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SETIS
SETIS magazineNo. 13 – November 2016
Energy SystemsModelling
10001001000100110101000101110100111010100101101000001000100010010001001101010001011101
ISSN 2467-382X
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Contents
4. EditorialbyJanNill,PolicyOfficeratDirectorate-GeneralforClimateAction
5. SET-Plan Update
8. DavidConnolly,coordinatoroftheH2020project“HeatRoadmapEurope", talks to SETIS
11. TheEUReferenceScenario2016
15. MarcOliverBettzüge,directoroftheInstituteofEnergyEconomicsattheUniversity ofCologne(ewi),talkstoSETIS
17. Abetterlifewithahealthyplanet:pathwaystonet-zeroemissions
20. AlistairBuckley,co-authorof‘AreviewofenergysystemsmodelsintheUK: Prevalentusageandcategorisation’talkstoSETIS
22. Energysystemmodellingintheindustry:theEDFR&Dperspective
27. METIS:thenewshort-termenergysystemmodelexploredbytheDirectorate-General forEnergy
30. Theimportanceofopendataandsoftwareforenergyresearchandpolicyadvice
34. TheNordicETP2016
37. OSeMOSYS:opensourcesoftwareforenergymodelling
39. Sharedexperiencesinintegratedenergysystemsmodelling
42. MarkO’Malley,directoroftheInternationalInstituteforEnergySystemsIntegration, talks to SETIS
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Policy-makersneeduptodateinformation,meaningfulfiguresand
analysisontheimpactofpolicymeasures.Energysystemsmodelling
canprovidethemwithallofthis.ThisismyexperienceasaEuropean
Commissionpolicy-makerwhohasusedenergysystemmodelling
forsevenyears.Atleastthreemodellingchallengesremain:energy
marketchanges,modelcombinationsandtransparency.
Up to date information: Energy system modelling needs to be
basedonthelatesttrendsand,unlikemacromodelling,ithasthe
opportunitytobeinformedbyrecentdata.AnexampleistheEU
ReferenceScenario2016(seeCantonetal.),whichprojectsenergy,
transportandgreenhousegas(GHG)emissiontrendsto2050.
Meaningful figures:Minus40%in2030,60%in2040and80%in
2050.ThisistheEU'sGHGemissionreductionpathway(compared
to1990)derivedbyenergysystemandnon-CO2 emission modelling
fortheCommission'sLow-CarbonEconomyRoadmapin2011.Itisa
goodexampleofhowmodellinghasinformedpolicy-makersinsetting
theGHGtargetfortheEU's2030climateandenergyframework.
Policy impact analysisisthemostdifficulttask.Howtoappropri-
atelyreflectexistingpolicyinstrumentsandtheirinteractions?How
tosimplifytheessenceoffuturepoliciesforpolicyscenarios?Itis
herethatthe“system”componentofenergysystemmodellingis
mostimportant.Forexample,apossiblefuturecarbonpricetrajectory
resultingfromtheinterplayofthelegallydeterminedamountofEU
EmissionTradingSystemallowancesandthechangingconditions
ofenergysupplyanddemandcanonlybegeneratedbyamodel
whichcoversalltheseelements.
Three challenges:First,energymarketschangeprofoundly.Supply
actorshavemultipliedandelectricitymarketdynamicshavechanged
withthepolicy-leddiffusionofrenewables,whileinterconnectionsare
becomingmoreimportant.Thesetrendsaresettocontinueandwill
bereinforcedwiththeriseofenergystorageanddemandresponse.
Thisisachallengeinparticularforenergymodelsofwhichthebasic
structurehasoftenbeendevelopedintimesofpublicmonopoliesor
ofoligopolisticcompetitionoflargesuppliers.Second,interactions
betweentheenergysystemandotherpartsoftheeconomyare
ofincreasingpolicyrelevance.Thedebateonthesustainabilityof
theincreasinguseofbiomassisonlyoneexample.TheEU'sGHG
effort-sharingtargetscouldonlybeproperlyanalysedbycombining
energysystemmodelsandmodelswhichcovertheagriculture,
forestryandwastesectors.Howtobestoperatesuchcombinations
toensurerobustandtimelyanalysesremainsachallenge.Third,
despitesignificant improvements,combiningcomplexmodelling
withtransparencyremainsachallenge,andstakeholders’demands
areincreasinginthisrespect.
MycolleaguesandIlookforwardtoseeinghowexistingandnew
energysystemmodelsaddressthesechallengeswhilecontinuing
toprovidequantitativeinformationtopolicy-makersthatisupto
dateandpolicyrelevant.
By Dr Jan Nill, European Commission, Directorate-General Climate Action
Editorial
Dr Jan Nill works at the European Commission, Directo-
rate-General Climate Action. He has been responsible for
climate policy-related EU energy modelling from 2009 to
2016. Currently he works as policy officer in the unit CLIMA
C.2 Governance & Effort Sharing, mainly on the Effort Sharing
Regulation Proposal on binding annual emission reductions
by Member States from 2021 to 2030 and the monitoring
of energy and greenhouse gas projections. Jan holds a PhD
in economics from the University of Kassel.
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Energy System Modelling
•• Somebackgroundontheenergymodellingactivitiescarriedout
attheJointResearchCentre(JRC),theEuropeanCommission’s
scienceandknowledgeservice, isavailableattheEuropean
CommissionScienceHub,togetherwiththeresultingpublications
datingbackto2005.
•• In2013,theJointResearchCentrepublisheda reportonthe
JRC-EU-TIMESmodel:Assessingthelong-termroleoftheSET-
Planenergytechnologies.Themainobjectiveofthisreportwas
topresentthemaininputsandassumptionsusedintheJRC-
EU-TIMESmodel,developedbytwoformer1JRCinstitutes:the
InstituteforProspectiveTechnologicalStudies(IPTS)andthe
InstituteforEnergyandTransport(IET).Themodelisdesigned
toanalysetheroleofenergytechnologiesinmeetingEurope’s
energyandclimatechange-relatedpolicyobjectives.Itmodels
theuptakeanddeploymentoftechnologyanditsinteractionwith
theenergyinfrastructure,includingstorageoptions,inanenergy
systemsperspective.
•• InAugust2014theDirectorate-GeneralforEnergylauncheda
publictenderaimedatdevelopinganewtool,METIS,tomodelthe
Europeanenergysystem,properlycustomisedtotheEuropean
1 TheDGJRCisorganisedinDirectoratesasofJuly2016.
Commissionneeds.METIS isexpectedtoaccuratelysimulate
themainaspectsoftheEuropeanenergysystemandbecali-
bratedwithdatafromthecurrentEUenergysystem(coveringall
28MemberStates).TheEuropeanCommissionwillusethisto
exploreandanalysetheeffectsofdifferentpoliciesandtrends
attheregional,nationalandEuropeanlevelsbyrunningseveral
scenariosfordifferenttimehorizons.Themodellingeffortwill
focusmainlyontheelectricity,gasandheatsectors,bothfor
theshort-termandthemedium-tolong-term.Thecontractwas
awardedinDecember2014toaconsortiumledbyArtelys.
•• TheJRCorganisedanexpertworkshopon“Addressingflexibilityin
energysystemmodels”inDecember2014.Theobjectiveofthe
workshopwastogatherexpertsfrommodellingteamsdealing
withtheseproblemsfromdifferentperspectives,rangingfrom
energysystem-widetodetailedsectoralenergymodels,inorder
toshareandcomparemodellingapproachesandresults,and
identifygapsandpotentialsolutions.
•• Followingtheworkshopon“Addressingflexibilityinenergysys-
temmodels”,in2015theJRCpublishedareportonAddressing
flexibilityinenergysystemmodelsinwhichitsummarisedthe
presentationsandfindingsfromthe2014workshop.
•• Also in 2015, the JRC published the JRC-EU-TIMES report
SET-Plan UpdateThe European Strategic Energy Technology Plan (SET-Plan) aims to transform the way we produce and use energy in the EU, with the goal of achieving EU leadership in the development of technological solutions capable of delivering 2020 and 2050 energy and climate targets.
Energy system models allow us to understand the impact, and thus consider the ‘design', of changes in the energy system. This is increasingly important for an energy system in transition that should absorb increasing levels of intermittency whilst meeting the objectives of security, sustainability and competitiveness and placing the consumer at the centre. The following is a non-exhaustive chronological overview of some selected actions taken to support the development and use of energy system models in EU energy planning, in addition to a more general look at recent actions in support of the SET-Plan.
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BioenergypotentialsforEUandneighbouringcountries.This
reportwasthefirstinaseriesofreportsonlow-carbonenergy
technologiespotentials,andaddressedthequantificationofcur-
rentandfuturebiomasspotentialcontributiontodecarbonisation
pathwaysoftheenergysystem.Thedatasetsproducedare
inputintotheJRC-EU-TIMESmodeltoanalysethemaindrivers
offuturebiomassusewithintheenergysystems.
•• InApril2015,theEuropeanCommissionissuedacallfortenders
foraStudyontheMacroeconomicsofEnergyandClimatePol-
icies.Thismajorproject,awardedtoaconsortiumledbyCam-
bridge EconometricsandincludingE3Modelling and Trinomics
aspartners,iscurrentlyongoingandwillextendthecapability
oftwoglobalenergy-economy-environmentmodelstogivea
fuller impactassessmentofthepoliciesdesignedtopromote
energyefficiencyandthetransitiontoalow-carboneconomy.
Thetwomodelshavebeenchosentorepresenttwoverydiffer-
enttraditionsineconomics:post-Keynesianmacro-econometric
modelling(theE3MEmodel)andComputableGeneralEquilibrium
modelling(GEM-E3).
•• InDecember2015theExecutiveCommitteeoftheEuropean
EnergyResearchAlliance(EERA)agreedtolaunchaJointPro-
gramme on Energy Systems Integration(ESI).Asub-programme
onmodellingaimstodevelopintegratedenergysystemmodels
thatcapturethestrongphysical,economicandregulatoryinter-
actionsthatexistwithinenergysystemsandthatfullyutilise
increasingvolumesofdata.
•• InFebruary2016,theMEDEASprojecthelditskick-offmeeting.
FundedunderHorizon2020,thisprojectaimstouseopensource
softwaretodesignanewenergy-economymodelforthefuture
EUtransitiontoalow-carbonenergysystem.
•• OnJune30,2016theEU’sInnovationandNetworksExecutive
Agency(INEA)organisedaworkshoponEnergySystemModelling
withtheobjectiveofbringingtogetherthefourH2020projects
fundedunderthetopic“LCE21–2015:Modellingandanalysing
theenergysystem,itstransformationandimpacts”toidentify
possiblesynergiesand/oroverlaps.ApartfromMEDEASpro-
jecttheother3awardedprojectsoftheLCE21-callareREEEM,
REFLEX and SET-Nav.
•• InJuly2016,theECpublisheditslatesteditionoftheEURef-
erenceScenario2016,whichprojectsenergy, transportand
greenhousegasemissionstrends intheEUupto2050.The
ReferenceScenarioisaprojectionofwhereourcurrentsetof
policiescoupledwithmarkettrendsarelikelytolead.TheEUhas
setambitiousobjectivesfor2020,2030and2050onclimate
changeandenergy,sotheReferenceScenarioallowspolicy-mak-
erstoanalysethelong-termeconomic,energy,climatechange
andtransportoutlookbasedonthecurrentpolicyframework.
•• AlsoinJuly2016theJRCpublishedanewissueoftheGECO
2016:GlobalEnergyandClimateOutlook.RoadfromParis,which
examinestheeffectsongreenhousegasemissionsandenergy
marketsofareferencescenariowherecurrenttrendscontinue
beyond2020;oftwoscenarioswheretheIntendedNationally
DeterminedContributionshavebeenincluded;andofa2°Csce-
narioinlinewithkeepingglobalwarmingbelowthelimitsagreed
in internationalnegotiations.Thereportpresentsanupdated
versionofthemodellingworksupportedbytheEuropeanCom-
mission’sDirectorate-GeneralforClimateAction(DGCLIMA)in
theUNFCCCnegotiationsthatresultedintheParisAgreement
oftheCOP21inDecember2015.
•• InAugust2016,theJRCpublishedatechnicalreportlayingout
themodellingapproachthat is implementedinthePOTEnCIA
modelling tool (PolicyOrientedTool forEnergyandClimate
ChangeImpactAssessment).Thismodelwasdevelopedbythe
JRC’sformerInstituteforProspectiveTechnologicalStudies(IPTS)
toassesstheimpactsofalternativeenergyandclimatepolicies
ontheenergysector,underdifferenthypothesesaboutsurround-
ingconditionswithintheenergymarkets.
•• InSeptember2016, theJRC,DGRTDandtheUnitedStates
DepartmentofEnergyorganisedanexpertworkshopon“Under-
standingtheWater-EnergyNexus:IntegratedWaterandPower
SystemModelling”,whereapproximately70EuropeanandUSsci-
entistsfromacademia,governmentandindustryinvolvedinpower
systemmodellinggatheredinordertocompareandexchange
state-of-the-artmodellingmethodologiesandbestpractices,
identifyinggapsandpotentialsolutions.Thediscussionstookinto
accountmodellinganddata-relatedmethodologicalaspects,with
theirlimitationsanduncertainties,aswellaspossiblealternatives
tobeimplementedwithinpowersystemmodels.
General SET-Plan related news and activities from JRC/SETIS
•• TheJointResearchCentrepublishedanumberofreportsin2016.
InadditiontothereportscoveredinthelastSET-Planupdate,
theJRChaspublishedareporttitledMapping regional energy
interestsforS3P-Energy,themaingoalofwhichwastocarryout
afirstidentificationofregionswithcommonenergytechnology
interestsaccordingtotheirsmartspecialisationstrategies.
•• OnJuly202016,theCommissionpresentedasetofmeasures
toacceleratetheshifttolow-carbonemissionsinallsectorsof
theeconomyinEurope.ThepackagewillhelpMemberStates
prepareforthefutureandkeepEuropecompetitive.Itispartof
theEU’sstrategyforaresilientEnergyUnionwithaforward-look-
ingclimatepolicy.
•• TheEuropeanParliamentadoptedtheEUStrategyforHeating
and Coolingataplenarysessionon13September2016.The
resolutionrecognisesthehugeuntappedpotentialofusingrecov-
erableheatanddistrictheatingsystemsandthefactthat“50%
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ofthetotalEUheatdemandcanbesuppliedviadistrictheating”.
•• InhisStateoftheUnionAddressinSeptember2016,European
CommissionPresidentJean-ClaudeJunckerhighlightedthat
smarterenergyusecombinedwithambitiousclimateactionis
creatingnewjobsandgrowthinEuropeandisthebestinvest-
mentinEurope’sfutureandinthemodernisationoftheEuropean
economy.
•• InthecontextoftheprocesstowardsaSET-PlanIntegrated
RoadmapandActionPlan,organisations(universities,research
institutes, companies, public institutions and associations)
involvedinresearchandinnovationactivitiesintheenergyfield
are invitedtoregister intheEuropeanenergyR&I landscape
database,whichaimsatfacilitatingpartnershipsandcollabo-
rationacrossEurope.Registrationisopentostakeholdersfrom
theEUandH2020associatedcountries.Organisationsareable
toindicatetheirareaofactivityaccordingtotheenergysystem
challengesandthemes,as identified intheSET-Plan process
towardsanIntegratedRoadmapandActionPlan.Thedatabase
ispubliclyavailableontheSETISwebsite.
