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INVESTMENT OPPORTUNITIESFORUTILITY-SCALESOLARAND

WINDAREAS

ELSALVADORZONINGASSESSMENT

©IRENA2024

Unlessotherwisestated,materialinthispublicationmaybefreelyused,shared,copied,reproduced,printedand/orstored,providedthatappropriateacknowledgementisgivenofIRENAasthesourceandcopyrightholder.Materialinthispublicationthatisattributedtothirdpartiesmaybesubjecttoseparatetermsofuseandrestrictions,andappropriatepermissionsfromthesethirdpartiesmayneedtobesecuredbeforeanyuseofsuchmaterial.

ISBN:978-92-9260-603-9

Citation:IRENA(2024),Investmentopportunitiesforutility-scalesolarandwindareas:ElSalvador,InternationalRenewableEnergyAgency,AbuDhabi.

AboutIRENA

TheInternationalRenewableEnergyAgency(IRENA)servesastheprincipalplatformforinternationalco-operation,acentreofexcellence,arepositoryofpolicy,technology,resourceandfinancialknowledge,andadriverofactiononthegroundtoadvancethetransformationoftheglobalenergysystem.Anintergovernmentalorganisationestablishedin2011,IRENApromotesthewidespreadadoptionandsustainableuseofallformsofrenewableenergy,includingbioenergy,geothermal,hydropower,ocean,solarandwindenergy,inthepursuitofsustainabledevelopment,energyaccess,energysecurityandlow-carboneconomicgrowthandprosperity.

Acknowledgements

IRENAwouldliketoacknowledgethedataprovidersfortheGlobalAtlasforRenewableEnergy,inparticulartheEnergySectorManagementAssistanceProgram(ESMAP)oftheWorldBank,theEuropeanCentreforMedium-RangeWeatherForecasts,theEuropeanSpaceAgency,theNationalAeronauticsandSpaceAdministration,theOakRidgeNationalLaboratory,theOpenStreetMapFoundation,Solargis,theTechnicalUniversityofDenmark,andtheUnitedNationsEnvironmentProgramme.ThemethodologyusedinthisstudyoriginatedfrompriorIRENAstudiesin2013and2016andhasbeenupdatedin2023.

IRENAwouldliketothankAidaAntonietaFloresAcosta,LuisCastaneda,VíctorSagastume,AdonayUrrutia,JuanCarlosGuevarafromtheGeneralDirectorateofEnergy,HydrocarbonsandMines(DGEHM);AnaMaríaOrellanafromtheExecutiveCommissionfortheLempaHydropower;SalvadorMontesfromtheOrganismodeInspecciónAcreditado(OIA);andIsaíasChafoyafromINVERLECSolarEnergy.

ThezoninganalysiswasconductedbySibghatUllahandMohammedNababaunderthesupervisionofImenGherboudjwhoauthoredthereport.

Contributingdevelopers:ImenGherboudj,MohammedNababa,JoelSilva(consultant),AbdulmalikOrichaAli(ex-IRENA),JacintoEstima(ex-IRENA),GeraldChamKpu(ex-IRENA)andSibghatUllah.

Furtheracknowledgement:JoseToron,CamiloRamirezIsaza,NatalieLedanois(consultant),RaghadElSalah(ex-IRENA)andSujanAdhikari.

TechnicalreviewwasprovidedbyPaulKomor.PublicationsandeditorialsupportwereprovidedbyFrancisFieldandStephanieClarke.ThereportwaseditedbyJonGorvett,withdesignprovidedbyPhoneixDesignAid.

Reportavailablefordownload:

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Disclaimer

Thedesignationsemployedandthepresentationofmaterialsfeaturedhereinareprovidedonan“asis”basisforinformationalpurposesonly,withoutanyconditions,warrantiesorundertakings,eitherexpressorimplied,fromIRENA,itsofficialsandagents,includingbutnotlimitedtowarrantiesofaccuracy,completenessandfitnessforaparticularpurposeoruseofsuchcontent.TheinformationcontainedhereindoesnotnecessarilyrepresenttheviewsofallMembersofIRENA,norisitanendorsementofanyproject,productorserviceprovider.ThedesignationsemployedandthepresentationofmaterialhereindonotimplytheexpressionofanyopiniononthepartofIRENAconcerningthelegalstatusofanyregion,country,territory,cityorareaorofitsauthorities,orconcerningthedelimitationoffrontiersorboundaries.

