1Pursuingalow-carbonruralenergytransitioninChinaandGermanyPerspectivesonself-sufficiencyandsectorcouplingfromtwovillagesSino-GermanEnergyTransitionProject2ImprintThereportPursuingalow-carbonruralenergytransitioninChinaandGermanyintroducestheresultsofparallelstudiesofru-ralvillagesinGermanyandChinawithpotentialforalow-carbon,cleanenergytransition,andmakespolicysuggestionsrelatedtopromotingcleanenergypoliciesthatcouldacceleratethattransition.ThereportispublishedintheframeworkoftheSino-GermanEnergyTransitionproject,aspartoftheSino-GermanEnergyPartnershipbetweentheGermanFederalMinistryforEconomicAffairsandClimateAction(BMWK)andtheNationalEnergyAdministrationofthePeople’sRepublicofChina(NDRC).TheDeutscheGesellschaftfürInternationaleZusammenarbeit(GIZ)GmbH,AgoraEnergiewende,andtheGermanEnergyAgency(DeutscheEnergie-Agentur,ordena)jointlyimplementtheprojectundercommissionofthepoliti-calpartners.AsaGermanfederalenterprise,GIZsupportstheGermangovernmentintheachievementofitsgoalsininternationalcoop-erationforsustainabledevelopment.PublishedbySino-GermanEnergyTransitionProjectcommissionedbytheGermanFederalMin-istryforEconomicAffairsandClimateAc-tion(BMWK)TayuanDiplomaticOfficeBuilding1-15-1,14LiangmaheSouthStreet,ChaoyangDistrict100600Beijing,P.R.Chinac/oDeutscheGesellschaftfürInternationaleZu-sammenarbeit(GIZ)GmbHTorstenFritscheKöthenerStr.2Berlin10963ProjectManagement:AndersHove,DeutscheGesellschaftfürInternationaleZusammenarbeit(GIZ)GmbHAuthors:BingXue,HongqingLi,ChineseAcademyofSci-encesInstituteofAppliedEcologyMichaelPopp,MarkusZdrallek,JessicaStephan,SvenPack,WuppertalUniversityUlrichJansen,ThorstenKoska,WuppertalInstituteAndersHove,PhilippGeres,GIZDesign:XuelingLiu,GIZedelman.ergo(oncommissionofBMWK)Image:BMWK/Cover,P11Shutterstock_108342809/P5Shutterstock_326698985/P20AdobeStock_478467898/P47©Beijing,May2022Thisreportinitsentiretyisprotectedbycopyright.Theinformationcontainedwascompiledtothebestofourknowledgeandbeliefinaccordancewiththeprinciplesofgoodscientificpractice.Theauthorsbelievetheinformationinthisreportiscorrect,completeandcurrent,butacceptnoliabilityforanyerrors,explicitorimplicit.Responsibilityforthecontentofexternalwebsiteslinkedinthispublicationalwayslieswiththeirrespectivepublishers.Thestate-mentsinthisdocumentdonotnecessarilyreflecttheclient’sopinion.GIZacceptsnoresponsibilityforthesemapsbeingentirelyuptodate,correctorcomplete.Allliabilityforanydamage,directorindirect,resultingfromtheiruseisexcluded.3ContentsExecutivesummary.......................................................................................................................4Introduction....................................................................................................................................6ComparingDongqiaotouandSchwaig.......................................................................................8Schwaig,Bavaria...........................................................................................................................................................................................8Dongqiaotou..................................................................................................................................................................................................9ComparisonofSchwaigandDongqiaotou............................................................................................................................................10CurrentsituationandpolicyframeworkinChinaandGermany........................................13PoliciesinGermany....................................................................................