•• DuringthelastSET-PlanSteeringGroup meeting in September,
fouragreementsonstrategictargetsandprioritieswereendorsed
bytheSET-PlanSteeringGroupandrelevantstakeholders.The
agreedDeclarationsofIntentconcerntheKeyActions1&2,and
9and10oftheIntegratedSET-PlandedicatedtoEurope“Being
n°1inrenewables”regardingoceananddeepgeothermalenergy,
“Renewingeffortstodemonstratecarboncaptureandstorage
(CCS)intheEUanddevelopingsustainablesolutionsforcarbon
captureanduse(CCU)”and“Maintainingahighlevelofsafety
ofnuclearreactorsandassociatedfuelcyclesduringoperation
anddecommissioning,whileimprovingtheirefficiency”.Themost
recentSteeringGroupmeetingtookplaceinBrusselsOctober19.
•• The9thSET-PlanConference ‘EnergyUnion:towardsatrans-
formed European energy system with the new, integrated
Research,InnovationandCompetitivenessStrategy’ istotake
placeinBratislava,Slovakiaon30November-2December2016.
•• TwoJRC-organisedside-eventsaretobeheldinthemarginsof
theSET-PlanConference.Thefirstisaworkshoptopresentthe
recentfindingsandinputsofSETIStotheStateoftheEnergy
Union reportanditsaddedvaluefortheoverallprogressofEU
innovationintheenergysector.Thisworkshopwillalsopresent
theTechnologyInnovationMonitoring(TIM)tooldevelopedby
theJRC.ThesecondworkshopwilldealwithFundinginnovative
low-carbonenergydemonstrationprojectsinthecontextofthe
NER300programme.
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What are the main insights that we aim to achieve through the development of energy system models?
Energysystemmodelshelpusunderstandtheimpactofmaking
changestotheenergysystembeforewemakethem.Theinsights
tendtovarysignificantlydependingonthetime-horizoninquestion.
Somemodelsfocusontheshort-term(yearsahead)sotheyusually
modelexistingtechnologieswithinexistingfinancialframeworks,
suchasamodelthatanalyseshowtodispatchapowerplanton
theelectricitymarketswehavetoday.Othermodelsfocusmoreon
thelong-term(decadesfromnow),sotheycanprovideinsightsfor
moreradicalchangestothetechnologies,institutions,andmarkets
wehavetoday.Forexample,thesemodelswilloftenincludewave
powerorpower-to-gas,bothofwhicharenotevencommercially
availablerightnow.EnergyPLANisprimarilydesignedtoanalysethe
large-scaleintegrationofrenewableenergyandenergyefficiency,
basedontheSmart Energy Systemsconcept.Renewableenergystill
providesarelativelysmallamountofourenergytoday,soanalysing
‘large-scaleintegration’requiresalong-termperspectiveovermany
decades.EnergyPLANisthereforefocusedonradicalchangesto
ourenergysystemcomparedtotoday,but italsosimulatesthe
energysystemonanhourlybasistoaccountforintermittencyfrom
renewableenergy.
Tell us a little about the EnergyPLAN model and its energy system analysis procedures.
EnergyPLANisprimarilyasimulationmodel,but italso includes
someoptimisation. Iwouldequatethe ‘user’ofEnergyPLANto
a‘designer’:theuserdesignsanenergysysteminEnergyPLANin
termsofdemands,capacities,efficiencies,andcostsandonceitis
complete,theusersimulateshowthatenergysystemperforms.
However,tocarryoutthesimulation,theusermustalso instruct
themodelhowto‘optimise’itsdecisionsduringeachhourofthe
simulation.Inotherwords,theoptimisationtellsthesimulationhow
tomakeitsdecisionsduringeachhouroftheyear.
ThemostcommonoptimisationweuseinEnergyPLANiscalledthe
‘technicaloptimisation’,wherethemainobjectiveistoreducethe
energyconsumedduringthesimulation.Alternatively,theusercan
usean ‘economicoptimisation’wherethemodelwill reducethe
costoftheenergysystemduringthesimulation.Itisimportantto
notethattheoptimisationonlyreferstotheoperationoftheenergy
systemduringeachhourandnottothe‘design’oftheenergysystem.
Inotherwords,thecapacityofwindturbinesinyourenergysystem
willnotbealteredduringtheeconomicoptimisation,buttheway
thosewindturbinesoperateeachhourmaybe.
DavidConnollyCoordinatoroftheH2020project“HeatRoadmapEurope”andoneofthedevelopers oftheEnergyPLANmodel
TALKS TO SETIS
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How does the EnergyPLAN model compare with other models; what are its distinguishing features?
IwoulddefineEnergyPLAN’snicheinthemixofmodelsthatcurrently
existas:itsimulatesallsectorsoftheenergysystemonanhourly
basisaftertheyhaveundergoneradicalchanges.Itcandothisdue
toacombinationofthefollowingkeycharacteristics:
•• Itcansimulateradicalchangesforrenewableenergyandenergy
efficiency,since itconsidersallmajortechnologiesthatexist
today(includingdistrictheating)aswellastechnologieswhich
arenotcommerciallyavailableyet,suchashydrogenproduction,
biomassgasification,carboncapture,andelectrofuels.
•• Themodelconsiderstheentireenergysystem,includingelec-
tricity,heating,cooling,industry,andtransport,sotheimpactof
changingtheheatsectorisreflectedintheothersectorsalso.
•• EnergyPLANisanhourlymodelsoitensuresthatdemandand
supplyarealwaysmetonhourlybasisacrosstheelectricity,
districtheating,andgasnetworks.
•• Itaccountsforsynergiesacrossallsectorsonanhourlybasis
whenintegratingrenewableenergy,whichisbasedontheSmart
Energy Systemconcept.Itisveryimportanttoconsiderthesesyn-
ergieswhenquantifyingtheimpactoffutureduetotheadditional
flexibilitythatthesesynergiescreateforintermittentrenewables
likewindandsolar.
How does the EnergyPLAN model contribute to the design of energy planning strategies?
Itquantifiestheimpactofimplementinglarge-scalepenetrationsof
renewableenergyandenergyefficiency,usuallyintermsofenergy,
emissions,andcosts.Byquantifyingtheimpact,wecanoftenreveal
thatsomedecisionsaremuchmoreorlesssignificantthanpolicy-
makersrealise.AverygoodexampleofthiscomesfromourHeat
RoadmapEuropework.Initially,policy-makersthoughtthatdistrict
heatingwasveryexpensive,especiallyduetotheconstructionof
thepipesinthestreets.However,byquantifyingthis,wehavebeen
abletodemonstratethatdistrictheatingischeaperthannatural
gasinmanycountries.Evenmoresurprising,duringthiscalculation
wefoundoutthatthepipesinthegroundareoneofthesmallest
costsforadistrictheatingscheme,eventhoughtheyarethemost
visiblesincetheyrequireconstructiononthestreets.This isvery
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importantforpolicy-makers:forexample,recentlywewereadvising
a localmunicipalityabouttherolloutofdistrictheating intheir
city.Theywerefocusingonthecostofthepipesinthestreetsince
theyassumedthiswouldhavethemost influenceontheoverall
economicviabilityoftheproject.However,afterquantifyingthe
breakdownofthecostforthem,theycouldseethatthepriceof
theheatsupplyhadamuchbiggerinfluencethanthepriceofthe
pipes,sowerecommendedthattheyfocustheireffortsonsecuring
alowandstableheatsupplyprice.Thisisaveryspecificexample,
butinmoststudiesEnergyPLANchangesperceptionslikethisona
broaderenergy-systemscale.Forexample,ithaspreviouslybeen
usedtodemonstratehow100%renewableenergysystemshave
comparablecoststofossil-fuelbasedenergysystems,whichcan
befoundat:www.SmartEnergySystem.eu.
A key objective of EnergyPLAN is to aid in the design of 100% renewable smart energy systems. How will it achieve this?
Ourresultstodateindicatethatthekeyto100%RenewableEnergy
andtheSmartEnergySystemsconceptisintegratingthevarious
sectors:electricity,heating,cooling,industry,andtransport.Historically
thesesectorshaveevolved individuallyfromoneanother:power
plantsproducingelectricity,boilerscreatingheat,andcombus-
tionenginesprovidingtransport.Weneedtoremovethis‘sectoral
approach’andmovetowardsan‘energysystem’approach,since
thiswillcreatemanynewopportunitiesforbothenergyefficiency
andrenewableenergyintegration.
Let’staketheelectricityandheatsectorsasanexample,sincemany
EUcountrieshavealreadystartedconnectingtheseinrecentdecades.
Ifthesesectorsaredesignedinisolationthenthepowerplantswill
onlyproduceelectricity,but ifthesetwosectorsaredesignedin
combinationwithoneanother,thenitisverylikelythatcombined
heatandpower(CHP)plantswillbemosteconomical.Apowerplant
hasanefficiencyof30-50%forelectricitygeneration,whereasaCHP
planthasanefficiencyof80-90%forelectricityandheatproduction
together.Hence,thereisoftenasignificantimprovementinenergy
efficiencybyreplacingapowerplantwithaCHPplant,something
wequantifiedforfiveEUcountriesintherecentSTRATEGOproject:
thesecountriesareCroatia,CzechRepublic,Italy,Romania,andthe
UnitedKingdom.
Similarly, ifwetrytooptimisetheintegrationofrenewableelec-
tricitywithasolefocusontheelectricitysector,thenwewilllimit
oursolutionstothosethatexistwithintheelectricitysectorsuchas
interconnection,demand-sidemanagement,batteries,andpumped
hydroelectricstorage.However,ifweoptimiseacrosstheelectricity
andheatsectorstogether,thenwewillbeabletousecheaper
alternativesforthe integrationofrenewableelectricitysuchas
heatpumpsandthermalstorage.WealreadyseethisinDenmark,
wherelarge-scaleelectricboilersareintegratingmorewindpower
viathermalonthedistrictheatingnetwork.Thisisoftenacheaper
solutionsincethermalstorageisapproximately100timescheaper
thanelectricitystorage,soweoftenuseEnergyPLANtoquantify
howmuchadditionalwindpowerwecanaccommodateduetothe
connectionbetweentheelectricityandheatsectors.
EnergyPLANalsoconnectscooling,industry,andtransportwiththe
electricityandheatsectorstoidentifysynergiesthatincreaseenergy
efficiencyandrenewableenergy.Byusingthissectoralapproach,
100%renewableenergysystemsbecomemoreeconomicallyviable
andthusmorelikelytobeimplemented.
How does your model accommodate new technologies and new research and development?
Wetrytoreleaseanewversionofthemodelevery6monthson
thewebsite.Updatesareverycloselylinkedtotheresearchprojects
thatweareinvolvedinandexistingtechnologieswithinEnergyPLAN
areregularlyupdatedifweidentifyanewconsiderationinoneof
theseprojects.Newtechnologiestendtobe includedovertime
ratherthanallatonce.Forexample,power-to-gasoriginallybegan
asanadditionalelectricitydemandforhydrogenproduction,butas
welearnedmoreaboutthetechnology, itevolvedintoindividual
componentsintheprocesssuchaselectrolysers,hydrogenstorage,
carboncapture&recycling,andbiomassgasification.
David ConnollyDavid Connolly is an Associate Professor in Energy Planning at Aalborg University in Copen-
hagen, Denmark. His research focuses on the design and assessment of 100% renewable
energy systems, with a key focus on the integration of intermittent renewables (such as
wind and solar power), district heating, electric vehicles, and the production of electrofuels/
synthetic fuels for transport.
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Approach
TheEuropeanCommission’spolicydecisionsareunderpinnedby
thoroughanalysesandimpactassessments.Whendevelopingand
implementingtheEnergyUnionStrategy,theCommissionusesa
widerangeofmathematicalmodelsandtoolstoexplorepolicy
proposalsandevaluatetheirpotentialenergy,transport,economic,
socialandenvironmentalconsequences.
TheEUReferenceScenarioisoneoftheEuropeanCommission’skey
analysistoolsusedinthecontextoftheEnergyUnion.Itisupdated
regularlyasitprojectstheimpactofcurrentEUpoliciesonenergy
andtransporttrendsaswellaschangesintheexpectedamount
ofgreenhousegasemissions.Itprovidesprojectionsonafive-year
periodupuntil2050fortheEUasawholeandforeachEUcountry.
Itisnotdesignedasaforecastofwhatislikelytohappeninthe
future. It ratherprovidesabenchmarkagainstwhichnewpolicy
proposalscanbeassessed.
On20July,theEuropeanCommissionpublisheditslatestReference
Scenario:theEUReferenceScenario2016(REF2016).Withtheactive
participationofnationalexpertsfromallEUcountries,theEuropean
Commissionworkedinpartnershipwithamodellingconsortiumled
bytheNationalTechnicalUniversityofAthenstodevelopREF2016,
makinguseofarangeofdifferentmodels.
Theprojectionsarebasedonasetofassumptions, includingon
populationgrowth,macroeconomicandoilpricedevelopments,
technology improvements,andpolicies.Regardingpolicies,pro-
jectionsshowtheimpactsofthefull implementationofexisting
legallybinding2020targetsandEUlegislation.Assuch,theyalso
showthecontinuedimpactpost2020ofpoliciessuchastheEU
EmissionsTradingSystemDirective(includingtheMarket Stability
Reserve),theEnergyPerformanceofBuildingsDirective,Regulations
on ecodesign and on CO2emissionstandardsforcarsandvans, as
wellastherecentlyrevisedF-gasRegulation.Suchpoliciesnotably
influencecurrentinvestmentdecisions,withimpactsonthestock
ofbuildings,equipmentandcars,whichhavelong-lastingeffects
post-2020onGHGemissionsorenergyconsumption.
TheEUReferenceScenario2016
12
S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Results
REF2016issetuptomeetthebindingenergy and climate targets
for2020,thelatterbeingachievedasaresultofexistingpolicies.
However,itshowsthatcurrentpoliciesandmarketconditionswill
deliverneithertheEU’s2030targetsnorthelong-term2050objective
of80to95%greenhousegas(GHG)emissionreductions.Overall
GHGemissionsdecreaseby26%in2020,35%in2030and48%
in2050.GHGemissionsfromsectorscoveredbytheEffortSharing
Decisionareprojectedtodecreaseby16%in2020andby24%
in2030below2005levels,lessthanemissionsinsectorscovered
bytheEU Emission Trading System.In2020,therenewableenergy
share(RES)ingrossfinalenergyconsumptionreaches21%,while
in2030itincreasesslightlyfurther,reaching24%.Inaddition,the
energyefficiency2020non-bindingtargetisnotmetinREF2016,the
scenarioprojectingareductioninprimaryenergysavings(relativeto
the2007baseline)of18%in2020,and,respectively,24%in2030.
The EU’s energy production is projected to continuetodecrease
fromaround760Mtoein2015toabout660Mtoein2050.The
projectedstrongdeclineinEUdomesticproductionforallfossilfuels
(coal,oilandgas)coupledwithalimiteddeclineinnuclearenergypro-
ductionispartlycompensatedbyanincreaseindomesticproduction
Figure 1: Projection of key policy indicators
712
16
2124
27 31
-18
-24
-7-15
-26-35
-42
-48
-80
-70
-60
-50
-40
-30
-20
-10
0
10
20
30
40
50
1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
RES share inGross FinalEnergyConsumption
Primary energysavingscompared to2007 baselineprojection(% change)
Total GHGemissions (%change to 1990)
ofrenewables.Biomassandbiowastewillcontinuetodominatethe
fuelmixofEUdomesticrenewableproduction,althoughtheshare
ofsolarandwindintherenewablemixwillgraduallyincrease.
The EU’s import dependencyshowsaslowly increasingtrend
overtheprojectedperiod,from53%in2010to58%in2050.RES
deployment,energyefficiencyimprovementsandnuclearproduction
(whichremainsstable)counteractsthestrongprojecteddecrease
intheEU’sfossilfuelproduction.