ELSALVADORZONINGASSESSMENT

CONTENTS

ABBREVIATIONS 5

EXECUTIVESUMMARY 6

1.INTRODUCTION 8

2.THEZONINGASSESSMENT 10

2.1.Definingtheassessmentcriteria 10

2.2.Mappingthesuitabilityindex 13

2.3.Clusteringofsuitableareas 16

2.4.Calculatingtechno-economicattributes 17

2.5.Identifyingfavourablezones 18

3.DATASCOPEANDQUALITY 19

3.1.Solarresourcedata 19

3.2.Windresourcedata 20

3.3.Meteorologicaldata 21

3.4.Topography 22

3.5.Populationdistribution 22

3.6.Transmissionlinenetwork 23

3.7.Roadnetwork 23

3.8.Protectedareas 24

3.9.Landcover 25

3.10.Ancillarydatasets 26

4.ASSESSMENTRESULTS 27

4.1.Favourablezones 27

4.2.Techno-economicattributes 28

5.CONCLUSION 36

REFERENCES 37

|3

INVESTMENTOPPORTUNITIESFORUTILITY-SCALESOLARANDWINDAREAS

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FIGURES

Figure1Zoningassessmentmethod 10

Figure2Suitabilityassessmentmethod 14

Figure3AverageannualglobalhorizontalsolarIrradiationinElSalvador 20

Figure4AnnualaveragewindspeedinElSalvador 21

Figure5TopographyofElSalvador 22

Figure6ElSalvador’stransmissionlinenetwork 23

Figure7ElSalvador’sroadnetwork 24

Figure8ProtectedareasinElSalvador 25

Figure9LandcoverinElSalvador 26

Figure10Landsuitabilityindexwiththemostpromisingzonesforutility-scalesolarPVprojects 27

Figure11Landsuitabilityindexwiththemostpromisingzonesforutility-scaleonshorewindprojects.28

Figure12Capacityfactorsofthemostpromisingzonesforutility-scalesolarPVprojects 29

Figure13Capacityfactorsofthemostpromisingzonesforutility-scaleonshorewindprojects 30

Figure14LCOEofthemostpromisingzonesforutility-scalesolarPVprojects 30

Figure15LCOEofthemostpromisingzonesforutility-scaleonshorewindprojects 31

Figure16Distanceofthemostpromisingzonesforutility-scalesolarPVprojectstothenearest

