsandplanstoleveragerenewableenergypotentialintheregionanddiversityindemandandhydrologicalconditions.

- Enhance / adapt technical standards and transmission (or Grid) codes ineachcountrytoallowforbetterinteroperationofnationalpowersystems.

- Establish dispatch protocols to better coordinate real-time dispatch ofpowersystemsintheregiontomakethebestuseofreal-timeinformationandcontinuouslyupdateddemandandrenewablegenerationforecasts.

- Develop a framework to encourage energy trade in the region, and inparticulartowardsamodelthatcansupportmultilateralpowertradingviaaregionalpowermarketorexchange(forexample).

• Takemeasurestoimprovepowerplanningintheregionto:

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- Explicitlyaccountforprojectexternalitiesandrisks,- Evaluateamorediverserangeofscenariosincludingthosewithhighlevels

ofrenewableenergy,- Takeintoconsiderationenergyefficiencyplans,- Take into consideration overarching plans to have tighter power system

integrationwithintheregion,and- Carefullyevaluatetheeconomicsofoff-gridagainstgridconnectionwhere

thisisrelevant.

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AppendixA TechnologyCostsTable 27 sets out the technology cost assumptions that were used in themodellingpresented in this report for theBAUandSESscenarios. Table28setsoutthetechnologycostsusedintheASES. Thetechnologycostsofcoalandgasdo not include overheads associatedwith infrastructure to develop facilities forstoring/managingfuelsupplies.Thesecostswerehoweveraccountedforinthemodelling.

Figure 115 and Figure 116 presents the levelised cost of new entry generationbasedonassumedcapacityfactors.LCOElevelspresentedinSection9arebasedonweightedaverageLCOE’sandmodelledoutputandwilldifferfromtheLCOE’spresented here. The LCOE for battery storage is combined with solar PVtechnologyassuming75%ofgenerationisstoredforoff-peakgeneration.

Table27 TechnologyCostsAssumptionsforBAUandSESScenarios

TechnologyCapitalCost(Unit:Real2014USD/kW)Technology 2015 2030 2040 2050GenericCoal 2,492 2,474 2,462 2,450CoalwithCCS 5,756 5,180 4,893 4,605CCGT 942 935 930 926GT 778 772 768 764WindOnshore 1,450 1,305 1,240 1,175WindOffshore 2,900 2,610 2,480 2,349HydroLarge 2,100 2,200 2,275 2,350HydroSmall 2,300 2,350 2,400 2,450PumpedStorage 3,340 3,499 3,618 3,738PVNoTracking 2,243 1,250 1,050 850PVwithTracking 2,630 1,466 1,231 997PVThinFilm 1,523 1,175 1,131 1,086BatteryStorage-Small 600 375 338 300Battery-UtilityScale 500 225 213 200Solar Thermal withStorage

8,513 5,500 4,750 4,000

Solar Thermal NoStorage

5,226 4,170 3,937 3,703

Biomass 1,800 1,765 1,745 1,725Geothermal 4,216 4,216 4,216 4,216Ocean 9,887 8,500 7,188 5,875Biogas(AD) 4,548 4,460 4,409 4,359*Batterytechnologyquotedona$/kWhbasis

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Figure115 LevelisedCostofNewEntry(BAU&SES,$/MWh)

0

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100

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300

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2017

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Levelised

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fGen

eraw

on($

/MWh)

Hydro Wind Coal

Gas Bio Solar

CSP PV+Bazery[75%] HydroROR

Geothermal PumpStorage

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Table28 TechnologyCostsAssumptionsforASESScenario

TechnologyCapitalCost(Unit:Real2014USD/kW)Technology 2015 2030 2040 2050GenericCoal 2,492 2,462 2,450 2,437CoalwithCCS 5,756 4,893 4,605 4,334CCGT 942 930 926 921GT 778 768 764 761WindOnshore 1,450 1,240 1,175 1,113WindOffshore 2,900 2,480 2,349 2,225HydroLarge 2,100 2,275 2,350 2,427HydroSmall 2,300 2,400 2,450 2,501PumpedStorage 3,340 3,618 3,738 3,861PVNoTracking 2,243 1,050 850 688PVwithTracking 2,630 1,231 997 807PVThinFilm 1,523 1,131 1,086 1,043BatteryStorage-Small 600 338 300 267Battery-UtilityScale 500 213 200 188Solar Thermal withStorage

8,513 4,750 4,000 3,368

Solar Thermal NoStorage

5,226 3,937 3,703 3,483

Biomass 1,800 1,745 1,725 1,705Geothermal 4,216 4,216 4,216 4,216Wave 9,887 7,188 5,875 4,802Biogas(AD) 4,548 4,359 4,309 4,259*Batterytechnologyquotedona$/kWhbasis

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Figure116 LevelisedCostofNewEntry(AES,$/MWh)

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/MWh)

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Gas Bio Solar

CSP PV+Bazery[75%] HydroROR

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AppendixB FuelPricesTable29setsouttheFreeonboard(FOB)fuelpriceassumptionsthatwereusedin themodellingpresented in this report. This fuel price setwas common to allthreescenarios.