The EU power generation mixchangesconsiderablyoverthe
projectedperiodinfavourofrenewables.Before2020,thisoccurs
tothedetrimentofgas,asastrongRESpolicytomeet2020targets,
verylowcoalpricescomparedtogasprices,andlowCO2 prices do
nothelpgastoreplacecoal.After2020,thechangeischaracterised
byfurtherRESdeployment,basedonmarketconditions,butalsoa
largercoaltogasshift,drivenmainlyinanticipationofincreasing
CO2prices.VariableRES(solarandwind)reacharound19%oftotal
netelectricitygenerationin2020,25%in2030and36%in2050,
demonstratingthegrowingneedforflexibilityinthepowersystem.
Theshareofnucleardecreasesgraduallyovertheprojectedperiod
despitesomelifetimeextensionsandnewbuilt,from27%in2015
to22%in2030.
Source: PRIMES, GAINS
13
S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Primary energy demand andGDPcontinuetodecouple,whichis
consistentwiththetrendsobservedsince2005.Energyefficiency
improvementsaremainlydrivenbypolicyupto2020andbymarket/
technologytrendsafter2020.Withregardtothefuelmixinfinal
energydemand,thereisagradualpenetrationofelectricity(from
Figure 2: Evolution of final energy demand by fuel (Mtoe – above, shares – below)
20%intotalfinalenergyuse in2005to28%in2050).This is
becauseofgrowingelectricitydemandascomparedtootherfinal
energyuseandtosomeelectrificationofheating(heatpumps)and
toalimitedextentofthetransportsector.
Solids
Oil
Gas
Electricity
Heat (from CHPand DistrictHeating)
Other
0
200
400
600
800
1,000
1,200
1,400
2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
5%4%
20%
24%
42%
5%
10%
4%
22%
23%
36%
4%
10%
5%
25%
22%
35%
3%
11%
5%
27%
22%
34%
2%
11%
5%
28%
22%
32%
1%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2005 2020 2030 2040 2050
Source: PRIMES
14
S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Cristina MohoraCristina Mohora received a Master’s Degree in Financial and Monetary Policies from the Academy of Economic Studies in Bucharest and a PhD in Economic Modelling from Erasmus University Rotterdam. After holding an academic position at the Academy of Economic Studies in Bucharest and a research position at Université Libre de Bruxelles, she joined the European Commission in 2008. Between 2008 and 2010, Cristina has been involved in the energy system modelling work at the Directorate-General Energy and Transport. Since 2010 she has been responsible for the modelling work coordinated by the economic analysis unit of the Directorate-General Mobility and Transport.
Jan NillDr Jan Nill works at the European Commission, DG Climate Action. He has been one of the coordinators of the EU Reference Scenarios 2013 and 2016. Currently he works as policy officer in the unit CLIMA C.2 Governance & Effort Sharing. Jan holds a PhD in economics from the University of Kassel.
Joan Canton Joan Canton is an Economic Analyst at the European Commission’s Directorate-General for Energy, focusing on the modelling of energy systems, supporting the preparation of the Commission's Impact Assessments on climate and energy issues, as well as on monitoring the implementation of the Energy Union Strategy. Before working for DG Energy, he worked in DG Climate Action and in DG Economics and Financial Affairs. He holds a PhD in econom-ics from the University of Aix-Marseille and has worked as an Assistant Professor in the Economics Department of the University of Ottawa (Canada).
Investment expendituresforpowersupplyincreasesubstantially
until2020drivenbyREStargetsanddevelopments,butslowdown
thereafter,until2030,beforeincreasingagainfrom2030onwards
notablyduetoincreasingETScarbonpricesreflectingacontinuously
decreasingETScapbasedonthecurrentlinearfactor.Newpower
plantinvestmentisdominatedbyRES,notablysolarPVandwind
onshore.Investmentexpendituresindemandsectorsoverthepro-
jectedperiodwillbehigherthaninthepast.Theynotablypeakin
theshorttermupto2020,particularlyintheresidentialandtertiary
sectors,asaresultofenergyefficiencypolices.
Energy system costsincreaseupto2020.Largeinvestmentsare
undertaken,drivenbycurrentpoliciesandmeasures.Overall,in2020
energysystemcostsconstitute12.3%ofGDP,risingfrom11.2%
in2015,alsodrivenbyprojectedrisingfossilfuelprices2.Despite
furtherfossilfuelpriceincreases,between2020and2030theshare
remainsstableanddecreasesthereafter,asthesystemreapsbenefits
fromtheinvestmentsundertakeninthepreviousdecade(notably
viafuelsavings).Inthisperiod,theshareofenergysystemcostsin
GDPisgraduallydecreasing,reachinglevelscloseto2005by2050.
2 Totalsystemcostsincludetotalenergysystemcosts,costsrelatedtoprocess-CO2 abatement and non-CO2GHGabatement.
15
S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
distinctivefeatureofourmodellingapproachisthestrongemphasis
oneconomictheoryalongsideadeepunderstandingoftherelevant
technologies.Thus,theinsightsgeneratedfromourmodelsreveal
importantfindingsabouteconomicinterdependenciesandeffects
ontopofmeretechnology-basedanalysis.
How do you ensure the robustness of your simulation tools?
Robustness isensuredbyconsistency-checks,back-testingand
economicreview.Consistency-checksverifythatmodelresultsare
internallyconsistent,e.g.,energybalancesheetsarecorrect,notech-
nologicalboundariesareinfringedetc.Back-testingrunsthemodel
withhistoricaldata,whichisaviablewayforidentifyingpossible
shortfallsofthemodel.However,duetofundamentaldifficulties
withaccurateback-testing inacomplexenergyenvironment,we
alsoaddwhatwecall “economicreviewofthemodels”,namely
checkingmodelsandmodelresultswithrespecttotheirfitwith
economictheoryandobservedandforeseeablemarketbehaviour.
Tell us a little about ewi Energy Research & Scenarios and the work that you do.
ewiEnergyResearch&Scenariosisanon-profitorganizationfocus-
singonappliedeconomicresearchonenergymarketsandenergy
policy.Wehaveateamofabout35people,manyofthemsimul-
taneouslypursuingtheirPhDattheUniversityofCologne.Besides
conductingresearchprojects,wealsoofferresearchanddevelopment
supportaswellaseconomicadvicetogovernment,organisations
andcompanies.Thus,weregularlyprovidedecision-makerswith
soundquantitativesupportbasedonourstrongeconomicand
modellingexpertise.
What role do energy system models play in your research?
Energysystemmodelsareattheanalyticalcoreofourresearch.
Werun,andcontinuouslyimprove,modelsofglobalfuelmarkets
aswellastheEuropeanelectricity,gas,andheatmarkets.The
MarcOliverBettzügeDirectoroftheInstituteofEnergyEconomicsattheUniversityofCologne(ewi)andPresidentof theSupervisoryBoardofewiEnergyResearch&Scenarios.
TALKS TO SETIS
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
How can energy systems modelling contribute to a suc-cessful energy transition in Europe?
Energy systems models are important analytical tools to assess
potentialmarketdevelopments,includingtheirreactiontocertain
politicalmeasures.Hence,decision-makers intheenergydomain
mayusesuchmodelstoobtainamoreprofoundinformationbase
fortheirdecisionsandactions.Importantly,however, itshouldbe
stressedthatmodelstypicallygeneratescenarios–notforecasts.
Hence,itisimportantfordecision-makers,andthegeneralpublic,
toadequatelyinterpretthemeaningofscenariosbeforecomingto
conclusionsabouttheirimplications.Therefore,wehavedesigned
ourmodelsas“anti-blackboxes”,andwedevotealotoftimeand
efforttosupplyingtransparencyandinterpretationalongsideour
scenarioanalyses.
Marc Oliver BettzügeDr Marc Oliver Bettzüge has been a professor of economics, in particular energy economics, and Head of the Chair of Energy Economics - Department of Economics - at the University of Cologne since 2007. He is also Managing Director and Chairman of the Management Board of the Institute of Energy Economics at the University of Cologne (EWI). Professor Bettzüge has been a member of the German Parliament’s Study Commission on Growth, Wellbeing and Quality from 2011 to 2013. In addition he plays an active role in various committees and advisory boards.
What has your research revealed to be the most urgent issues facing the European energy system?
Thereisofcourseadifferencebetweenurgencyandimportance.From
aneconomicperspective,themosturgentissueinelectricityisthe
increasinggeographicimbalancebetweensupplyanddemandinthe
Europeanelectricitysystem,exacerbatedbyaratherslowexpansion
ofthegridandaninadequateconfigurationofbiddingzones.Forthe
gassupplysystem,ourmodelssuggestthaturgentdecisionsaround
Nord Stream 2havewide-rangingpoliticalramificationswhichshould
betransparentlytakenintoaccount.Withrespecttoimportance,our
modelsconsistentlyshowthattheinsufficientalignmentofEUand
nationalenergypoliciesleadstoinefficientandineffectiveoutcomes
withrespecttomitigatingCO2-emissionsinEurope.Thus,afunda-
mentaloverhaulofthepoliticalapproachtoenergyandclimatepolicy
wouldbeveryreasonablefromaneconomicperspective.
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Energy transitions are not new
Theworld’senergysystemisenteringamajortransition.Transitions
havehappenedbefore.Thenineteenthandtwentiethcenturiessaw
growthintheuseofcoal,andthenoilandnaturalgaswhenthe
moderncombustionenginetookoff.Butsincearoundthe1970s,
whilstthere’sbeenplentyofgrowthintheuseofenergy,themixof
fuelshasbeenrelativelystatic.Morerecently,withadditionalconcerns
overlocalandatmosphericemissions,theworldisseeingimpressive
ratesofgrowthinwindandsolarpower–aneweraoftransition.
Shell Scenarios help to navigate uncertainties about the future
Shellhasbeenusingscenarioplanningforover40yearstohelp
deepenitsstrategicthinking.Thescenarioshelpdecision-makers
toexplorethefeatures,uncertainties,andboundariesshapingthe
futurelandscape,andtoengagewithalternativepointsofview.
Ourscenariosconsiderlong-termtrendsineconomics,geopolitical
shiftsandsocialchangeaswellastechnologicalprogressand
theavailabilityofnaturalresources.Theyarebasedonplausible
assumptionsaboutfuturedevelopment,andincludetheimpactof
differentpatternsofindividualandcollectivechoices.
Shell’s Energy Scenarios are underpinned by quantitative modelling
Shell’sWorldEnergyModel(WEM)providesarigorousquantitative
frameworktounderpinthelogicofourscenarios.TogetherwithShell’s
GlobalSupplyModel,theWEMisacoretoolexploringalternative
evolutionsofenergydemandindifferentcountriesandindifferent
sectors,helpingtomaintainsystemconsistency,toexplorethemost
significantfactorsinpolicy,technologyandconsumerchoices,and
toexaminetheimpactsinonepartoftheworldmadebyshiftsin
another.
Shell’s latestScenariospublication,“ABetterLifewithaHealthy
Planet.PathwaystoNet-ZeroEmissions,”takesthemostoptimistic
featuresofour2013“NewLensScenarios”–MountainsandOceans
–andcombinesthemwithindividuallyplausiblefurthershiftsinpolicy,
technologydeployment,circumstances,andeventsthatmightmove
theworldontoanew,evenlower-emissiontrajectory,resultingin
net-zeroemissionsonatimescaleconsistentwithglobalaspirations.
Future energy demand will at least double
Thisworkstartsbyattemptingtoquantifythemagnitudeoffuture
energydemand.Asweconsiderthefuturedevelopmentofecono-
mies,andassumesignificantenergyefficiencyimprovements,we
estimatethatanaverageofabout28,000kWhofprimaryenergy
perpersonisapproximatelyrequiredtosupportthedecentquality
oflifetowhichpeoplenaturallyaspire.
Andifweassumeafuturepopulationofaround10billionpeopleby
theendofthecentury,andmultiplyitby28,000kWhpercapita,we
seethattheglobalenergyneedwouldbeabout280trillionkWha
year–roughlytwicethesizeofthecurrentenergysystem.
Abetterlifewithahealthyplanet:pathwaystonet-zeroemissions
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Fossil Approximately 50% electrification of end use.With Carbon Capture and Storage
EmergingNet-ZeroEmissionsWorld
2015
Hydrocarbons alongside renewables
Acrosstheenergysystem,it’slikelythatdifferentdegreesofdecar-
bonisationandenergyefficiencywillbeachievedatdifferentpaces,
indifferentplaces,andindifferentsectorsoftheeconomy.
Toarresttheaccumulationofgreenhousegasesintheatmosphere,
theworldwilleventuallyneedtoseeoverallemissionstodropto
net-zero.Inanet-zeroemissionsworld3withadecentqualityoflife
enjoyedbythemajorityofthepopulation,renewableenergieswill
dominate,andtogetherwithnuclearcouldmakeaboutthreequar-
tersoftheenergysupplycarbonneutral.Butrenewablesprimarily
produceelectricity,whichcurrentlycountsforlessthanone-fifthof
energyuse.Theproductionofchemicalsandplasticswouldcontinue
torelyonfeedstockfromoilandgas,andwherehightemperatures
3 Aworldinwhichtheamountofcarbonreleasedisbalancedbyanequivalentamountsequesteredoroffset.
ordenseenergystoragearerequired–suchasinmanyindustrial
processeslike iron/steel/cementmanufactureorheavyfreightor
airtransport,wewillseethecontinuedneedforhydrocarbonfuels.
Electrification is key for low CO2 and high efficiency
Inordertoachievebothlowemissionsandhighefficiency,theelec-
tricitymarketsharewillneedtogrowfromonefifthoftheenergy
consumedtoatleastahalf.Electrificationneedsbeparticularlyhigh
inhouseholdsandservicesectors,butneedstoextendfurtherinto
othersectorssuchasfoodprocessingandlightmanufacturing.For
passengertransport,hydrogenfuelcellandelectricdrivesshould
becomecommon,whileforaviation,shippingandfreighthydrocar-
bonswilllikelyremainimportant.
Foraworldwithwidespreadprosperity,theenergysystemwilldoubleoverthecourseofthis century.
ENERGYSOURCE GAS OIL COAL BIOENERGY NUCLEAR SOLAR WIND OTHER
2015 21% 31% 28% 11% 5% 0.5% 0.5% 3%
Net-Zero emissionsworld 9% 7% 9% 15% 8% 30% 12% 10%
Figure 3: Plausible energy mix in an emerging net-zero emissions world
Source: Shell analysis
19
S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Carbon Capture and Storage is indispensable
It’simportanttonotethatanet-zeroemissionsworldisnotneces-
sarilyaworldwithoutanyemissionsanywhere.It’saworldwhere
remainingemissionsareoffsetelsewhere inthesystem.Toboth
mopupremainingemissionsandprovideopportunitiesfor‘negative’
emissions,theworldwillneedwidespreaddeploymentofcarbon
captureandstorage(CCS).
Incentivising the transition
Achievinganet-zeroemissionsworldatpacewillrequiresignificant
developmentsinnewtechnologydeployment;industrial,agricultural
andurbanpractices;consumerbehaviour;andpolicyframeworks
whichshape,incentiviseormandatethesetransitions.Itwillalso
entailhighlevelsofcollaborationbetweenpolicymakers,businesses
andcivilsociety.
Governmentsneedtoprovidefinancialincentivesviacarbonprices
ortaxesforavoidingemissionsandremoveenergysubsidieswhere
theystillexist.Thisallowsthemarkettofindtheoptimalenergy
mixatlowestcosts.