transmissionlines 31

Figure17Distanceofthemostpromisingzonesforutility-scaleonshorewindprojectstothe

nearesttransmissionlines 32

Figure18Maximumdevelopmentpotentialforutility-scalesolarPVandonshorewindprojects

perregion 32

Figure19Cumulativesolarandwindpotentialvs.zonalcapacityrange 33

TABLES

Table1SuitabilityassessmentapproachforsolarPVandwindprojects:Scoringsystem,lower

andupperthresholds,andassignedweightsforeachcriterion 16

Table2Assumptionsontechnicalparametersforzoningassessment 17

Table3Technologyspecificationsandinfrastructurecosts 17

Table4Zoningassessmentrequirementsandresults 34

BOXES

Box1TheGlobalAtlasforRenewableEnergyInitiative 9

Box2Thetypicalmeteorologicalyear 13

ELSALVADORZONINGASSESSMENT

|5

ABBREVIATIONS

AC

alternativecurrent

IUCN

InternationalUnionforConservationof

Ah

amperehours

Nature

AHP

analytichierarchyprocess

JICA

JapanInternationalCooperationAgency

CF

capacityfactor

km

kilometre

C-FDDA

climatefour-dimensionaldata

km2

squarekilometre

assimilation

kWh

kilowatthour

CFSR

climateforecastingsystemreanalysis

kWh/m2

kilowatthourspersquaremetre

CNE

NationalEnergyCouncil

LBNL

LawrenceBerkeleyNational

CSP

concentratedsolarpower

Laboratory

DC

directcurrent

LCOE

levelisedcostofenergy

DGEHM

GeneralDirectorateofEnergy,

m

metre

HydrocarbonsandMines

m2

squaremetre

DHI

diffusehorizontalirradiation

m/s

metrespersecond

DNI

directnormalirradiation

MERRA-2

Modern-EraRetrospectiveAnalysisfor

DTU

TechnicalUniversityofDenmark

ResearchandApplications,Version2

ECMWF

EuropeanCentreforMedium-Range

MCC

maximumconcentrationcapacity

WeatherForecasts

MCDM

multi-criteriadecisionmaking

EFC

equivalentfirmcapacity

MW

megawatt

ELCC

effectiveloadcarryingcapability

MWh

megawatthour

ERA-5

EuropeanCentreforMedium-

MW/km2

megawattpersquarekilometre

RangeWeatherForecasts(ECMWF)Reanalysis5th

NASA

NationalAeronauticsandSpaceAdministration

ESA

EuropeanSpaceAgency

ORNL

OakRidgeNationalLaboratory

ESMAP

EnergySectorManagementAssistanceProgram

OSM

OpenStreetMap

EUMETSATEuropeanOrganisationforthe

PV

photovoltaic

ExploitationofMeteorologicalSatellites

RRA

RenewableReadinessAssessment

FSFinkelstein-Schafer

SAR

syntheticapertureradar

GADMGlobalAdministrativeAreas

SAW

simpleadditiveweighting

GCCGulfCo-operationCouncil

SODA

solarradiationdata

GEOSGoddardEarthObservingSystem

SRTM

ShuttleRadarTopographyMission

GHIglobalhorizontalirradiation

TMY

typicalmeteorologicalyear

GISgeographicinformationsystem

UAE

UnitedArabEmirates

GMAOGlobalModellingandAssimilationOffice

UNEP

UnitedNationsEnvironmentProgramme

GWGigawatt

USD

UnitedStatesdollar

GWAGlobalWindAtlas

WAsP

WindAtlasAnalysisandApplication

IECInternationalElectrotechnical

Program

Commission

WDPA

WorldDatabaseforProtectedAreas

IRENAInternationalRenewableEnergyAgency

WCMC

WorldConservationMonitoringCentre

INVESTMENTOPPORTUNITIESFORUTILITY-SCALESOLARANDWINDAREAS

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3

4

EXECUTIVESUMMARY

ThisreportsummarisesresultsfromananalysisconductedbyIRENAtomapthosezonesacrossElSalvadorthatarehighlyattractivewhenitcomestoinvestmentinthedeploymentofutility-scalesolarphotovoltaic(PV)andonshorewindprojects,whilealsomappingthosezones’correspondingtechno-economicparameters.

Thestudyaimsto:i)providespatialinformationonrenewableenergypotential,alongwithinsightsintothecountry’stotaldevelopmentpotentialwhenitcomestoadoptingsolarPVandonshorewindpower;ii)informnationalinfrastructureplanningacrosstheelectricitysupplyvaluechain,spanninggeneration,transmission,anddistribution;andiii)providecriticalinputforhigh-levelpolicymodelsthataimtoensureuniversalelectricitysupplyandsupportthelong-termabatementofclimatechange.

Thisanalysishasbeenconductedviaarigorousandinteractiveprocess,involvingofficialrepresentativesfromtheGeneralDirectorateofEnergy,HydrocarbonsandMines(DGEHM),inordertogivedueconsiderationtothelocalcontext.Theanalysisreliesonhigh-qualityresourceandmeteorologicaldata(bothannualaverageandhourly),whilealsotakingintoaccountancillarydataonlocalpopulationdensity,protectedareas,topography,landuse,powertransmissionlinenetworks,roadnetworks,costs(capitalandoperational)andtechnologicalparameters.Thesecriteriahavebeenadaptedtothecountry-specificrenewableenergystrategy,thusallowingtheidentificationofthezonesmostpromisingforprioritisationintherenewabledeploymentplan.