Table29 FuelPriceAssumptions(Real2014USD/GJ)

Year Coal Gas Diesel Uranium FuelOil Biomass Biogas2015 2.39 10.08 13.34 0.72 9.13 2.57 1.002016 2.51 11.88 15.24 0.76 10.49 2.62 1.002017 2.63 12.91 15.28 0.80 11.68 2.67 1.002018 2.74 13.72 16.41 0.80 12.43 2.72 1.002019 2.86 14.47 17.53 0.80 13.18 2.78 1.002020 2.98 15.16 18.64 0.80 13.93 2.83 1.002021 3.10 15.81 19.73 0.80 14.65 2.89 1.002022 3.21 16.46 20.80 0.80 15.36 2.95 1.002023 3.33 17.10 21.86 0.80 16.06 3.01 1.002024 3.45 17.72 22.90 0.80 16.76 3.07 1.002025 3.56 18.34 23.93 0.80 17.44 3.13 1.002026 3.56 18.29 23.86 0.80 17.39 3.19 1.002027 3.56 18.24 23.79 0.80 17.34 3.25 1.002028 3.56 18.19 23.72 0.80 17.29 3.32 1.002029 3.56 18.14 23.65 0.80 17.24 3.39 1.002030 3.56 18.09 23.58 0.80 17.19 3.45 1.002031 3.56 18.06 23.53 0.80 17.15 3.52 1.002032 3.56 18.02 23.49 0.80 17.12 3.59 1.002033 3.56 17.99 23.44 0.80 17.08 3.67 1.002034 3.56 17.96 23.40 0.80 17.05 3.74 1.002035 3.56 17.92 23.35 0.80 17.02 3.81 1.002036 3.56 17.89 23.30 0.80 16.98 3.89 1.002037 3.56 17.86 23.26 0.80 16.95 3.97 1.002038 3.56 17.83 23.21 0.80 16.92 4.05 1.002039 3.56 17.79 23.16 0.80 16.88 4.13 1.002040 3.56 17.76 23.12 0.80 16.85 4.21 1.002041 3.56 17.76 23.12 0.80 16.85 4.29 1.002042 3.56 17.76 23.12 0.80 16.85 4.38 1.002043 3.56 17.76 23.12 0.80 16.85 4.47 1.002044 3.56 17.76 23.12 0.80 16.85 4.56 1.002045 3.56 17.76 23.12 0.80 16.85 4.65 1.002046 3.56 17.76 23.12 0.80 16.85 4.74 1.002047 3.56 17.76 23.12 0.80 16.85 4.84 1.002048 3.56 17.76 23.12 0.80 16.85 4.93 1.002049 3.56 17.76 23.12 0.80 16.85 5.03 1.002050 3.56 17.76 23.12 0.80 16.85 5.13 1.00

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AppendixC MethodologyforJobsCreationThis section briefly summarises the methodology that we adopted for jobscreation.ThemethodologythatwehaveadoptedhasbeenbasedonanapproachdevelopedbytheInstituteforSustainableFuturesattheUniversityofTechnology,Sydney and used by the Climate Institute of Australia59. In essence the jobscreatedindifferenteconomicsectors(manufacturing,construction,operations&maintenance and fuel sourcing and management) can be determined by thefollowingwiththeinformationbasedonthenumbersprovidedinTable30.

Figure117 JobCreationCalculations

Wehaveappliedthismethodologytotheresultsineachscenariodiscussedinthisreportinordertomakeestimatesofthejobscreationimpactsandallowcomparisonstobemade60.

59Adescriptionofthemethodologycanbefoundinthefollowingreference:TheClimateInstitute,“CleanEnergyJobsinRegionalAustraliaMethodology”,2011,available:http://www.climateinstitute.org.au/verve/_resources/cleanenergyjobs_methodology.pdf.60Thepercentageoflocalmanufacturingandlocalfuelsupplyisassumedtobe1toreflectthetotaljobcreationpotential.

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Table30 EmploymentFactorsforDifferentTechnologies

Annualdeclineappliedtoemployment

multiplier

Constructio

ntim

e

Constructio

n

Man

ufacturin

g

Ope

ratio

ns&

mainten

ance

Fuel

Technology 2010-20 2020-30 years perMW perMW perMW perGWh

Blackcoal 0.5% 0.5% 5 6.2 1.5 0.2 0.04

(includeinO&M)

Browncoal 0.5% 0.5% 5 6.2 1.5 0.4

Gas 0.5% 0.5% 2 1.4 0.1 0.1 0.04

Hydro 0.2% 0.2% 5 3.0 3.5 0.2

Wind 0.5% 0.5% 2 2.5 12.5 0.2

Bioenergy 0.5% 0.5% 2 2.0 0.1 1.0

Geothermal 1.5% 0.5% 5 3.1 3.3 0.7

Solarthermalgeneration

1.5% 1.0% 5 6.0 4.0 0.3

SWH 1.0% 1.0% 1 10.9 3.0 0.0

PV 1.0% 1.0% 1 29.0 9.0 0.4

ies thailand power sector vision part 2

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