Sensible measures for progress towards a net-zero emissions world
Analysingthelikelyevolutionofdemandacrosskeyareasofthe
economy,somethingofalogicalorder-of-priorityofactionsemerges:
1. Stimulatingefficiencymeasuresandextendingelectrification
acrosstheeconomywhereverandwheneverpossible;
2. Sustainingmomentumofrenewablesgrowth,particularlysolar
PVandwind,andmaximisingtheabilityofthegridtohandle
theirintermittency;
3. Acceleratingtheswitchfromcoaltogastoimmediatelyreduce
powersectoremissionswhileensuringsupplytomeetdemand
–awayofkeepingcumulativeemissionstoaminimumduring
thetransition;
4. Improvingbuildingsandcityinfrastructuretolowerenergyservice
demandsignificantly;
5. Acceleratinggovernment-directedeffortstopromotelow-carbon
technologiesandinfrastructures,includingnuclear,CCS,hydro-
gentransport, responsiblebioenergyandsustainableforestry,
agricultureandland-usepractices.
Concluding remarks
WehopethatourlatestScenariosworkwillhelpbuildsharedinsights
andperspectivesamongbusinesses,nationalgovernmentsandcivil
societymorebroadly.Asharedunderstandingwouldnotonlyaccel-
eratethenear-termactionstoreduceCO2emissions,butalsothe
deeperstructuraltransformationsrequiredtosustaindecarbonisation
andeconomicgrowthinthelongerterm.
Formoreinformationvisit:www.shell.com/scenarios
Note: Shell Scenarios are part of an ongoing process used in Shell for
40 years to challenge executives on the future business environment.
We base them on plausible assumptions and quantification, and
they are designed to stretch management to consider even events
that may be only remotely possible. Scenarios, therefore, are not
intended to be predictions of likely future events or outcomes and
investors should not rely on them when making an investment
decision with regard to Royal Dutch Shell plc securities. While we
seek to enhance our operations’ average energy intensity through
both the development of new projects and divestments, we have
no immediate plans to move to a net-zero emissions portfolio over
our investment horizon of 10-20 years.
Wim ThomasWim Thomas is Shell’s Chief Energy Advisor and also leads the Energy Analysis Team in Shell’s Global Scenario Group. He has been with Shell for over 30 years. Wim is also Chairman of World Petroleum Council UK National Committee, a Distinguished Fellow of the Institute of Energy Economics Japan, and a former chairman of the British Institute of Energy Eco-nomics in 2005. He holds a postgraduate degree in Maritime Technology, Delft University, the Netherlands.
20
What are the main insights that we aim to achieve through the development of energy systems models?
Inthepast,themainuseofacademicandpolicy-ledenergymodels
wastounderstandtheflowsoftraditionalenergyresourcesinthe
contextsofvalueformoneyandsecurityofsupply.Morerecently,the
emphasisofacademicmodellinghasbeentounderstandlow-car-
bonenergytransitionsand,indoingthis,themodelsneedtolook
muchfurtherintothefutureandtryandpredicthowthesystemwill
evolveandwhatconsequencessuchanevolutionwillhave.However
Ithinkthattherealchallengewhenwedevelopmodelsistounder-
standwhotheintendedaudienceisandwhetherthataudienceis
listening.Fromanacademicpointofview,theendgoalistypically
togetyourmodelusedinapolicycontext.However,policy-makers
oftentypicallyhavealreadyinvestedintheirownmodelsand,as
wefoundasaspillerfromourresearch,intermsofgettingused,
thelanguage,cultureandaddedvalueofamodelisasimportant
asthetechnicalaccuracyorscope.
How do these models help to balance uncertainty in the energy system?
Wereviewedarangeofacademicandpolicymodelsofenergy
systemsbut,intermsofbalancinguncertaintyintheenergysystem,
akeyinteractionistheuseofarangeofdifferentmodelsbysystem
operators.Shorttermenergysecurityneedstobenegotiatedalong-
sidethetransitiontoamoresustainableenergysystem,sohighly
accurateandnumericaloperationalmodelsneedtobeinconversa-
tionwithfuturescenario-basedmodels.IntheUK,theNationalGrid
“GoneGreen”scenariomodelisagoodexampleofhowthisisdone
AlistairBuckleyco-authorof‘AreviewofenergysystemsmodelsintheUK:Prevalentusageandcategorisation’
TALKS TO SETIS
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
inpractice.“GoneGreen”sitsattheinterfacebetweenthesystem
operatorNationalGridandtheirday-to-dayoperationalmodelling,
withpolicy-ledtransitionalmodelsheldbytheUKgovernment
energydepartment(nowaspartofthedepartmentforBusiness,
EnergyandIndustrialStrategy)andacademicenergymodels.Itis
citedformallyandinformallyacrossthesestakeholdersandhasa
bigroleindiscussionsaroundtransitionsintheUKenergysystem.
You recently conducted a review of energy system models in the UK. What were the main findings from this review?
Wefoundthatthemajorityofpublicationsofmodellingresultscame
fromonlyaveryfewdifferentmodelsandthatthepolicydocuments
citethesamemodelsastheacademic literature.This isagood
thing,asitmeansthattheacademicandpolicycommunitiesare
joinedup.FromourresearchIthinkit’sfairtosaythatthereisn’t
thesameinternationaltravellingofenergysystemsmodellingasin
otherscienceandtechnologyfields.Themodelsthatwefoundcited
intheUKscienceandpolicy literatureweremainlyhome-grown.
Itwouldbeinterestingtodoacomprehensivestudytoseewhere
modelshavetravelledinternationallyandhowthishasimpacted
onenergypolicyinthosecountries.
What are some of the limitations of existing energy system modelling tools?
I thinkoneofthemajorchallengesisthe integrationofqualita-
tiveresearchfromthesocialsciencesaroundscenariosandpolicy
changes.It’sallverywellhavinghighlyaccurateandgranularenergy
flowmodelsfordifferentfuturegenerationmixscenariosbutifthe
transitiontothesescenariosisentirelydependentonpoliticalfactors
atboththeEU,nationalandlocallevelthenthemodeliskindof
irrelevant.Ithinkinvestmentinnewapproachestothedemocrati-
sationofmodellingwithparticipationfromkeystakeholderswould
beveryinteresting.WehaveattemptedthisinaUK-basedresearch
projectandfoundcomputationalenergymodelstobeimpenetrable
bymostofthesestakeholders.
Alistair BuckleyAlastair Buckley is a senior lecturer in the department of physics at the University of
Sheffield. His research investigates the integration of solar PV into future energy systems
from technological and socio-technical viewpoints. His Sheffield-based research team has
developed real-time PV power monitoring for the UK transmission network.
Based on your review, do you have any recommendations regarding the optimisation of modelling capacity?
Ithinkthatopeningupallenergybaseddataacrosstheacademic,
policyandsystemoperatorcommunitieswouldresult inastep
changeinintegrationofthedifferentmodellers.Accesstodatais
akeyconstraintinmodellingandopendatasourceswouldallow
validationofdifferentmodelsacrossdifferentscenarios.This,inturn,
wouldresultinawidervarietyofstakeholderstouseawidervariety
ofmodels.Ithinkthiswouldbehighlybeneficial.
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
EnergysystemmodellingisakeytoolforEDFR&D.It isusedto
evaluatethe impactofenergypolicies(renewabledeployment,
EUETS),torecommendbusinessstrategiesandanalysebusiness
opportunitiesbasedonevolutionsintheenergy/powersystemsand
tocontributetothepublicdebate.
Multi-energyanalysisisgainingincreasedattention,asmoreinter-
actionsbetweenelectricity,heatandcold,andgassystemscre-
atepromisingopportunitiesfordecarbonisation(for instance,by
developingmoreefficientusagesorsharingflexibilitiesforabetter
integrationofvariablerenewables).Somemajorchallengesneed
tobeaddressed:modellingtheseinteractionsiscomplex,andcan
leadtooverlycomplexmodelsor,onthecontrary,totheuseof
significantsimplifications.Thesesimplificationsmustbemade
carefully,especiallywhenmodellingpowersystems,astheycan
easilydistorttheresultsandleadtoapartialunderstandingofthe
system’scomplexity.
Morespecifically,energysystemmodellingisoftenlinkedtoone
typeofmodelling,namelymodelsbasedonTIMES,representingthe
interactionsbetweenseveralenergyvectors.Thesemodelsmakeit
possibletosimulateandoptimisedecarbonisationscenariosover
severaldecades,whichmakesthemhighly interesting.However,
mostTIMESmodelsdonotcurrentlyallowforadetailedenough
Energy system modelling intheindustry:theEDFR&Dperspective
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
representationoftheelectricitymix. Inparticular, theygenerally
cannotgivespecificinsightsontheneedsforflexibilityrelatedtothe
growingpenetrationofwindandsolarsources(forexample,asthese
modelsdonotusehourlystepsormulti-scenarioapproaches,rules
ofthumbareneededtodecideontherequiredpeakingcapacity-an
approachthathasobviouslimitations).
EDFR&Dhasledamajoreffortinrecentyearstostudytheimpli-
cationsofvariousenergyscenariosontheelectricpowersystem.
Variousapproachesweretestedanddevelopedin-house.Oneof
these,usedin“TechnicalandeconomicanalysisoftheEuropean
electricitysystemwith60%RES”,4consistsofusinga“chainof
models”(insteadofasinglemodel),witheachmodelinthechain
makingitpossibletostudyandgraspvariouskeyimpactsofwind
andsolarintegrationinpowersystems.
TheCONTINENTALmodel(seeLangrenéetal)5isthemainstepin
themodellingchaindescribedbelow.Theinputdataandhypothe-
ses(suchastheCO2price,demandlevel,etc.)comefromenergy
4 Alain Burtin, Vera Silva, “Technical and economic analysis of the European electricity system with 60% RES”, EDF R&D, June 2015.
5 Nicolas Langrené, Wim van Ackooij, and Frédéric Bréant, “Dynamic Constraints for Aggregated Units: Formulation and Application”, IEEE transactions on Power Systems, Vol 26, no. 3, August 2011.
scenarios,whicharesometimesestablishedusing largeenergy
systemsmodels(suchastheEDFR&DMadone/TIMESmodel,or
theJRCmodel(seeSimoesetal)),6whichthenconstitutethefirst
stepofthemodellingchain.TheCONTINENTALmodel’s5outputscan
alsobefedintoothermodules/models,constitutingthelaststeps
inthechain,asdescribedbelow.Thefollowingparagraphsdescribe
inmoredepththecoremodelandthesub-modulesdeveloped.
Inordertostudytheimpactofwindandsolar,thecorepowersystem
model(CONTINENTAL)needstofeaturesomeminimumcharacter-
isticstoprovidecredible insights.These“minimal/recommended
requirements”havebeenwelldiscussedintheresearchcommunity
inrecentyears,andthemostoftencitedare:
•• Hourly base And multi scenariosofdemandandvariable
generation:assessingtheneedforbackupgenerationimplies
beingabletotakeintoaccountextremeeventsthatcanhappen
overafewhours,incertainyears.Theuseofaverageprofiles
(forinstance,onlypeakandoff-peaksteps,ononeaverageday
permonth)cannotcapturesuchevents.
6 Sofia Simoes, Wouter Nijs, Pablo Ruiz, Alessandra Sgobbi, Daniela Radu, Pelin Bolat, Christian Thiel, Stathis Peteves, “The JRC-EU-TIMES model, Assessing the long-term role of the SET-Plan Energy technologies”, JRC Scientific and Policy Report, 2013.
Investment / hourly dispatchDetailed description of VGLocationofVG
Loadfactors(with resolution1horlower)
VGforecasterrors
Input dataDemandtimeseries
Investmentcosts
Generationdynamic constraints
Fuelscosts
CO2 price
Networktransfercapacities
Generationmix
Interconnection loadfactors
Generationloadfactors
VGcurtailment
Market prices andgeneration costs
Plantrevenues
Reservesandflexibilityadequacy
Frequencystability
Investment loop
CONTINENTALMODEL
Madone/TIMES model
Dynamicsimulationmodel
Flex Assessment
Economical analysis
© Burtin and Silva
Figure 4: EDF chain of models
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Figure 5: European load duration curve of demand and net demand with 60% RES (left) and structure of the generation mix with and without wind and PV generation (right)
•• Multi-zone modelling(i.e.modellingexchangesbetweencoun-
triesintheEuropeansystem):nationalstudiesoftenusea“single
zone”model,usingroughapproximationsforthelevelandprices
ofimportsandexport.AstheEuropeangridgetsmoreintegrated
andinterconnected,theimpactofthesesimplificationsshouldbe
re-assessedregularly.TheCONTINENTALmodelmakesitpossible
tofeatureaEuropeanmulti-zonemarket.
•• Water reservoirs and pump storage management:Hydro
resourcesandexistingpumpstoragearekeyprovidersofflexibil-
ity–mostmodelsrelyonsimplifiedrulesofthumbandadeter-
ministicvisiontodispatchtheseenergy-constrainedresources.
Suchsimplificationsmightunder-oroverestimatetheroleof
theseresources,whileastochasticmodellingofhydro(such
astheoneusedinCONTINENTAL)givesamorerealisticview.
•• Detailed modelling of thermal unit constraints:dynamic
constraintssuchasminimumon/offtime,start-upcosts,mini-
mumstablegeneration,etc.areimportantwhenestimatingthe
systemflexibility–modellingtheseconstraintsgenerallyimplies
verystrongincreasesinproblemcomplexityandcomputingtime.
Itmightthereforenotbepossibletoalwaysmodelthem,but
sensitivitiestotheseparametersshouldbeconsidered.
Additionally,suchmodelsshouldmakeitpossibletoanalysethe
needfordifferenttypesofback-upfossilgeneration(e.g.theshare
ofcombinedcycleversusopencyclegasturbines)– intheEDF
modellingchain.Thesocalled“investmentloop”makesitpossible
toestablishaleastcostback-upgenerationfleet,respectingapre-
definedadequacycriteria(a3/yhoursLossofLoadExpectation).
Figure5givesanexampleofhowthermalgenerationwouldevolve
fromaEuropeansystemwith0%windandsolartoonewith40%.
However,asalreadymentioned,addingtoomanyfeaturesatonce
inonesinglepowerdispatchmodelmightnotalwaysbeagood
option:thecomputingtimeis likelyto increasesharply,butalso
(andperhapsmore importantly) itmight limitthepossibilityto
understandallthephenomenaatplayinahighRESsystem(when
modelsbecomeoverlycomplex,thereisariskthattheybecomefor
mostpeopleamysteriousblackbox,insteadofatoolthatallowsa
betterunderstandingbyengineersandeconomists).
No Wind & SolarTotal: 444 GW
With Wind & SolarTotal: 352 GW
European thermal installed capacity
89GW71GW
34GW
89GW78GW
250GW
86GW99GW
0
50
100
150
200
250
300
GW
1000 2000 3000 80007000600050004000 Nuclear Coal CCGT OCGT
600
500
400
300
200
100
-
-1000
is The need for baseload generation
is reduced by 160 GW
700
With 40% wind and PV the need forbackup generation increases 60 GW
0 2
12
10
8
6
4
2
04 6 8 10 12
2013 Scenario 60% RES
Upw
ard
mar
gin
(GW
)
percentiles 2.5 - 97.5%
14 16 18 20 22 24 0 2
12
10
8
6
4
2
04 6 8 10 12
Upw
ard
mar
gin
(GW
)percentiles 25 - 75%percentiles 47.5 - 52.5%
© Burtin and Silva
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Figure 6: Day-ahead operating in 2013 and the simulated operating margin
for the scenario “60% RES” for France during summer
Therefore, for its2015study4, EDFR&Ddevelopedadditional
sub-modulesusingoutputdatafromthepowersystemmodelto
analysespecificpowersystemissues,suchastheneedforopera-
tionalmarginscomparedtotheavailableflexibility(“FlexAssessment”
–seeFigure6),orthebehaviouroffrequency(“Dynamicstability
module”),withoutmodifying(andmakingmorecomplex)thecore
powersystemmodelitself.