Thezoningapproachforautility-scalerenewableenergyprojectdevelopmentconsistsoffourmainsteps:

Anassessmentismadeofthe

technicalrenewableenergypotential

ofeverysquarekilometre(km2)ofa

countryorregion,basedonselected

criteria.Thesecriteriaare:resource

quality;transmissionlinenetworks;

roadnetworks;topography;

protectedareas;populationdensity;

Thecapacityfactor,energy

output,levelisedcostofenergy

(LCOE)andotherfactorsare

calculated.Theseexpressthe

capabilityofeachzone,from

thetechnicalandeconomic

perspectives,tohostsolarPVor

onshorewindprojects.

andlandcover.

1

CALCULATING

IDENTIFYING

FAVOURABLE

ZONES

MAPPING

CLUSTERINGZONES

TECHNO-

THESUITABILITY

ECONOMIC

INDEX

ATTRIBUTES

2

Highlysuitablecontiguouscells

aregroupedintodefinitive

zones(orclusters)basedona

definedcut-offsuitabilityscore

andonthemaximumcapacity

ofeachzone.

Themostpromisingzonestobe

prioritisedinordertoenablethe

bestinvestmentenvironment

areselectedbyevaluatingand

analysingthecalculatedzone

attributes.

ELSALVADORZONINGASSESSMENT

|7

ThisstudyfindsthatasignificantportionofElSalvador’slandareaishighlysuitableforsolarPVandonshorewinddevelopment.However,themostpromisingzonestoprioritiseintherenewabledeploymentplanareconcentratedalongexistingandplannedtransmissionlinesandroadnetworks.

ONSHOREWIND

Maximumdevelopmentpotential:

0.24GW

Installation

density

of:

Maximum

concentrationcapacitiesof:

Land

utilisation

factorof:

15

5000

50%

MW/km2

MWperzone

Thestudysuggestsamaximumdevelopmentpotentialofapproximately12.2gigawatts(GW)forsolarPVand0.24GWforonshorewindprojects.Thistakesintoconsiderationinstallationdensityof100megawattspersquarekilometre(MW/km2)and15MW/km2forsolarPVandonshorewind,respectively,alongwithmaximumconcentrationcapacitiesof5000MWperzoneforbothsolarPVandonshorewind,givenalandutilisationfactorof50%.Theutilisationfactorwasdeterminedbasedonthepremisethatnotallofthesuitableareaiseligibleforpowerproductionduetocompetinglanduses,suchasagricultureandheritageprotection;thisisexploredfurtherinsection2.

Installation

density

of:

Maximum

concentrationcapacitiesof:

Land

utilisation

factorof:

100

5000

50%

MW/km2

MWperzone

Maximumdevelopmentpotential:

12.2GW

SOLARPV

Thesefindingsareintendedtopromptfurtheractioninidentifyingspecificsitesforanin-depthassessmentusinghighresolutionspatialandtemporaldata.Thelimitationsofthisstudymustalsobetakenintoaccount,however,specificallyintermsofthesensitivityoftheresultsbothtotheassumptionsmadeinsettingthethresholdsforeachcriterionandtotheunderlyingqualityofthedatasets.Non-technicalissues,suchaslandownership,mayalsoinfluencetheselectionofareastoconsiderforfurtherevaluation.

PotentialsiteswithintheseareascouldbenefitfromthesiteassessmentserviceoftheInternationalRenewableEnergyAgency(IRENA).Thisserviceoffersapre-feasibilityassessmentthatdeterminesthetechnicalandfinancialviabilityofsitesforsolarPVandwindprojectdevelopment.Inthis,itusesdownscaledtimeseriesresourcedata,sitespecificcharacteristics,technology-specificparametersandrepresentativeprojectcostdata.

INVESTMENTOPPORTUNITIESFORUTILITY-SCALESOLARANDWINDAREAS

8|

1.INTRODUCTION

ThisstudywascarriedoutattherequestofthegovernmentofElSalvador.ItisanextensionofthesupporttheInternationalRenewableEnergyAgency(IRENA)providedthroughtheRenewableEnergyReadinessAssessment(RRA)processsince2020(IRENA,2020).

Thestudy–azoningassessment–allowszones(orclusters)thatarehighlyattractivetoinvestmentinrenewableprojectdevelopmenttobespatiallymapped,alongwiththeircorrespondingtechno-economicparameters.