TheCONTINENTALmodelandthevarioussub-modulesmakeit
possibletosimulateoneyearperiods.So,itisnotpossibledirectly
toproposeevolutionscenarios,forwhichTIMESmodelsarebetter
suited.Itwould,however,bepossibletoextendthe“chainofmodels”
andtoback-feedinformationintotheTIMESmodel(suchas,for
example,abettervisionoftherequiredthermalback-upgeneration).
Interactionbetweenmodelsinthiswaycanbeagreattooltobuild
decarbonisationscenariosthattakeintoaccountbothmulti-energy
interactionsandthestrongspecificitiesofelectricalpowersystems.
The“chainofmodelling”discussedhere isoneexamplewhere
modellinghasprovidedsignificant insights intothe implications
andchallengesofahighRESEuropeanscenariofortheelectricity
system.4EDFR&D,alreadywithalonghistoryofenergymodelling,is
continuingtoworkonenergysystemmodelling,inanefforttokeep
increasingourunderstandingofthecurrentandfuturechallenges
oftheelectricityandenergysystems.
89GW71GW
34GW
89GW78GW
86GW99GW
0
50
100
150
200
250
300
GW
1000 2000 3000 80007000600050004000 Nuclear Coal CCGT OCGT
600
500
400
300
200
100
-
-1000
is The need for baseload generation
is reduced by 160 GW
0 2
12
10
8
6
4
2
04 6 8 10 12
Time (hours )
2013 Scenario 60% RES
Upw
ard
mar
gin
(GW
)
percentiles 2.5 - 97.5%
14 16 18 20 22 24 0 2
12
10
8
6
4
2
04 6 8 10 12
Time (hours)
Upw
ard
mar
gin
(GW
)
14 16 18 20 22 24
percentiles 25 - 75%percentiles 47.5 - 52.5%
© Burtin and Silva
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Paul Fourment Paul Fourment graduated in energy engineering from the Ecole Polytechnique (Paris). He
has worked for three years at EDF R&D as a research scientist on renewable integration in
the European Power System. His work deals in particular with the power system’s flexibility
needs, the articulation between nuclear and renewable technologies, and the cohabitation
between global and local systems.
Dr. Vera Silva Dr. Vera Silva is the director of the EDF R&D research program on “Energy systems and
markets” and a senior researcher at EDF R&D in the field of “operation of electricity systems
and markets”. She has 18 years’ experience in the power systems industry and before joining
EDF in 2009 she worked as a research assistant at the Control & Power research group of
Imperial College London and at the University of Manchester.
Miguel Lopez-Botet Miguel Lopez-Botet is the manager and technical leader of a project team responsible for
“Analysis of future energy mixes” within EDF R&D. His main research topics are generation
expansion planning and operation, the integration of wind and solar PV generation and the
value of flexibility and ancillary services.
Timothée Hinchliffe Timothée Hinchliffe is project manager on energy storage economics at EDF R&D. His main
focus over the past five years has been the assessment of energy storage needs through
the use of modelling, and considering the competition with other flexibility levers such as
interconnections or demand response. Timothée holds a Master’s in Electrical engineering
from Supelec.
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
METIS is a researchprojectoftheEuropeanCommission’sDirecto-
rate-GeneralforEnergy(DGENER)forthedevelopmentofenergy
simulatorsoftwarewiththeaimtofurthersupportENER’sevi-
dence-basedpolicy-making.Itisdevelopedbyaconsortium(Artelys,
IAEW,ConGasandFrontierEconomics)aspartofHorizon2020and
iscloselyfollowedbyDGENER.
Software description
Unlikeothersimulators,METIS will be owned and operated by DG
ENER,withthesupportoftheCommission’sin-housescienceand
knowledgeservice,theJointResearchCentre.Theintentionisto
haveanin-housetoolthatcanquicklyprovideinsightsandrobust
answerstocomplexeconomicandenergyrelatedquestions,focusing
moreontheshort-termoperationoftheenergysystemandmarkets.
METISwasused,alongwithPRIMES,intheimpactassessmentof
theMarketDesignInitiative.
METISisanenergymodelthatcovers,withhighgranularity(geo-
graphical,timeetc.),thewholeEuropeanenergysystemforelectricity,
gasandheat.Initsfinalversionitshouldbeabletosimulateboth
systemandmarketoperationfortheseenergycarriers,onanhourly
levelforawholeyearandunderuncertainty(capturingweather
variationsandotherstochasticevents).METISworkscomplementary
tolong-termenergysystemmodels(likePRIMESandPOTEnCIA)as
itfocusesonsimulatingaspecificyearingreaterdetail.
METIShasamodularstructurethatmakes iteasytoextendthe
softwarethroughtheadditionofnewmodulesortheadjustmentof
existingones.Themodelrunsareperformedbysoftwarededicated
to large energy system optimisation7.Allcomponentsandmodules
aremanagedbyaplatform8providingacommonframeworkand
setofinteroperablelibraries.
Althoughintendedtobeadetailedoutput-tool,significantemphasis
isalsoplacedonitsuser-friendlinessandfastoperability.Theend
goalofMETISisthatitcanbeusednotonlybyexpertmodellers,
butalso(trained)policy-makersandanalysts.
WiththefirstversionofMETIShavingbeendelivered inJanuary
2015,newversionsareexpectedtobedeliveredgraduallyoverthe
nexttwoyears,includingadditionalmodellingcapabilitiesrelated
toelectricityandgasmarkets,heatanddemandsidemodelling.
METIS Studies
Paralleltothesoftwaredevelopment,theconsortiumwillbeproducing
studiesusingMETIS.Theseareintendedtobetechnicalstudiesof
around50pagesinlength,fullyexploitingtheavailablecapabilities
oftheMETISsoftware.Thescopeofthestudiesisthreefold:
(a) InvestigatetopicsthataredeemedimportantforDGENER,
7 Crystal Optimization Engine,propertyofArtelys.8 Artelys Crystal Platform, propertyofArtelys.
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METIS:thenewshort-termenergysystemmodelexploredbythe Directorate-GeneralforEnergy
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
providingquantitativeresultsassociatedwiththeimpactofthe
examinedpoliciesoraspectsoftheenergysystem;
(b) Presentthecapabilityandappropriatenessofthesoftwareto
addresspolicyquestionsofinteresttoDGENER;
(c) ProvidereadytemplatesforDGENERinordertoperformsimilar
studiesinthefuture.
Which policy questions can METIS answer and which ones can’t it?
Uponfinaldelivery,METISwillbeabletoansweralargenumberof
questionsandperformhighlydetailedanalysesoftheelectricity,gas
andheatsectors.Itwillbepossibletotackleanumberoftopicswith
METISforthewholeEUand/orforspecificregions/MemberStates
(thelistbelowisindicative):
•• TheimpactsofmassRenewableEnergySourceintegrationon
theenergysystemoperationandmarketsfunctioning(forone
orallsectors);
•• Modellingofelectricityandgasmarketsunderdifferentmarket
designs;
•• Modellingofelectricityandgasflowsbetweenzones;
•• Cost-benefitanalysisofinfrastructureprojects,aswellasimpacts
onsecurityofsupply;
•• Generationadequacyanalysis;
•• Studyingthepotentialsynergiesbetweenthevariousenergy
carriers(electricity,gas,heat);
•• Whatisthecost/savingofaspecificmeasureforagivenyear?
•• Impactofnewenergyusages(e.g.electricalvehicles,demand
response)onthenetworkreinforcementandgenerationcosts.
Figure 9: METIS module architecture
Figure 8: Power model
Figure 7: Gas model
Source: METIS
Source: METIS
Source: METIS
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
OntheotherhandMETISisnotdesignedtoanswer(atleastinthe
initialstage)thefollowingquestions(again,thelistisindicative):
•• Anytypeofprojectionforthewholeenergysystem;
•• Optimal investmentplanning(capacityexpansion)fortheEU
generationortransmissioninfrastructure9;
•• Impactsofmeasuresonnetworktariffsandretailmarkets;
•• Short-termsystemsecurityproblemsfortheelectricityandgas
system(requiringapreciseestimationofthestateofthenetwork
andpotentialstabilityissues);
•• Flow-basedmarketcouplingandmeasuresontheredesignof
biddingareas.
9 TheplannedversionofMETISwillincludesomecapacityexpansioncapability,abletooptimisethecapacityofcertaintransmissionandgenerationassets.FutureversionsofMETISmayhaveadditionalcapabilities.
Transparency
METISwillbefullytransparentconcerningthemodellingtechniques
applied,withthefinalgoalofbeingabletooffertherelevantsource
codeandnon-commercialdatainputs.Furthermore,alltechnical
documentationandstudiesproducedwillbemadeavailable.
Fortransparencyreasons,alldeliverablesrelatedtoMETIS,including
alltechnicalspecificationsdocumentsandstudies,areintendedto
bepublishedonthewebsiteofDGENER10.
10 Onceoperational,theenvisagedlinkisexpecttobethefollowing: https://ec.europa.eu/energy/en/data-analysis/energy-modelling/metis
Kostis Sakellaris Kostis Sakellaris joined the Economic Analysis Unit of the European Commission’s Direc-torate-General for Energy in 2012. He has been working in the modelling team since then, heavily involved in a number of energy-related impact assessments and projects (METIS, Market Design, 2030 Energy and Climate Framework, Reference Scenario). Prior to that, he worked as an electricity market expert in the Markets and Competition Unit of the Greek Regulatory Authority for Energy. He graduated as a mathematician in Athens, Greece and holds an MSc in Mathematical Finance from the University of British Columbia, Canada.
Figure 10: Performing studies with METIS – screenshot from user interface
Source: METIS
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Giventheuncertaintyandcomplexityoftheenergysystem,quanti-
tativemodelsarevitaltoolstoexplorealternativescenariosandhelp
guidepublicpolicy.Yetmostmodelsanddataremaininscrutable
“blackboxes”–whethersmalleconometricmodelsorlargelinear
optimisationmodelswithhundredsofthousandsofinputvariables.
Incontrasttoclosedmodels,“open”modelsimplythatanyonecan
freelyaccess,use,modify,andsharebothmodelcodeanddatafor
anypurpose(OpenKnowledgeFoundation,2015).11Inthisarticlewe
arguewhyenergydataandmodelsurgentlyneedtobecomeopen;
discussthekeyreasonswhymanyarecurrentlynot;andpropose
somenextstepsfortheenergyresearchcommunity.
11 OpenKnowledgeFoundation,2015.OpenDefinition2.1-OpenDefinition-DefiningOpeninOpenData,OpenContentandOpenKnowledge[WWWDocument].URLhttp://opendefinition.org/od/2.1/en/(accessed3.15.16).
Why models and data should be open
Giventhecriticalguidancethatenergymodelsanddataprovideto
decision-makers,theyshouldbemadeopenandfreelyavailableto
researchersaswellasthegeneralpublic,forfourreasons:
1. Improved quality of science.Transparency,peerreview,repro-
ducibilityandtraceabilityleadtohigherqualityscience.Yetthese
principlesarealmostimpossibletoimplementwithoutaccessto
modelsanddata(DeCarolisetal.,2012;Nature,2014).12Human
errorisinevitableunderpressuretodeliver,andmodelmistakes
canhaveprofoundimplications.Forexample,theReinhart-Rogoff13
12 DeCarolis,J.F.,Hunter,K.,Sreepathi,S.,2012.Thecaseforrepeatableanalysiswithenergyeconomyoptimizationmodels.EnergyEconomics34,1845–1853.doi:10.1016/j.eneco.2012.07.004;Nature,2014.Journalsuniteforreproducibility.Nature515,7–7.doi:10.1038/515007a
13 Herndon,T.,Ash,M.,Pollin,R.,2014.Doeshighpublicdebtconsistentlystifleeconomicgrowth?AcritiqueofReinhartandRogoff.Camb.J.Econ.38,257–279.doi:10.1093/cje/bet075
Theimportanceofopendata andsoftwareforenergyresearchandpolicyadvice
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spreadsheeterrorarguablyskewedtheinternationaldebateon
austerity(Herndonetal.,2014)14.Suchincidentsserveaswarnings
againstpoorprogrammingpracticessuchasalackofauditing,
aswellasclosedmodelsanddata:itwasonlythroughsharing
thespreadsheetthattheerrorswerediscovered.
2. More effective collaboration across the science-policy
boundary.Betterandmoretransparentscienceitselfoughtto
enablebetterpolicyoutcomes.Academicpeerreviewroutinely
doesnotcheckmodelarithmeticanddatavalidity,andsoa
separateprocessofqualityassuranceisrequired.Whilemostly
absentfromacademicpractice,this isoftenimplementedas
aformalprocedure ingovernment(e.g.,DECC,2015)15.Unlike
academics,governmentsoftenmodelfornumbersratherthan
insight.Thespecificnumberscanbeofgreatsocietal impor-
tance,suchasthelevelatwhichtosetsubsidiesorthecostof
specificpolicies.Often,themostimportantaspectisthequality
ortransparencyof inputdata,ratherthanthenoveltyofthe
modellingmethodology.Inlargedatasetsusedingovernment
decision-making,traceabilityandreferencingcanbecomemajor
problems,ascivilservantsdevelopingmodelsanddataareoften
nottrainedscientists.Openlyavailable,collaborativelydeveloped
datasetsandreferencemodelswouldallowtheburdenofthis
worktobesharedmorewidely,andacrossbothacademiaand
government.
3. Increased productivity through collaborative burden shar-
ing.Collectingdata,formulatingmodelsandwritingcodeare
resource-intensive,whileresearchfundingandtimearescarce
resources.Societybenefits if researchersavoidunnecessary
duplicationandlearnfromoneanother.Individualresearchersgain
moretimetospendonpressingresearchquestionsratherthan
redundantworkonmodelordatasetdevelopment.Furthermore,
researchonlymattersifit isseenandused,andopen-access
publishinghasbeenshowntoincreasereadershipandcitations
(McCabeandSnyder,2014)16.Sinceopenlysharedcodeordata
ismorelikelytobeknowntoothers,itismorelikelytobeused
andfurtherimproved.Thisbenefitstheoriginalresearcherthrough
peerrecognitionandacademiccredit,andmovestheresearch
communityasawholeforward.
4. Profound relevance to societal debates.Reengineeringtheenergylandscapewillaffecteveryone,producingwinners
andlosers.Abalancedsocietalandpoliticaldebaterequires
transparentargumentsbasedonscientific justifications,but
14 Herndon,T.,Ash,M.,Pollin,R.,2014.Doeshighpublicdebtconsistentlystifleeconomicgrowth?AcritiqueofReinhartandRogoff.Camb.J.Econ.38,257–279.doi:10.1093/cje/bet075
15 DECC,2015.QualityAssurancetoolsandguidanceinDECC[WWWDocument].URLhttps://www.gov.uk/government/collections/quality-assurance-tools-and-guidance-in-decc(accessed6.2.16).
16 McCabe,M.J.,Snyder,C.M.,2014.IdentifyingtheEffectofOpenAccessonCitationsUsingaPanelofScienceJournals.EconomicInquiry52,1284–1300.doi:10.1111/ecin.12064
escalatingconcernaboutreproducibilityinsomefieldsisshaking
publicconfidenceinscientificresearch(Goodmanetal.,2016)17.
Finally,besidesthepracticalconsiderationsoutlinedabove,there
remainstheethicalargumentthatresearchfundedbypublic
moneyshouldbeavailabletothepublicinitsentirety.
Why they are (mostly) not open
Despitethesearguments,weseefourmainreasonswhyclosed
modelsanddatamayremainattractiveandrationalinsomecases:
1. Thereisarangeofvalidethicalandsecurityconcerns,particu-
larlywithdata.Researchersmayhaveaccesstodatacontaining
commercialsensitivitiesorpersonal information(particularly
relevantwhenmovingtowardsmoredecentralisedsmartgrids
withtheirfocusonindividualhouseholds).
2. Openlysharingdetailsofmodels,analysisanddatacancreate
unwantedexposure.Flawedcodeordatacandiscreditresearch
resultsandcauseembarrassmenttotheirauthors,butonlyifthey
arevisible.Somemayalsofearthatinexperiencedresearchers
willuseanopenmodeloropendatatoproduceflawedanalysis
thatreflectspoorlyonitsoriginalauthors.
3. It istime-consumingtowrite legibleandreusablecode,track
processingsteps,writedocumentationandrespondtofeature
requests.Becausemodelanddatasetdevelopmentare large
investments,itisoftenrationalforresearchersandinstitutions
tomaintain“tradesecrets”tocompeteforthird-partyresearch
funding:aclassicalcollectiveactionproblemwhereindividual
actorsaretrappedinasuboptimalnon-cooperativeequilibrium.
4. Finally,there issimple institutionalandpersonal inertia,often
alongsidecomplexanduncoordinatedinstitutionalsetups.
Whileunderstandablefromtheperspectiveof individualactors,
collectivelytheseengenderasenseofmistrustincomplex,impen-
etrablemodelsandenigmaticdatasets.Forexample,theEuropean
CommissionfacedcriticismforusingtheproprietaryPRIMESmodel
todeliverkeyresultsfor itsEnergyRoadmap2050(Helmetal.,
2011).18Moresignificantly,theUK’sdecarbonisationwasarguably
delayedforyearsbymodelsthatunderestimatedthescaleofthe
challengeduetoopaqueandheroicallyoptimisticcostassumptions
foronshorewind(HouseofLords,2005).19
17 Goodman,S.N.,Fanelli,D.,Ioannidis,J.P.A.,2016.Whatdoesresearchreproducibilitymean?ScienceTranslationalMedicine8,341ps12–341ps12.doi:10.1126/scitranslmed.aaf5027
18 Helm,D.,Mandil,C.,Vasconcelos,J.,MacKay,D.,Birol,F.,Mogren,A.,Hauge,F.,Bach,B.,vanderLinde,C.,Toczylowski,E.,Pérez-Arriaga,I.,Kröger,W.,Luciani,G.,Matthes,F.,2011.FinalreportoftheAdvisoryGroupontheEnergyRoadmap2050.
19 HouseofLords,2005.TheEconomicsofClimateChange.Vol.II.2005,HL12-IIof2005-06,QQ407-408.
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What needs to be done
Individualresearchersandresearchgroupsmustunderstandthe
practicalitiesofopencodeanddata.Theserangefromissueslike
consideringtheintendedtargetaudienceandchoicessuchaslicensing
anddistributionchannels.Pfenningeretal.(2016)20giveguidance
specificallyforenergyresearch.Moreimportantly,theenergyresearch
communityasawholeneedstomoveforwardonseveralfronts:
1. Work towards reducing parallel efforts and duplication of
work.Thereshouldbebettercoordinationbetweendifferentmodellingefforts.Thiscanincludethedevelopmentofcommon
codebases,commondatasets,communitystandardstoensure
interoperability,andcoordinatedeffortstoenablethird-party
verificationofmodel-basedresults.
2. Increase transparency and reproducibility.Communityefforts
towardstestedanddocumentedcodepackagesforspecifictasks
canserveanimportantpurpose.Butone-offanalysescreated
forspecificpapers,orcodethatiswrittenwiththeunderstanding
thatitwillneverbemadepublic,maybepoorlydocumentedand
structured,meaningitsreleasewouldbeoflimiteduse.
20 Pfenninger,S.,Schmid,E.,Wiese,F.,Hirth,L.,Davis,C.,DeCarolis,J.F.,Fais,B.,Krien,U.,Matke,C.,Momber,I.,Müller,B.,Pleßmann,G.,Quolin,S.,Reeg,M.,Richstein,J.C.,Schlecht,I.,Shivakumar,A.,Staffell,I.,Trön-dle,T.,Wingenbach,C.,2016.Benefits,challengesandsolutionsforopenenergymodelling.OpenEnergyModellingInitiativeWorkingPaper.URLhttps://openmod-initiative.github.io/openmod-working-paper/(accessed1.7.16).
3. Change incentives and bring aboard different stakeholders. Theenergyresearchcommunityandspecificallytheemerging
openmodellingandopendatacommunitiesmustengagewith
otherstakeholderstoensureinstitutionalandacademicrecog-
nitionforopenenergymodels,andtostarttacklingtheharder
problemsthatfollow.Openandtransparent research isnot
currently incentivised: infact,theopposite isoftenperceived
asadvantageousforscientificcareeradvancement.Changing
theseincentiveswill requireeffortsnotonlyfromresearchers
themselvesbutalsofromtheiremployers,fromgrantagencies,
andotherstakeholderslikepublishers(Noseketal.,2015).21
Giventheimportanceofrapidglobalcoordinatedactiononclimate
mitigationandtheclearbenefitsofsharedresearcheffortsand
transparentlyreproduciblepolicyanalysis,thecommunitystillhas
muchworkahead.
21 Nosek,B.A.,Alter,G.,Banks,G.C.,Borsboom,D.,Bowman,S.D.,Breckler,S.J.,Buck,S.,Chambers,C.D.,Chin,G.,Christensen,G.,Contestabile,M.,Dafoe,A.,Eich,E.,Freese,J.,Glennerster,R.,Goroff,D.,Green,D.P.,Hesse,B.,Humphreys,M.,Ishiyama,J.,Karlan,D.,Kraut,A.,Lupia,A.,Mabry,P.,Madon,T.,Malhotra,N.,Mayo-Wilson,E.,McNutt,M.,Miguel,E.,Paluck,E.L.,Simonsohn,U.,Soderberg,C.,Spellman,B.A.,Turitto,J.,VandenBos,G.,Vazire,S.,Wagenmakers,E.J.,Wilson,R.,Yarkoni,T.,2015.Promotinganopenresearchculture.Science348,1422–1425.doi:10.1126/science.aab2374
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Joseph DeCarolis Joseph DeCarolis is an Associate Professor in the Department of Civil, Construction, and Environmental Engineering at North Carolina State University. His research is focused on the interdisciplinary assessment of technologies and public policies that promote long-term energy sustainability. He is particularly interested in developing robust decision-making strategies for climate mitigation by conducting analysis with technology-rich energy system optimisation models.
Sylvain QuoilinSylvain Quoilin obtained a European Doctorate in Mechanical/Energy Engineering in 2011 at the University of Liege (Belgium), where he then became lecturer. He is now a scientific officer at the Joint Research Centre of the European Commission, focusing on energy policy support and on the modelling of future European energy systems.
Iain StaffellIain Staffell is a lecturer in Sustainable Energy at Imperial College London, holding degrees in Physics, Chemical Engineering and Economics. His research centres around decarbonising electricity, ranging from the economics of battery storage and nuclear power to modelling the integration of renewables into electricity systems.
Dr Stefan Pfenninger Dr Stefan Pfenninger is a member of the Climate Policy Group at ETH Zurich, Switzerland. He holds degrees in environmental science, environmental policy, and environmental engi-neering. His research interests span the challenges and opportunities in the clean energy transition, particularly the modelling of futures with high shares of wind and solar energy.
Dr Lion Hirth Dr Lion Hirth is a post-doctoral researcher at the think tank MCC, a fellow at the PIK research institute, and director of the consulting firm Neon. His research interest lies in the econom-ics of wind and solar power. He has been concerned with open energy data in a number of projects and maintains the open-source power market model EMMA.
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
TheNordicEnergyTechnologyPerspectives(NETP)seriesassesses
howtheNordicregioncanachieveacarbon-neutralenergysystem
by2050.NETP2016marksthesecondeditionintheseries,thefirst
havingbeenpublishedin2013,andpresentstechnologypathways
towardsanear-zeroemissionNordicenergysysteminadditionto
in-depthscenariostailoredtoinformpolicy-makingintheregion.
TheanalysisconductedinNETP2016ispresentedaroundtheNordic
CarbonNeutralScenario(CNS),whichcallsforan85%reductionin
emissionsby2050(from1990levels).22Toachievethistarget,three
macro-levelstrategicactionsareelaborated.Thefirstofthesecalls
fortheplanningandincentivisationofaNordicelectricitysystem
that issignificantlymoredistributed, interconnectedandflexible
thanatpresent.Thesecondcallsfortheaccelerateddevelopment
oftechnologythatwillincreasethedecarbonisationoflong-distance
transportandtheindustrialsector.Finally,thethirdstrategicaction
22 TheNordic4°C(4DS)entailsa42%reductionandservesatthebaseline.
aimstotapintothepositivemomentumofcitiestostrengthen
nationaldecarbonisationandenergyefficiencyeffortsintransport
andbuildings.
Achieving a carbon-neutral energy system
TheNordiccountrieshavealreadydecarbonisedaspectsoftheir
energysystems,havingdecoupledCO2emissionsfromGDPgrowth
overtwodecadesago.Howeverthisprocesswillhavetopickupin
paceiftheCNSistobeachieved.Policyandtechnologyinnovationwill
becrucialinthisregard.Thepoliciesandtechnologiesimplemented
todatehavealreadycapturedthemostcost-effectiveopportunities
toweakenthelinkbetweeneconomicgrowthandemissions,leaving
greaterchallengesinsectorswhereprogresshasbeenmoredifficult.
TheCNSrequiresadramaticchangeinthecompositionofprimary
energysupply,coupledwithaggressiveenergyefficiencypoliciesthat
TheNordicEnergyTechnologyPerspectives2016
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substantiallyreducedemand.Underthescenario,bioenergysurpasses
oilasthelargestenergycarrier,withtotaldemandforbiomassand
wasteincreasingfromalmost306millionMWhin2013toover444
millionMWhin2050.However,themostdramatictransformation
oftheNordicpowerandheatingsystemwillcomefromthecom-
binationofadeclineinnuclearandasignificantbuild-outofwind
power,resultingingenerationthatfarexceedsdomesticdemand,
evenwhenreducednucleargenerationisfiguredin.
Withanincreasefrom7%ofelectricitygenerationin2013to30%
in2050,windwilldisplacefossilandnuclear.Whilethetransition
ofheatingnetworksfromfossilfuelstoheatpumpsandelectric
boilerswilladdflexibilitytoanintegratedpowerandheatsystem,
theincreaseinwindgenerationwillputnewdemandsonhowthe
electricitymarketisorganised.Hydropowerwillbeincreasinglyval-
uableforregulatingthemarket,butwillnotsufficeonitsown.The
increaseinvariabilitywillrequirebalancingthroughacombination
offlexiblesupply,demandresponse,storageandelectricitytrade.
Increasedtradewillreducesystemcostsandenhanceflexibility,but
longleadtimesinsettingupinterconnectorsandstrengtheningthe
gridmaydelayachievingfullpotential.
Industrial sector decarbonisation the greatest challenge
The60%reductionintheCO2intensityofindustrycalledforinthe
CNSwillrequireaggressiveenergyefficiencycombinedwithother
measures,suchasswitchingfuelandfeedstockto lower-carbon
energymixes,andthedeploymentof low-carboninnovativepro-
cesses,includingCCS.Increasedinternationalcooperationwillalso
berequired,forexamplethroughinternationalcarbonpricingor
energyperformanceauditingmechanisms,asthesewillplayakey
roleinmitigatingtherisksofthelow-carboninvestmentsneeded
todecarbonise industry, therebyreducingpotential impactson
competitiveness.
AchievingtheCNSwillrequirea10%increaseininvestmentsover
thatneededforthe4DS22targetintheperiodfrom2016to2050,
representinganadditionalinvestmentofaboutEUR298billion.23
Thegreatestrelativeinvestmentincreasesarerequiredinbuildings
andindustry,withanincreaseof47%requiredinthefiveindustrial
sectorsanalysed,whichtogetheraccountfor80%ofthetotalfinal
energyusebyindustryintheNordicregion.Thisrepresentsacumu-
lativeinvestmentofaroundEUR27billion,mainlyassociatedwith
energyefficiencyimprovementsandthedeploymentoflow-carbon
innovativeprocesses.AtEUR179billion,thelargestshareofaddi-
tionalcumulativeinvestmentisaccountedforthebytransportsector.
23 US$333billion.
Radical transformation of transport
Transport,whichcurrentlyaccountsforalmost40%ofNordicCO2
emissions,deliversthegreatestemissionreductionintheCNS.Trans-
portrequiresadramaticemissionsslash–fromabout80million
tonnesofCO2in2013tojustover10milliontonnesin2050.This
targetcanbeachievedthroughathree-pronged‘avoid-shift-improve’
strategyofreducingtransportactivity(avoid),shiftingtomoreeffi-
cientorlesscarbon-intensivetransportmodes(shift)andadoption
ofmoreefficientorlesscarbon-intensivetransporttechnologiesand
fuels(improve).Improvementstotechnologiesandfuelswillplay
thelargestroleinthetransformationoftransport,largelybecause
avoidandshiftstrategieshavealreadybeendeployed.
Inthefaceofsteadilyrisingdemandfortransportservices, the
successoftaxationandsubsidyapproaches inpowerandheat
generationwillprovideasolidfoundationforsimilarlyassertive
policiesintransport.Consequently,transport’soverallenergyusein
theCNSwilldecreasebyover20%comparedto2000,despitea70%
increaseinoverallpassengerandfreightactivity.Underthescenario,
electricityaccountsfor10%offinalenergyuseintransportin2020,
butthankstothehighpowertrainefficiencyofelectricmotors,elec-
tricity’sshareoftransportactivityismuchhigher:64%ofroadand
railpassengerkilometresand42%ofroadandrailfreightactivity.
Furthermore,theCNSrequiresatriplingofthecurrentrateofimprove-
ment inspaceheatingenergy intensityofNordicbuildings.This
willbeachievedprimarilythroughthedeepenergyrenovationof
existingbuildings,whichwillconstitute70%oftheNordicstockin
2050.Energyefficiencygainsinbuildingscanunlockbiomassand
electricityforuseinothersectors,avoidinginfrastructureinvestments
inpowerandheatandCO2emissionsintransportandothersectors.
Nordic Energy Research
NordicEnergyResearchisanintergovernmentalorganisation
supportingandcoordinatingsustainableenergyresearchinthe
Nordicregion.Itistheplatformforcooperativeenergyresearch
andpolicydevelopmentundertheauspicesoftheNordicCouncil
ofMinisters.NordicEnergyResearch’sgovernancestructureis
closelyconnectedtoboththenationalpoliticalsystemsofthe
fiveNordiccountriesaswellastheintergovernmentalNordic
system.Thiscreatesaconstantinteractionbetweenresearch
strategies,resultsandkeyissuesonthepoliticalagenda.For
moreinformation,seeNordicEnergyResearch’sstrategy.
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Recommendations
TheNETP2016stipulatesthatgovernmentswillneed,individually
and inacoordinatedmanner, toplaya leadrole instimulating
actionstoachievethesettargets.Specifically,actionsinfourkey
areasareidentified.Governmentswillneedtostrengthenincentives
for investmentandinnovation intechnologiesandservicesthat
increasetheflexibilityoftheNordicenergysystem.Furthermore,
effortswillberequiredtoboostNordicandEuropeancooperation
ongridinfrastructureandelectricitymarkets.