SuchanassessmentcanassisttheDGEHMinidentifyingthebestzonesfornewutility-scalesolarphotovoltaic(PV)andonshorewinddevelopmentandforplanningtransmissionandgenerationexpansion.Italsohelpscreateleast-costenergymasterplans,whichcanreducetheriskofinvestinginrenewableprojectsandsecuresustainablesourcesofelectricitygeneration.

Thesecondsectionofthereportdescribesindetailthemethodology,theunderlyingassumptionsandtherequirementsforconductingazoningassessmentforutility-scalepowerplantdeployment.

Themethodologyforidentifyingthebestzonesforrenewableprojectsisbasedon:

i.Amappingofthetechnicalrenewableenergypotentialofeverysquarekilometreofland,basedonresourcequality,transmissionlinenetwork,roadnetwork,topography,protectedareas,populationdensityandlanduse.

ii.Theclusteringofzoneswithhightechnicalpotentialbasedonspecificassumptionsrelatedtothecut-offsuitabilityscore,maximumconcentrationcapacityandlandutilisationfactor.

iii.Thecalculationoftechno-economicparameterscharacterisingthezonesbasedonthetechnicalequipmentspecificationsandprojectcostestimates.

Thethirdsectionofthisreportexplainsthedatasourcesforeachcriterionandtheassumptionsusedtoprovideatailor-madeanalysisforthecountry.Itincludesspecificdetailson:thespatialandtemporalresolutions;theextentofvalidation;andtherecommendeduseforeachdataset,givenitsstrength.

Theresultsofthisstudyareincludedinthefourthsectionandconsistof:i)landtechnicalrenewableenergypotential(suitabilitymaps)forsolarPVandonshorewind;ii)zonesofhighinvestmentattractiveness,withtheirtechno-economicparameters,suchasinstalledcapacity,hourlyandannualenergygeneration,capacityfactor,levelisedcostofelectricity(LCOE),anddistancestoinfrastructuresuchasroadandtransmissionlines;andiii)thecountry’smaximumdevelopmentpotential.

Thereportconcludeswithasummaryofthekeyfindingsoftheassessmentandpresentsrecommendationsforusebylocalauthorities.

ELSALVADORZONINGASSESSMENT

|9

Box1

TheGlobalAtlasforRenewableEnergyInitiative

TheGlobalAtlasforRenewableEnergyisaninitiativedevelopedbyIRENAinpartnershipwiththeCleanEnergyMinisterialMultilateralSolarandWindWorkingGrouptoadvancethedeploymentofrenewables.

Theinitiativeassistspolicymakers,projectdevelopers,investors,andtheglobalcommunitybyprovidingasingleonlinerepository,namelythe

GlobalAtlasplatform

,thatassemblesandcollatesover1000high-qualityrenewableresources(solar,wind,bioenergy,geothermal,hydropowerandmarine)andsupplementarydatasets(transmissionandroadnetwork,landcover,topographyandprotectedareas)tounderstandtherenewablepotentialinanyregionorcountry.Thesedatasetsserveasinputstothedevelopmentoftheonlinetoolsandcountry-levelanalyses,including:

•The

BioenergySimulator

,aweb-basedapplicationdevelopedtoestimatepotentialbioenergyandplanbioenergydevelopmentconsideringnumerouscombinationsofarea,biomassresource,technologyandend-use.Thesimulatoraimstoraiseawarenessonmodernbioenergyproductionoptionstohelpmeetglobalclimategoals,decarbonisetheworld’senergysystemandensureaccesstoaffordable,reliable,sustainableenergyforall.

•The

SolarCitySimulator

,aweb-basedapplicationdevelopedtoacceleratethedeploymentofrooftopsolarphotovoltaic(PV)systemsinselectedcities,suchasChongliinChina,UlaanbaatarinMongolia,PortLouisinMauritius,BurgunjinNepal,CastriesinSaintLucia,VictoriainSeychellesandKaseseinUganda.TheSimulatorassessesrooftopsolarPVpotential(electricityproduction,cashflowandsocio-environmentalbenefits)bytestingdifferentpolicyinstruments,incentiveschemesandinstallationscenariosthatcouldleadtopotentialeconomicsavingsandsocial-environmentalbenefits.