Itwillalsobenecessarytoensurethelong-termcompetitivenessof
Nordicindustrywhilereducingprocess-relatedemissions.Forthis,
governmentswillhavetoacttoreducetheriskof investment in
low-carbonindustrialinnovationsandusepublicfundingtounlock
privatefinanceinareaswithsignificantemissionreductionpotential
butalowlikelihoodofindependentprivatesectorinvestment.
Finally,governmentsintheregionwillhavetoactquicklytoaccel-
eratetransportdecarbonisationbyusingprovenpolicytoolssuchas
congestioncharges,differentiatedvehicleregistrationtaxes,bonus-
malusregimesandalteredparkingfees.Atthesametimetheyshould
stepupinvestmentsincycling,publictransportandrailnetworks.
Implementationoftheseshort-termpolicyrecommendationswill
createtheframeworkconditionsfortheambitiouspartwayoutlined
bytheCNStobeachieved.
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
OSeMOSYS: opensourcesoftware forenergymodelling
OSeMOSYSisafree,opensourceandaccessibleenergysystems
modelgenerator. Itcangeneratesmallvillageenergymodelsto
globalmulti-resourceintegratedassessmenttools.Itcanbeused
toassessenergysupplysecurity, investmentoutlooks,andGHG
mitigationstrategies.
Ingeneralterms, itcalculateswhat investmentstomake,when,
atwhatcapacityandhowtooperatethemtomeetthesaidpolicy
target(s)atthelowestcost.
Itisthereforeusedtodevelopmodelstoinformpolicydesignandis
partofthelargestHorizon2020LCE21energymodellingresearch
effortREEEM.org.Furthermore,itisusedtounderpinselectedoutputs
oftheDGEnergyInsightEnergy.orgthinktank,andisusedbynational
governmentsintheECandbeyondformediumtolong-termplanning.
OutsideofEurope,itwasusedfortheWorldBankandtheUnited
NationsEconomicCommissionforAfrica.Thereinthedevelopment
(andtradebetween)theelectricitysectorofeveryAfricancountry
wasanalysed.Intheformer,thefocuswasunderstandingthecli-
materesilienceofthesystemunderdifferentfutures.Inthelatter,
thescaleofinvestmentfortheworld’sfastestgrowingcontinent
wasquantified.AsimilareffortforSouthAmericaisbeingusedto
understandthatcontinent’s infrastructuredevelopment.Models
generatedhavebeenbroadanduseful.
OSeMOSYS.orgwaslaunchedatOxfordUniversity in2011ata
UKEnergyResearchCentre (UKERC)meetingandincludedco-authors
fromUniversityCollegeLondon(UCL),theUnitedNationsIndustrial
DevelopmentOrganization(UNIDO),UniversityofCapeTown(UCT),
StanfordUniversity,thePaulScherrerInstituteandothers.Itwasin
responsetotheobservationthatallcountriesneedtoassessthe
quantitativeevolutionoftheirenergysectorsduetoenergy’shighly
strategicroleindevelopment.Atthetimetherewerenoopensource
optimisingenergysystemmodelgeneratorsavailabletodoso.All
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
aspectsofthetoolareopen,thisincludesthecode,themathematical
programminglanguageandthesolversused.
CurrentlyadministeredbyKTH(theRoyalInstituteofTechnology,
Sweden)itsuptakeinanacademicsettingisaccelerating.Scoresof
universities,academicpapersandagrowingnumberofgovernments
aretakingthetooluptouseinacademicandreal-worldanalysis.
Thisbodeswell,asthecommunitycontributingtoitsdevelopment
bothgrowsandaddscriticallyacademicallyreviewedadvances.
Importantly,italsoensuresthatthereareamultitudeof‘service
providers’shouldcommissionedstudiesneedtobeundertaken.
Italsofeaturesaspartofabroader initiative(called Optimus
Community) ledbytheUN.Furtherstarterdata-setsandoffthe
shelfmodelsarebeingdevelopedtohelpmakeopenrevieweddata
availabletobebuiltonrapidly. Initialdatasetsbeingdeveloped
includeallEU,AfricanandSouthAmericancountries.Theaimisto
covertheglobewithpeer-reviewedopenaccessdata.
Whilethere isagrowingcommunityofusersandapplications,a
specialfocusisEurope.FocusingontheSET-Plan,attheheartof
theREEEM.orgprojectareintegratedEuropeanenergysystemmod-
els.OneofthetoolsbeingdevelopedisanOSeMOSYSgenerated
model.Thatmodel(togetherwithamoredetailedMARKAL-TIMES
modeldevelopedbytheUniversityofStuttgart)willdeterminethe
costoptimaltechnologypathwaytomatchsupplywithdemandin
allEUcountriesintechnologicaldetail.Itwillprovidethebackbone
toatailoredevaluationoftheimpactofSET-Plantechnologies.
Todoso,informationfromseveralothermodelsisbeingintegrated.
TheOSeMOSYS-generatedmodelwillfocusonbeinganopen-source
engagementtool.Itwillreplicateandhighlightthekeyunderlying
dynamicsoftheintegratedEuropeanenergysystem.(Thiswillbe
complementedbye-learningtoolstobuildcapacitiesandshare
expertisebasedontheassessmentsperformedinthisproject.)Itwill
enableanswerstoquestionslikewhatresearchfundingandincreased
investmentcostwouldberequiredtomeetSET-Planobjectives,in
additiontosettingoutdetailedsub-targets-andtheirimplications.
ThemodelgeneratorcanbedownloadedfromOSeMOSYS.org.
Therein,resources,papers,datasetsandcodeinthefreemathemat-
icalprogramminglanguageGNUMathProgcanalsobedownloaded.
Recentlythecodehasbeentranslatedintomorethanonelanguage
(or‘technology’)andiscurrentlyavailableinGAMS(apopularlan-
guageamongsteconomists)andPython(awidelyusedopensource
language).YoucansignuptotheOSeMOSYSnewsletteronthe
website,wheretoolsarealsoavailabletodownload.Furthermore,in
thenextfewweeksanewinterfaceistobereleased,andaglobal
summerschoolistobelaunched.
Mark HowellsMark Howells directs the division and holds the chair of Energy Systems Analysis (KTH-dESA)
at the Royal Institute of Technology in Sweden. His group leads the development of some of
the world's premier open source energy, resource and spatial electrification planning tools;
he has published in Nature Journals; coordinates the European Commission's think tank
for Energy; is regularly used by the United Nations as a science-policy expert; and is a key
contributor to UNDESA's ‘Modelling Tools for Sustainable Development Policies'.
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Sharedexperiences in integrated energy systems modelling
Akeychallengeinachievingasuccessfultransitiontoalow-carbon
Europeisimplementingthecorrectsuiteofpolicymeasuresthatare
basedonrobustevidence.Todaypolicy-makersacrossEuropedraw
onintegratedenergysystemmodelstoinformlongrangeclimate
mitigationandenergypolicychoices.EstablishedEuropeanmodels
suchasPRIMES,TIMES,MESSAGE,EnergyPLANandnewermodels
suchasPOTEnCIAandOSeMOSYSconsiderallmodesofenergy
(electricity,heatingandtransport)acrossallsectorsoftheeconomy
inanintegratedfashion,ratherthantreatingindividualmodesin
isolationwhichcanleadtopoorlyinformedinsights.
Ourresearchinintegratedmodellingstartedwithaspecificfocuson
thewiderenergysysteminIreland.WeusetheTIMESintegratedmod-
el,24whichisatechno-economicoptimisationframeworkdeveloped
overthepast40yearsthroughtheInternationalEnergyAgency’s(IEA)
EnergyTechnologySystemsAnalysisProgram(ETSAP).Themodel
allowsuserstogeneratefutureenergysystempathwaystomeet
energyneedsatleastcost,subjecttouserdefinedconstraints.TIMES
optimisesforenergyservicedemands(i.e.theutilitywegetfrom
24 TheTIMESIntegratedEnergyModelofIrelandwasfundedbytheEnvironmentalProtectionAgency(EPA)andSustainableEnergyAuthorityofIreland(SEAI).
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energyuse)suchaslighting,heating,passengerkilometres,tonnes
ofsteelandcementetc.This issignificantbecauseasasociety
wedon’tintentionallyuseenergy,butratherhaverequirementsfor
mobility,lighting,goodsetc.Inall,TIMESconsidersawiderangeof
over1,300technologiesinthetimeframeto2050fromlightbulbs,
cars,fridges,heaters,boilers,powerplants,biorefineriesetc.
Early inourresearchwerecognisedanumberof limitationsto
ourmodellingtechniquesandidentifiedkeyareasthatrequired
improvement.Oneoftheseareaswashowintegratedmodelslike
TIMESdealtwithvariablerenewablegenerationsuchaswindand
solarpower.Manyintegratedmodelshaveasimplifiedtemporaland
technicalresolutionofthepowersysteminordertokeepproblems
computationallymanageable,howeverthiscomeswiththetrade-off
ofpoorrepresentationofvariabilitywithinthemodels.Toresolvethis
issue,wedevelopedsoft-linkingtechniquestolinktheenergysystem
modeltodedicatedpowersystemmodels.Thisallowsustoleverage
thestrengthofhigh-resolutiontechnicalandtemporalpowersystem
models.Indoingthiswecouldaccountforgreatertemporalresolution
(15minuteorhourlysimulations)andalsocaptureimportanttechnical
characteristicsofthepowerplantssuchasramprates,startcosts
etc.WerecentlyexpandedthesetechniquestoincludethefullEU28
powerandgassystemswithwaterasournexttargetfordevelopment.
Thegeographicalexpansionoftheresearchwaspartiallydrivenby
theneedtomodelgreater interconnectedmarkets(bothgasand
electricity)withintheEUandalsotounderstandthedistributionof
effortfordecarbonisationacrossallEUMemberStates.Soft-linking
techniqueshastheadvantagethatitallowsustoverifythetechnical
robustnessofsimulationsbutcomeswiththechallengethatanextra
modelmustbemaintainedanditrequiresmodellerjudgementon
feedbacktotheenergysystemmodel.
Anotherchallengewastheintegrationofland-useandagriculture
intoourmodels.IrelandisuniqueinEuropeasover30%ofGHG
emissionscomefromagriculture.Thisresearchrequiredustowork
closelywithagriculturalscientiststodevelopaframeworkwhere
wecouldaccountfortheseemissionsandmodeltheinteractions,
particularlyforlandusecompetition,betweentheenergysectorand
agriculturalsector.Ourcurrentresearchonlanduseandagriculture
hasanimportantfocusontheroleofbioenergyandtheimplications
ofindirectlandusechange(ILUC)andrecentamendmentstothe
RenewableEnergyDirective(socalled ‘ILUCdirective’).Whilethe
scienceofILUCisatanearlystageourinitialresultspointtoincreased
costsfordecarbonisationwhenILUCisconsidered.
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
Dr Paul Deane Dr Paul Deane is a research fellow with the Energy Policy and Modelling Group in University College Cork in Ireland. He has been working in the energy industry for approximately 15 years in both commercial and academic research. His research activities include integrated energy systems modelling to assess holistic pathways to low carbon energy futures. Paul is also a member of the Insight_E group which is a European, scientific and multidisciplinary think-tank.
LikemanyresearchgroupsacrossEurope,wehaveseenourinte-
gratedmodelsexpandinsizeandcomplexity.Complexityisunavoid-
ableinsuchlargemodelsduetothemulti-dimensionalandintricate
natureofenergysystems,butcomplexityhastobebalancedwith
theinherentuncertaintyin longrangeinputssuchasfuelprices
andmacroeconomicestimations.Thechallengeofmakingmodels
computationallymanageablehasoftenforcedusto lookatour
simplificationsandheuristicsandaskthequestion,“arewemaking
ourmodelsbetterorjustgettingthewronganswerquicker?”Arecent
focusofourresearchistryingtounderstandwhatlevelofcomplexity
isappropriateinlongtermmodelsgiventheuncertaintyininputs,
andtryingtounderstandhowthisvalueofcomplexitydiminishes
aswelookintothefuture.Wehavefounditbeneficialtoexplore
multiplepathwaysandseekoutcommonalitybetweenpathways
ratherthanfocusondeterministicsolutions.
High-performancecomputingoffersexcitingpossibilitiesforfurther
developmentofintegratedmodelling,howevermanyofthecurrent
architectureprocessesarechallengingtoparallelise.Projectslike
‘BEAM-Me’inGermanyareinvestigatingthepotentialforhigh-per-
formancecomputingtoenhanceenergysystemmodels,anditwill
beinterestingtoseewhatdevelopmentsoccur.
Aboveallwehavelearnedthatmodellingthefutureisahumble
scienceandgreatcaremustbetakennottoconfusemodelinsights
forpredictions.Humanbehaviour,economicvolatilityandtechnol-
ogyreadinessarebutasmallsectionofelementsthathavebig
influenceonresultingpathwaysfrommodels.Wemustbeaware
thattheboundariesoftheenergysystemdon’tstopattheendof
thepipelineorcable;theyextendintoourlives,communities,and
wellbeing.Currentmodellingeffortsprimarilyhaveatechno-eco-
nomicfocus,howeverthechallengeofdecarbonisation,andmore
recentlythegreaterlevelofdecarbonisationrequiredbytheParis
Agreementwillrequireourmodellingcommunitytolookoutwardto
otherdisciplinestoinformpathwaysthatweasasocietyarewilling
totravelontogether.
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
What does Energy System Integration involve and what value does it bring?
Energy Systems Integration (ESI) is the process of coordinating
the operation and planning of energy systems across multi-
ple pathways and/or geographical scales to deliver reliable,
cost-effective energy services with minimal impact on the
environment.
Energysystemshaveevolvedfromindividualsystemswith little
ornodependencies intoacomplexsetof integratedsystemsat
scalesthatincludecustomers,cities,andregions.Thisevolutionhas
beendrivenbypolitical,economic,andenvironmentalobjectives.As
wetrytomeetthegloballyrecognisedimperativetoreducecar-
bonemissionsthroughthedeploymentoflargerenewableenergy
capacitieswhilealsomaintainingreliabilityandcompetiveness,
flexibleenergysystemsarerequired.Thisflexibilitycanbeattained
throughintegratingvarioussystems:byphysically linkingenergy
vectors,namelyelectricity,thermal,andfuels;bycoordinatingthese
vectorsacrossotherinfrastructures,namelywater,data,andtrans-
port;byinstitutionallycoordinatingenergymarkets;and,spatially,
byincreasingmarketfootprintwithgranularityallthewaydownto
thecustomerlevel(Figure11).
ESIisamultidisciplinaryarearangingfromscience,engineering,and
technologytopolicy,economics,regulation,andhumanbehaviour.
ItisthisfocussimultaneouslyonbreadthanddepththatmakesESI
suchachallengingandexcitingarea.
ESIisoneofseveralglobalsocialandengineeringtrendsthatwill
shapethesolutionstothekeychallengesofthenextdecades:
resourcestress,climatechange,megacities,urbanisation,cyberse-
curity,andinfrastructureresilience.ESIisanumbrellaconceptthat
encompassesactivitiestackledinthecontextofsmartgrids(grid
MarkO’MalleyDirectoroftheInternationalInstituteforEnergySystemsIntegration
TALKS TO SETIS
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
modernisation)andsmartcities.However,thesetwoapproachesare
morelimited,withonefocusedonasingleenergyvector(electricity)
andtheotherlimitedingeographicalscaletoacity–sotheymay
missimportantopportunitiesthatcanarisebyconsideringallenergy
vectorsandallscales.
The value of ESI is in coordinating how energy systems
produce and deliver energy in all forms to reach reliable,
economic, and or environmental goals at appropriate scales.