•Thezoningassessment,aGIS-basedmulticriteriaanalysisthatidentifiesthefavourablezoneswithinacountryfordevelopingutility-scalesolarPVorwindprojects.Themethodologycombineshighqualityresourcedatawithinfrastructureandlandfeaturesrelateddata–includingroadandtransmissionlinenetworks,topography,protectedareasandpopulationdensity–toidentifythezonesofhighdegreeoffeasibilitytodevelopsolarandonshorewindprojects.Thesezonesarefurthercharacterisedwithattributes,whichincludepotentialinstalledcapacity,hourlyenergygenerationprofiles,distancestotransmissionandroadinfrastructure,andlevelisedcostofelectricity(LCOE).Thisserviceaimstosupportcountriesindevelopingandimplementingtheirnationalenergymasterplan.

•Thesiteassessment,acost-effectivepre-feasibilityanalysisdevelopedtosupportcountriesinfindingeconomicallyviablesitesforsolar(photovoltaic,parabolictroughcollector,centralreceiversystemandlinearFresnel)andwindprojectdevelopment.Theservicereliesonsite-specificresourceprofiles,industrystandardenergyyieldandfinancialassessmentmethodologiestoestablisharangeoftariffsandlevelisedcostsofasiteforpotentialinvestmentongroundmeasurementsandsubsequentdevelopment.Throughthisservice,theAgencyhasassistedlocalauthorities-ministriesandpublicutilities-inseveralcountriesinAfrica,LatinAmericaandsmallislanddevelopingstates(SIDS),intheselectionandscreeningofmorethan140promisingsitesforsolarandwindpowerprojects.

INVESTMENTOPPORTUNITIESFORUTILITY-SCALESOLARANDWINDAREAS

10|

2.THEZONINGASSESSMENT

Zoningforutility-scalerenewableprojectsaimstodeliverarefinedmappingofdevelopmentpotentialatascalethatdelimitsthezonesofhighinvestmentattractiveness(orcost-effectiveness).Itdoesthisbyconsidering:highrenewableresourcepotential;proximitytothenecessaryinfrastructure;thecurrentfinancialcontext;andareaswheretherewouldbealowenvironmentalandsocialimpact.

Suchanassessmenthelpsauthoritiesmakegoodstrategicdecisionswhenplanninggenerationandtransmissionexpansion.Thiscanreducetherisksofinvestinginrenewableprojectsandsecuresustainablesourcesofelectricitygeneration.

Thezoningapproach(Figure1)consistsof:

i.definingtheassessmentcriteria;

ii.mappingthesuitabilityindexforprojectdevelopmentatthecountrylevel;

iii.clusteringsuitableadjacentareas;

iv.calculatingthetechno-economicattributesforeachzoneidentified;and

v.identifyingcost-effectivefavourablezones.

2.1.DEFININGTHEASSESSMENTCRITERIA

Azoninganalysisreliesonrenewableresourceandmeteorologicaldatasets,combinedwithtechno-economicandsocio-environmentalcriteria.

Figure1Zoningassessmentmethod

•Renewableresourceand

meteorologicaldata

•Techno-economiccriteria

•Socio-environmentalcriteria

•Highsuitabilityindex

•Maximuminstallable

capacity

•Minimumzonesize

•LowLCoE

•Highcapacityfactor

•Closebyroadandtransmissionlines

1

CALCULATING

DEFININGTHE

ASSESSMENT

ECONOMIC

CRITERIA

ATTRIBUTES

4

•Installedcapacity

MAPPINGTHE

SUITABILITY

INDEX

IDENTIFYING

FAVOURABLE

ZONES

•AGIS-basedmulti-criteriadecision

CLUSTERINGTHEZONES

THETECHNO-

5

3

2

making(MCDM)approach

•Pairwisecomparisonbetweencriteria

•Weightedlinearcombinationofcriteria

•Generationprofile

•Levelisedcostof

electricity(LCoE)

ELSALVADORZONINGASSESSMENT

|11

2.1.1.Renewableresourceandmeteorologicaldata

Renewableresourcedata,suchassolarirradiance,orwindspeedataspecificheight,alongwithmeteorologicaldata,providethemostimportantinformationneededinevaluatingthefeasibilityofhostingarenewableprojectinaparticularzone.Suchdatamakeitpossibletodeterminethedevelopmentcapacityandhourlygenerationprofilesofsuchprojects.

ThesolarirradiancecomponentaffectingtheoutputofPVcellsisglobalhorizontalirradiance.Thisiscommonlycalculatedusingeitherphysically-basedorstatistically-basedapproachesthatrequirehightemporalandspatialresolutionsatelliteorgroundmeasurements.

Thelong-termaverageannualglobalhorizontalirradiation(GHI)at1kmto3kmgridcellresolution–asgivenintheWorldBank’sGlobalSolarAtlasandTransvalor’sSODAsolardatasets,whichcovermorethan20yearsofhourlyhistoricaldata–areusedtoproducethefeasibilityindexforhostingarenewableproject.Inaddition,thehourlyhistoricalglobalhorizontalirradiancedataataround25kmgridcellresolution–asgivenintheModern-EraRetrospectiveAnalysisforResearchandApplicationsVersion2(MERRA-2)datasetdevelopedbytheNationalAeronauticsandSpaceAdministration(NASA)–areusedtocalculatethegenerationprofileofapotentialsolarPVpowerplant(seesection3.1).

Windspeeddataarecommonlyderivedusingweatherresearchandforecastingmodelsanddataassimilationtechniques.Theseareusedinordertoachievethemostrealisticdescriptionofweatheroccurrencesinwhatisknownas‘reanalysis’data.Thelong-termannualaveragewindspeedata1kmto3kmgridcellresolution,suchasthatgivenintheglobalwindatlasoftheTechnicalUniversityofDenmark(DTU)andinVortex’swindmaps,coverslong-termhourlyhistoricaldatasetsatdifferentheights.Thesedataareusedtoproducethefeasibilityindexforhostingrenewableprojects.Conversely,thehourlyhistoricalwinddataataround25kmgridcellresolution,suchasthatgivenbytheEuropeanCentreforMedium-RangeWeatherForecasts(ECMWF)Reanalysis5thModern-Era(ERA5),areusedtocalculatethegenerationprofilefromwindpowerplants(seesection3.2).

Othermeteorologicaldataarealsocommonlyderivedusingweatherresearchandforecastingmodelsanddataassimilationtechniquestoproducereanalysisdata.Thesedata,suchasthehistoricallong-termairtemperatureandpressurerecordedintheMERRA-2andERA5reanalysisdatasets,areimportanttocalculatethehourlyandannualpotentialenergygenerationofarenewableprojectsite(seesection2.4).Suchevaluationiscommonlyconductedconsideringtypicalmeteorologicalyear(TMY)data,whichrepresentthemostfrequentweatherconditionsatagivenlocation(Capacity4dev,EU,2011)(seesection3.3).

2.1.2.Techno-economiccriteria

Techno-economiccriteriaareofgreatimportanceinestimatingthefeasibilityofhostingarenewableprojectinagivenareaandforcalculatingthehourlygenerationprofilesofthezonesidentified.Thesecriteriainclude:landfeatures;slopeandelevation;infrastructure,suchastransmissionlinesandroadnetworks;land-useconstraints,suchasthesuitabilitycut-offvalue,themaximumconcentrationcapacity,installationdensityandthelandutilisationfactor;renewableequipmentspecifications;andprojectcosts.

•Thelandelevationandslopehaveaninfluenceontheequipmentinstallation.Areaswithsteepslopesandhighelevationsposechallengesintermsofsiteaccessforconstructionandmaintenance,whichincreasesthecosts.Thecharacteristicsoftheseareasalsoaffectthemountingoftheequipment,oftenleadingtopoorresourceextraction.Theelevationisderivedfromstereoimagepairsusingsoftphotogrammetry,orfromradardatausingsyntheticapertureradar(SAR)interferometrymethodology.Slope,meanwhile,isderiveddirectlyfromelevation.

INVESTMENTOPPORTUNITIESFORUTILITY-SCALESOLARANDWINDAREAS

12|

•Proximitytoexistingorplannedinfrastructu

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