Analysis and design of integrated energy systems can inform
policymakers and industry on the best strategies to accom-
plish these goals.
What are the principal objectives of the European Energy Research Alliance, Joint Programme on Energy Systems Integration and the International Institute for Energy Sys-tems Integration?
TheimportanceofESIisbeingrecognisedglobally.Mostsignificantly,
ESIisacentralthemerunningthroughtheEuropeanCommission’s
StrategicEnergyTechnologyPlan(SET-Plan)IntegratedRoadmap.
It isalsoacentralthemeoftheCleanEnergyMinisterialanda
majorresearchthemewiththeU.S.DepartmentofEnergynational
laboratorycomplex.
InFebruary2014theUSDepartmentofEnergy,NationalRenew-
ableEnergyLaboratoryandPacificNorthwestNationalLaboratory
co-hostedaninvitationonlyworkshoponESI inWashingtonDC.
Therewere40seniorlevelattendeeswith29fromtheUS,10from
EuropeandonefromChina.Theworkshopwasdesignedtovalidate
theimportanceofESIasanemerginginterdisciplinaryscientificarea
andgaugetheappetitefortheestablishmentofaninstitute–the
InternationalInstituteforEnergySystemsIntegration(iiESI).Itwas
agreedbyallparticipantsthatESIisanimportantandemergingarea
andthatforminganorganisationsuchasiiESIwasverypositiveand
timely.TheroleandvalueofiiESIinfosteringinternationalcollabora-
tion,stimulatingthesharingofknowledgeandprovidingindependent
analysiswasrecognisedbyall.TheindependenceofiiESIwasseen
asafundamentalcharacteristic,inparticularwithrespecttovaluing
ofparticulartechnologies/solutionsdeployedintheenergysystem.
iiESIasaformalorganisationcameintobeinginJuly2016asa
globalinstituteaimedattacklingthechallengesofenergysystems
integrationthroughglobalcollaborationandeducation.Formalising
iiESI as a global, member-driven organisation of leading ESI
scholars and practitioners provides a structure for leveraging
each other’s experiences and expertise, coordinating research
agendas, and sharing best practices from around the world.
Theestablishmentofaformal institutewillallowthegroupto
expandandgrowtomeetthechangingneedsoftheESIcommunity.
Figure 11: Energy Systems Integration
Source: iiESI
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ThereisalsoanewEuropeanEnergyResearchAlliance(EERA)Joint
Programme(JP)inESI.AnEERAJPiscreatedbyinterestedorgan-
isationsthatdefineajointresearchagendaforatopicincludedin
theSET-Plan.EERAJPscoordinateresearchbasedonthepartic-
ipating institutionsownresources. Inaddition,theJPcanobtain
supplementaryfundingfromnationalorEUsources.Theaimis
tograduallyincreasetheamountofdedicatedfundingtotheJPs.
ThiswillallowaJPtowidenanddeepencoordination.EERA JP ESI
seeks to bring together research strengths across Europe to
optimise our energy system, in particular by benefiting from
the synergies between heating, cooling, electricity, renewable
energy and fuel pathways at all scales.Theenergyelementsof
thewaterandtransportsystemarealsoincluded,asistheenabling
dataandcontrolnetworkthatenablestheoptimisation.TheEERAJP
ESIisdesignedtodevelopthetechnicalandeconomicframework
thatgovernmentandindustrieswillneedtobuildthefutureefficient
andsustainableEuropeanenergysystem.
What are the main ESI research challenges and how can they be overcome?
InMarch2015,ImperialCollegeLondonhostedaniiESIworkshop,on
ESIResearchChallenges.Thiswasattendedby38expertsfromEurope,
USA,Africa,Asia,RussiaandAustralia.Thedisciplinesrepresented
rangedfromEngineering,Economics,SocialSciences,Mathematicsand
Physics,andindustrywasalsorepresented.Notsurprisinglyoneofthe
mainoutcomesoftheworkshopwasthe“needtocombineeconomic,
social,andpoliticalperspectiveswithengineeringknowledge”.The
needforeducationanddisseminationfeaturedstrongly.Intryingto
identifyresearchchallengeshowever,theneedforcleardefinitionsof
ESIandof“optimality”inanintegratedenergysystemwasapparent.
Therewaslittleornoconsensusontheoptimalityissuedespitesome
followupteleconferencesandemailexchanges.
EachenergysystemwillapproachESIfromadifferentstartingpoint
(e.g.,anurbanareainthedevelopedworldwillhaveadifferent
approachcomparedtoaruralareainthedevelopingworld).It is
crucialtodefinethegeographicalscopeaswellasthecomponents,
theboundaries,andtheinfluenceofthesurroundings.Forexample,
renewableintegrationisthedrivingforceofESIinmanyregions,but
notall.Insomeregions,themaindriversareincreasedcombined
heatandpower(CHP),increasedefficiency,ashiftfromcoalgen-
erationtonaturalgas,orsimplyelectrification.Differentincentives,
decision-makingprocesses,andaccesstocapitalduetolocation
orscalewillresultinverydifferentenergysystemsandapproaches
toESI(e.g.,agovernmentcaninvestinhigh-voltagetransmission,
whileindividualswillnot).Aseachenergysystemdevelops,itwillbe
necessarytoconstantlyre-evaluatethesysteminordertoassess
howitisbestcoordinated.
DevelopingcoordinatedsystemsthroughESIanalysisrequiresa
properunderstandingofthedifferentactors involved,alongwith
theirmotivations,their incentives,andtheinformationtheyhave
accessto.Fromawhole-systemperspective,theactors ineach
energydomaintendtoactontheinformationtheyhaveinways
thatmaximisebenefitsfortheirdomain,butnotfortheentireenergy
system.Forexample,eachuserconsumesbasedontheirown
requirements,eachmarketvaluescertainfinancialoutcomes,and
eachgovernmentservesitsownsocialorpoliticalmotivations–but
theremaybenocoordinationacrossthesedomainstodetermine
thebestoptionforallactorsinvolved.Pooroutcomescanpotentially
arisefromthislackofinformationand/orcoordination,andmaynot
bemonetaryinnature;apoorlyexecutedenergytransitioncould
resultinenergysystemsthatlacktechnicalintegrity,socialequity,
and/orpoliticalacceptability.
TheconsiderationsthatgovernESIarenumerousandcomplex,
andtheoutcomesandtheirvaluecanbedifficulttodefine.Oneof
thefirststepstodeterminethisvalueistodefineasetofrobust
metricsspanningtheengineeringandsocialsciences(e.g.,financial
impacts,emissionscosts, resiliency,publichealthconsiderations,
socialutility,etc.)tomeasureandhighlightthevariousbenefits.
Anysetofdefinitionsormetricswillhavetobeflexibleenoughto
accommodateawiderangeofcircumstances.Metricsalsoneedto
besimpleenoughtoallowforanoverallholisticunderstandingof
howthedifferentaspectsinteract.
The main outcome of the London Workshop is the need for the
global research community to adopt a common and clearly
understood common language and consensus on the scope
of the ESI. This is needed before a detailed interdisciplinary
research roadmap for ESI can be articulated with confidence.
BecauseESIisabroadtopicthatincludesalltypesofenergysources
andend-useapplications, it ishelpfultocategoriseexamplesof
ESIintoafewareas.HereweprovideseveralexamplesofESIthat
havebeenorganised intothree“opportunityareas”:streamline,
synergise,andempower.
Streamlinereferstoimprovementsmadewithintheexistingenergy
systembyrestructuring,reorganising,andmodernisingcurrentenergy
systemsthroughinstitutionallevers(i.e.,policies,regulations,and
markets)or investment in infrastructure. Increasingtheflexibility
ofenergyendusehaspotentialsystem-widebenefitsandcould
createnewmarketsforproductsandservices.However,capturing
thesebenefitswillrequireproperregulatoryandmarketstructures,
newoperationalandplanningparadigms,physicalenergynetwork
characteristics,anintegratedcommunicationssystem,andsuitably
flexibleend-useproducts.Manyofthesearecurrentlylackinginthe
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existingenergysystemandrequireasystem-wideunderstanding
todeliverpragmaticandsustainablesolutions.Developingmore
integratedenergysystem-widepolicieswillenablebettermanage-
mentofuncertainties.
Moreintegratedenergynetworksandproperfunctioningreal-time
locationalmarketswillrewardcapacityandflexibility.Inaddition,the
removalofinstitutionalbarriersbetweendistributionandtransmission
systemswillallowbetterintegrationofdistributedresourcesand
facilitateregional integration.Byprovidingstandardisedrequire-
ments,updatedinterconnectionandinteroperabilitystandardsand
gridcodeswillstreamlinetheenergysector.
Investmentintheappropriateinfrastructurewithintheintegrated
energysystemwill improveflexibility.Expansionoftheelectrical
transmissiongridwillenableflexibilitybyaggregationacrossscales.
Pipelineinfrastructureisrequiredtoincreasethepenetrationofbio
and/orsyntheticfuels.Investmentindatainfrastructurewillenable
consumerstomorefullyparticipateintheenergysystemandwill
improveenergynetworkoperationsthroughforecastingandanalytics.
SynergisedescribesESIsolutionsthatconnectenergysystems
betweenenergydomainsandacrossspatialscalestotakeadvantage
ofbenefitsinefficiencyandperformance.Todate,thecouplingof
heatandelectricitysectorshasfocusedonthesupplyside(e.g.,CHP)
forfuel-savingpurposes.However,atthesystemlevel,itsinherent
inflexibilitycanleadtosub-optimaloverallsystemperformance.A
goodexampleofthisiswindcurtailmentinChina,whichisinpartdue
totheinabilityofphysicallyinflexibleCHPplantstoreduceelectricity
productionwhileprovidingheat.ESIsolutionsthatintegrateheat
storageintotheCHPplantarebeingdevelopedandindicateashift
fromthesupplysidetothedemandside(e.g.,electricalheatingof
water,thermalstorageinbuffersandheatpumps). It ispossible
tocapitaliseon“virtualstorage”wheretheflexibility inonepart
ofthesystem(e.g.,heat,transport,water,etc.)canbeintegrated
with,forexample,theelectricitysystem,andusedinasimilarman-
nertoelectricitystorage.Thisvirtualstoragecanbesignificantly
cheaperthandedicatedstorage,asitdoesnotrequirelargecapital
investment–butitdoesrequireamoreintegratedenergysystem.
Demandmanagement(e.g.,controllingheatingandcoolingloads)
technologiescurrentlybeingdeployedanddevelopedare inpart
leveragingthisvirtualstorage.However,ESIproposesthatitisata
grandscalewherefuel,thermal,water,andtransportsystemswill
besystematicallyplanned,designed,andoperatedasflexible“virtual
storage”resourcesfortheelectricitygrid(andviceversa).Thereis
alsothepotentialtousethenaturalgasfuelgridtocreateenergy
storagethroughthe“power-to-gas”concept.
EmpowerreferstoESIactionsthatincludetheconsumer,whether
throughtheirinvestmentdecisions,theiractiveparticipation,ortheir
decisionstoshiftenergymodes.Investmentsinenergyefficiencyare
increasinglyrecognisedasacost-effectivewaytoreduceenergy
demandandcanleadtosystem-widebenefitsthatincludeupstream
capitalandoperationalsavings.Fromanoverallenergysystempoint
ofview,energyefficiencyatthelevelofanindividualbuildingmay
beinconflictwiththeflexibilitythatthedemandsidecanprovideto
thegrid.Energyefficiencyimprovementsortargetsalsocontributeto
broadersocialandpolicygoals,notablymacro-economicefficiency,
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S E T I S M a g a z i n e N o v e m b e r 2 0 1 6 - E n e r g y S y s t e m s M o d e l l i n g
industrialproductivity,publicbudgetbalance,securityofsupply,and
healthbenefits.Thisbuilding-levelinvestmentneedstobemade
bytheconsumer.Theformerlytotallyseparatedsectorsoftrans-
portandelectricitymaybecomemoreintegratedthroughplug-in
electric(hybrid)vehiclesandcarbatteries,buttheconsumerneeds
toacceptthismodeoftransport.Thepotentialinsomeregionsfor
thermalgridshasbeenraised,butquestionsremainastohowlarge
theyshouldbe,howbesttointegratethemintotheelectricitygrid,
and,importantly,howconsumerrequirementswillbeensuredand
whetherconsumerswillacceptthem.
What is the role and main requirements of modelling in ESI?
ModellingplaysacriticalroleinESIresearch.Modellingisameans,
notagoalinitself.
ESIismostvaluableatthephysical,institutional,andspatialinter-
faces,wherethereareinteractionsandnewchallengesandoppor-
tunitiesforresearch,demonstration,anddeploymenttoreapits
commercialandsocietalbenefits.Thereforetheseinteractionsmust
beunderstood,quantified,analysedandthensolutionsdesigned
anddeployed.Asthesystemsarecomplex,typicallydistributed
withphysical,economicandregulatoryaspects,itisonlypossible
toinvestigatethemeffectivelyandatreasonablecostbyusinggood
models.Thesemodelsneedtofocusontheinterfacesandwillneed
torepresentallmajorenergyproducingandconsumingsectors
withsufficienttemporalandgeographicalgranularitytobeableto
trulyrepresenttheESIchallengesandopportunities.Ofparticular
importanceisuncertaintyinoperationsandininvestmenttimescale,
whichneedstobecaptured.Theneedforhighqualitydatacannot
beoveremphasised.Modelsareonlyasgoodasthedatathatis
usedtotunemodelparameters,validatemodels,developscenarios
andinputdatasetsetc.
Mark O’Malley Mark J. O’Malley received B.E. and Ph.D. degrees from University College Dublin, Ireland, in 1983 and 1987, respectively. He is the Full Professor of Electrical Engineering at University College Dublin, is the Director of the University College Dublin Energy Institute and Electricity Research Centre and is a member of the Royal Irish Academy. He is also the Director of the International Institute of Energy Systems Integration and the coordinator of the European Energy Research Alliance Joint Programme in Energy System Integration. His research area is energy systems integration in particular grid integration of renewables.
Thesemodelsallowustoaddressunanticipatedfeedbacksinthe
system,identifyefficientstrategies,evaluatepossiblemarketdesign
andpolicies,etc.Modellingisneededtounderstandhowtoachieve
costeffective integrationofenergysectors,whatarethemost
promisingnewpathwaysandtechnologiesandhowthesystem
performancemaychangeunderdifferentscenariosandpolicies.
Modellingthereforeneedstosimulatethephysicalsystemaswell
astheenergymarket,regulatoryframework,underlyinguncertainty
inweatherandlonger-termresourcesandallthewaytoconsumer
behaviour,andhowtheactors’decisions(operationalandinvestment
decisions)affecttheperformanceofthephysicalsystem,andhow
regulationaffectstheactors’decisions.
Anextremelywidesetofdiversemodelsdoexist.However,focus
typicallyisonsectorsandenergycarriers,individually.Overallenergy
sector(oreconomywide)modelsexist,butoftenlacktechnicaldetail,
crucialtoaccountforthevariabilityofrenewableenergysources
suchaswindandsolarphotovoltaic.ThescopeofESImodelsneeds
tobelargerthanthatoftraditionalmodels.Theidealmodelwould
includealltheabove-mentioneddimensions,thephysicsaswellas
themarket,butthisisneitherfeasiblenorpractical.As a result,
the challenge is to develop a suite of models than can be
used together. Preferably this should be made in a way that
enables much better co-operation between model developers
and users across the globe. Well-defined interfaces between
models, open source code and high quality open source data
would help to avoid duplicate effort.Differenttypesofmodels
areneededfordifferentquestions:simulationandoptimisation,
shorttermandlongterm,physicalandmarketmodels.
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