................................................................................................13PoliciesinChina...........................................................................................................................................................................................13Methodsandanalysis..................................................................................................................15Analysis–Schwaig....................................................................................................................................................................................24Researchquestions,assumptionsandmethodologies-Dongqiaotou...........................................................................................32Surveyresults-Dongqiaotou..................................................................................................................................................................37Analysis-Dongqiaotou............................................................................................................................................................................39Discussionofdifferencesbetweenthetworesearchapproaches....................................................................................................45AvillageinGermanyandChinaintheyear2030.................................................................46Policyrecommendations...........................................................................................................47Conclusions...................................................................................................................................51Annexes..........................................................................................................................................53References....................................................................................................................................564ExecutivesummaryRuralareasplayavitalroleinthelow-carbonenergytran-sition,giventheirampleopenspace,andconsiderableen-ergyconsumption.Yetmuchoftheanalysisoflow-carbontechnologyadoptionorlow-carbonenergysystemfore-castingomitsmentionofruralcommunities,focusingin-steadonwealthier,urbanresidentsoroverallinstallationsofutility-scalerenewableenergyorstorage.Forthisstudy,theSino-GermanEnergyTransitionprojectbroughttogetherscholarsofenergymodellingandruralecologytoexaminethequestionofhowcleanenergytech-nologywillaffecttheenergyflowsandcarbonemissionsofruralareasinGermanyandChina.Thisreportdescribestheresultsofcasestudiesoftworuralvillages/towns—DongqiaotouinShandongprovince,China,andSchwaiginBavaria,Germany—toexaminethequestionofhowtoac-celeratethecleanenergytransitioninareas,andtoiden-tifythepotentialforruralcommunitiestobecomemoreself-sufficientintheirenergysupplytoenhanceresilienceandlowernetworkcosts.InthecaseofDongqiaotouvillageinShandongprovince,avillage-scalesurvey,semi-structuredinterviews,andacombinationoftop-downandbottom-upanalysisenableddevelopmentofanenergyflowmodelandscenarioanaly-sisofthevillage’scurrentandfutureenergysystem.Theanalysisfindsthatthevillagehasapotentialtomeetalargeshareofitselectricpowerandheating/coolingde-mandviasolarPVandheatpumps(whichprovidebothheatingandcooling).Withagrowingshareofelectricve-hicles,villagerscansavemoneyforfuelbyusingsolaren-ergyforchargingduringdaytime.Acceleratingthevil-lage’splanstoadoptPVpanelsandsolarstreetlightswillnotonlybenefittheresidentsthroughreducedenergycosts,butalsopromotethedevelopmentofalow-carbonsociety.Storageforelectricityandheatcouldfurtheren-hanceself-sufficiencyinthefuture.InthecaseofSchwaig,acombinationofvillage-scalesur-veydata,energydatafromlocalutilities,andscenarioanalysisenabledtheconstructionofanenergyflowmodelandscenarioanalysis.ThereportfindsthatSchwaighasahighpotentialtofurtherincreaseitsalreadyhighdegreeofcleanenergyself-sufficiency,throughtheadoptionofres-identialheatpumpsandelectricvehicles.However,sea-sonalenergystorageandbalancingfromthegridwillstillbenecessary.Overall,thetwovillages/townshavecommonalitiesintermsofthepotentialforcleanenergy,eventhoughtheyexhibitmarkeddifferencesintermsofincome,occupa-tions,andcurrentfuelsforheatingandpower.Fromourscenarioanalysisandprojections,weconclude:Distributedenergyandself-sufficiencyareattractiveinbothGermanyandChina:InGermany,adoptionofdis-tributedsolar,electricvehicles,andheatpumpsislikelytocontinue,givingtheregion’shighpotentialforenergyself-sufficiency.Similarly,wefindthatDongqiaotouhasthepotentialtoincreaseitsself-sufficiencywithEVsandPV,evenasitsenergyconsumptionrisesmorerapidlyduetorisingincomes.InGermany,heatpumpsandinsulationcouldhelpreducetheimpactofsolarvariability:Adoptionofdistributedcleanenergywillalsomakedailyelectricitysupplyandloadsmorevolatile,giventhatPVcouldsupplyuptoafourthoflocalenergyproductionandfarexceedthetotalhouseholdmonthlyloadinsummer.Weestimatethatheatpumpsandwell-insulatedGermanhouseshavehighpo-tentialforsmoothinghouseholdnetloads.WhileheatpumpadoptioninOberdingispresentlylow,62%ofhomescouldhaveheatpumpsinstalledby2035accordingtothedena95scenario.EVadoptionandtimedchargingcouldplayarole,butitisfarsmallergiventhattheEVloadisexpectedtobejust4-5%oftotalenergyconsumption,comparedto16-17%forheatingandcooling.InChina’sruralareas,distributedenergytechnologyadoptionismoreuncertain,buthashighpotential:InChina,bioenergywillcontinuetoplayalargerroleinboostingthevillage’srenewableenergyuptake.WhilethereisuncertaintyaboutadoptionofdistributedPV,heatpumps,orEVs,scenariosandestimatesemployedinthisstudysuggestthatby2030thesetechnologieswilllikelyhaveasignificantlylargerpresence,particularlyPV.Heatpumpsarealreadyeconomicalforthosehomesthatre-quirebothcoolingandheating.Undertheexistingdevel-opmentmodel,thevillagewas16.8%energyself-suffi-ciencyratein2020.Underanoptimisticdevelopmentsce-nario,theenergyself-sufficiencyratescouldreach80.70%in2025and126.16%in2030.TheanalysisinbothChinaandGermanyemployedamixedapproachthatquantifiesthepresentenergyproductionandconsumptionbasedonexistingdatasets,estimatesfromnationalorregionaldata,datafromthedistributiongrid(intheSchwaigcase),andhouseholdsurveys.Forthehouseholdenergysurveys,inSchwaig/Oberdingthesur-veyresponseratewas19%,andinDongqiaotou18.8%.5ScenariosforPV,EV,andheat-pumpadoptioncombinemultiplesourcesincludingdiscussionwithlocalofficialsandexperts,dena,Agora,BDI,andBWPforGermany.ForChina,scenariosincludeinformationfromlocalsurveys;analysesonexpectednationalandregionaldevelopmentofEVsandheatpumpsservedasabasisforestimatesonvillagelevel.Themodellingapproachesandmethodologiesthatthere-searchersappliedinthetwovillagesdiffer,andthereforetheresultingestimatesonenergyself-sufficiencyforbothvillagesarenotdirectlycomparable.Forinstance,inDongqiaotoutheresearchersconsideredagriculturalwasteandallenergyconsumption,whereasinSchwaigtheanalysisonlyconsideredgridelectricityandhouseholdelectricity.Theruralenergytransitionisanimportantpolicypriorityforbothcountries,giventhatruralcommunitieshaveanimportantpositivecontributiontomaketotheenergytransition,andpolicymakerswanttoensurethebenefitsoftheenergytransitionreachruralcommunities.Inthefuture,studieslikethiscanenablegreaterawarenessamongruralresidentsandfacilitateexchangewithpolicymakersabouthowtoensureajustenergytransitioninru-ralareas.6IntroductionItiscriticalthatruralareasbothparticipatein,andbenefitfrom,thelow-carbonenergytransition.China’senergytransitiontodatehasinvolvedmassivedeploymentofwindandsolar,efficiencyupgradestothecountry’scoalplantsandindustry,andcommercialisationofnewenergytechnologyinfieldssuchaselectricvehiclesinmajorcities.InGermany,whichwasoneofthefirstcountriestodeploywindandsolarenergyatscale,ruralcommunitieshavebenefitedfromownershipinruralenergyfacilities.Tore-alisetheenergytransition,bothcountriesarelikelytoac-celeratetheirdeploymentofrenewables,electrificationoftransportandheating,andreplacementoffossilfuelheat-ingwithelectricheatpumpsorotherlow-carbonoptions.Howthiswillaffectruralresidentsisanopenquestion,es-peciallygivenconcernsthatthetrendtowardselectrifica-tionmightentailmajorupgradestoruraldistributiongrids.Ifdistributedenergyandstorageenablegreaterself-reli-ance,thiscouldbenefitlocalareasbothbyreducinginfra-structurecosts,andtherebyloweringgridcharges,aswellasimprovingoverallruralclimateresilience.ChinaTheenergytransitiondiscussioninChinasometimesfo-cusesmainlyontheenergyindustryoronurbanareas.Inthecontextofrapidurbanisation,itiseasytooverlookthecountry’svastruralareaseventhoughtheystillarehometoover509millionpeople,accountingfor36%ofthetotalpopulation.AchievingtheenergytransitioninruralareasisanimportantpartofrealisingChina’snationalstrate-giesandtargets,suchastheEnergyRevolution,RuralRe-vitalisation,theBeautifulChinaStrategy,andcarbonpeakingandcarbonneutrality.RuralareasinChinafacechallengessuchasanagingpop-ulation;soilandwaterpollution;andalargeincomeandwealthgaptolargercities.RuralareasinChinahavelowerincomesandoftenrelyonoldertechnologiessuchastwo-strokedieselthree-wheeledvehiclesorheatingwithloosecoal(散煤inChinese)orbiomass.Manyvillagesemployolderbuildingpracticeswithpoorinsulation.Smallertownsoftenhaveminimalconnectionstothepowergrid.YetChinaisfocusingonraisingthelivingqualityofruralareas,andthecleanenergytransitionispartofthatpro-cess—withthepotentialforimprovinglocalairqualityandtheefficiencyofdailylifetasks.Thoughruralareasuselessenergypercapitathanurbanareas,itisneverthelessim-portantthattheyalsoplayaroleincarbonneutrality—notjustthroughlargeenergyprojects,butalsothroughdis-tributedcleanenergytechnologiesandenergyefficiencyupgrades.GermanyGermany’senergytransition,incontrasttoChina’s,earlyonfocusedoninvolvingruralareasindeployingcleanen-ergy.ThefirstimpetusforGermany’senergytransitioncamefromtheoilcrisesofthe1970s,butacrucialturningpointwasthe1997KyotoProtocol,whichsetthefirstcli-matepolicytargetsfortheindustrialisedcountriestore-ducegreenhousegasemissions.1Accordingtothis,theEu-ropeanUnion(EU)setclimate,renewableenergy,anden-ergyefficiencytargetstoreducegreenhousegasemissionsin2007.TheEUhassteadilytightenedandupdateditstar-getsunderthe2015ParisAgreementandtheEUGreenDeal.2AfterthereactorcatastropheinFukushima2011,Germanydecidedonafasterphase-outofnuclearenergyby2022.3In2020,theGermangovernmentdecidedtoshutdownallcoal-firedpowerplantsby2038atthelatest,whilethenewFederalGovernmentthattookofficeinDe-cember2021intendstodosoby2030.4Germanyaimstobecomeclimateneutralby2045.Germanyonlycanachievethesegoalswithalargeamountofrenewableenergyandamassiveexpansionofdistrib-utedenergyresources(DERs).Thesetargetsalsoimplyelectrifyingthetransportandheatingsectors,whichtodaymainlyrelyonfossilfuels.Thistransitionwillfurtherin-creaseelectricitydemand,whichalsounderlinestheim-portanceofinstallingasmanydistributedrenewablesaspossibletoreducetheneedforimportedenergyandnet-workupgrades.Distributedwindandsolarareatthefore-frontoftheGermanlow-carbonenergytransition,oftenowneddirectlybyindividualsorsmallcommunities.ButtheGermanruralenergytransitionisalsoaworkinpro-gress.Ruralareashaveampleroomtoadoptelectrictrans-portationandefficientheatingandcooling,forexample.ComparisonofruralenergytransitionsTheenergytransitioniscreatingopportunities,especiallyinruralareas.RuralareasinChinaandGermanyoftenhavemorelocalrenewableenergyresourcesandmorespacefordeployingrenewableenergygenerationtechnologiesthanurbanareas.Hence,theyhaveapotentialforachievinga7highdegreeofself-sufficiencyfromtheirlocalrenewableenergyresources.Ingeneral,ruralareasoftenhavevariousstructuralweak-nessescomparedtourbanareas,reflectedinlowerin-comesandfewerjobs.Forexample,inBavariain2019,thepercapitaincomeinruralregionswasabout9.3%lowerthaninurbanareas.5Inthisstudy,weseektounderstandandcomparetheverydifferentcleanenergyfuturesofGermanandChinesetownsandvillagesbybothquantifyingtoday’senergypro-ductionandconsumption,andbyanalysingfutureenergyscenarios.WeexaminethetownofSchwaiginBavaria,lo-catedneartheMunichairport,andDongqiaotouinShan-dongprovince.Bothareagriculturaltowns,buttheGer-mancommunityhasafarhigherper-capitaincomethantheChinesevillage,aswellasmoredistributedenergyin-stalled.Dongqiaotoureliesheavilyoncoal,electricity,andoil,buthasinstalledsolarwaterheatingonmosthouses.ThetownhasminimalPV,withjustaround5%ofhouse-holdshavingPVinstalled.Bothvillages,despitetheirdifferentdevelopmentstates,arepartoftheirrespectivecountries’energytransitionsandwillundergochangesinthisdecade.Thisstudyaimstocontributetounderstandingthepossibledirectionofthesechangesandthevillages’potentialstomakeanam-bitiouscontributionintheirrespectivecontexts.8ComparingDongqiaotouandSchwaigSchwaig,BavariaThevillageofSchwaigislocatedintheGermanstateofBa-varia,about30kmnortheastofMunich.SchwaigbelongstothecommunityofOberdingwhichconsistsofsixsmallervillages:Aufkirchen,Niederding,Notzing,Oberding,Schwaig,SchwaigerlohandSchwaigermoos.MunichAirportisalsopartofthecommunityofOberding.6Atotalof6,455peopleliveinthecommunity,1,140ofwhomliveinSchwaig.7Themapbelowshowsthecommu-nityofOberdingwiththedifferentlanduses.Figure:QGISmapofOberdingwithlanduseindicatedSource:WuppertalUniversity,2021Schwaighasahighproportionofresidentialspaceandalowproportionofcommercialspace.Itismostlysur-roundedbyagriculturalland.Intotal,253residentialbuildingsoutofthetotalof1,416residentialbuildingsinthecommunityofOberdingcanbeassignedtoSchwaigus-ingthepopulationkey.8Schwaighasrelativelyfewindus-trialandcommercialbusinesses,withjustaround30com-paniespresentinSchwaig.Mostlocalcompanieshavetiestotheairport,suchashotels,commercialparkinglots,orlogisticsandtransportcompanies.9Agriculturebusinessesarenotincludedinthisanalysis,astheyarenotlistedintheChamberofCommerceandIndustry.However,thelandusemapshowsthatthereareagriculturalbusinesseslocatedinthearea.Theaveragepercapitaincomeintheregionisaround€25,000.10BasedondataofE-WerkSchweigeroHG,asoflate2021Schwaighad978kWofPVinstalled.privateresidencescommerce,industryagriculture9DongqiaotouDongqiaotouVillageissituatedinShandongProvince,200kmfromtheprovincecapitalcityofJinanandcirca350kmfromtheimportantcoastalcityofQingdao.Thevillagehas446householdswithatotalpopulationof1,832.Thepop-ulationlivingoutsidethevillageis380,including210workingpeople,170attendingschool,andaround40-50peopleworkinginthevillageandnearbycompaniesorfac-tories.AnnualincomepercapitaisRMB22,500,equivalenttoroughly€3,000.Figure:LocationofDongqiaotouinChinaandsatelliteimageSource:InstituteofAppliedEcologyattheChineseAcademyofSciencesThegraphsbelowshowtheincomedistributionamonghouseholdsinthevillage.Formorethan90%ofhouse-holds,themainincomesourceisagriculture,onlyasmallpartofincomecomesfromworkingoutsidethevillage(7%),theserviceindustry(2%),andaquaculture(1%).Figure:HouseholdincomecompositionandsourcesinDongqiaotouSource:InstituteofAppliedEcologyattheChineseAcademyofSciences90%7%2%1%AgricultureOtheremploymentServices10%50%25%15%<RMB30,000RMB30,000-50,000RMB50,000-100,000>RMB100,00010ComparisonofSchwaigandDongqiaotouFigure:Monthlyaveragesolarinsolation(left)andtemperature(right)Source:NRELPVWatts,GIZ,2022Figure:Estimatedpercapitaenergyconsumption(left)andincome(right)inSchwaigandDongqiaotouSource:GIZ,2022-5.00.05.010.015.020.025.030.0JanFebMarAprMayJunJulAguSepOctNovDecSchwaigDQT℃01234567JanFebMarAprMayJunJulAugSepOctNovDecSchwaigDQTkWh/m2/day05,00010,00015,00020,00025,00030,000SchwaigDQTEUR02,0004,0006,0008,00010,00012,00014,00016,00018,000SchwaigDQTMJ11Figure:EstimatedfuelmixofSchwaigandDongqiaotouin2022(left)and2030(right)Note:Note:gridelectricityandliquidfuelsexcludedforSchwaigcase.Source:GIZ,2022Table:ComparisonofsocioeconomicandenergydataonSchwaigandDongqiaotouGermanyChinaNameofvillage/townSchwaig,OberdingDongqiaotouProvince/stateBavariaShandongPopulation1,1401,832Households388446ApproximatepercapitaincomeEuro25,000RMB22,500Annualpercapitaenergyconsumption4,529kWh2,377kWhAnnualpercapitaelectricityconsumption1,082kWh1,257kWhShareofelectricityinenergyconsumption23.89%52.88%Coalconsumption/sharenone41.54%Oilconsumption/share1,769MWh6.49%Gasconsumption/share590MWh12.67%Bioenergyconsumption/share751MWh10.50%Solarpowerconsumption/share1,209MWhWindpowerconsumption/share0MWhHydropowerconsumption/share22,240MWhEnergyusecooling/heating(%)10%33.10%05,00010,00015,00020,00025,00030,00035,00040,000SchwaigDQTPVGasBiomassOilGridLPGCoalOthersGJ05,00010,00015,00020,00025,00030,00035,00040,000SchwaigDQTPVGasBiomassOilGridLPGCoalOthersGJ12GermanyChinaEnergyusetransport(%)78.22%10.81%Energyuseother(%)11.78%56.09%Carbonemissionspercapita5,500kg(StateofBa-varia)115,005kgCarownershiprate(%ofhouseholds,excluding2-or3-wheelers)99%49.33%Solarinsolation(annual,kWh/m2/day)3.423.85Solarinsolation(summer)5.35W/m24.47W/m2Solarinsolation(winter)1.42W/m22.89W/m2Averagetemperature(annual)813Averagetemperature(summer)16.524.5Averagetemperature(winter)-10.3MainoccupationsAgriculture(90%)MainlocalindustriesAgriculture,industry,services,logistics(air-port)Agriculture13CurrentsituationandpolicyframeworkinChinaandGermanyPoliciesinGermanyToachieveGermany’sclimatetargets,thecountryhassteadilybuiltupaframeworkoflawsandvariousfunding,startingwiththeRenewableEnergySourcesAct(EEG),whichcameintoforcein2000andrecentlyunderwentsig-nificantupdates.ThelawprovidesincentivestopromotetheexpansionofDERsforelectricitygeneration.PVsys-temsreceivedafeed-intariffofatleast€0.506/kWhiftheywereinstalledbefore2001.12Thesefeed-intariffshavebeenreducedeveryyearasthecostofpurchasingthesys-temshasalsodecreased.Asof2022,PVsystemsreceiveafeed-intariffofatleast€0.0475/kWh.13Thefixedfeed-intariffexpiresafter20years.Inadditiontothefixedfeed-intariffs,DERsalsohavefeed-inpriority,whichmeansthatthesystemsaregenerallynotsubjecttocurtailment.Duetothedecreaseoftheregulatedfeed-intariffofDERs,todaymostoftheownersofPVsystemsinvestinstoragesystemstomaximisetheirself-consumption,becauseinmostcasesthefeed-in-onlyoptionisnolongerprofitable.Therefore,thereisstillaneedforactionbythepolicytoencouragehouseholdstoinvestinthosesystems.TheCombinedHeatandPowerAct(KWKG)alsocreatedabasisforsupportingrenewableenergiesacrosssectors.14Theenergytransitionisalsopromotedbyactsinthemo-bilityandheatingsectors.Inthepast,theRenewableEn-ergiesHeatAct(EEWärmeG)andtheEnergySavingOrdi-nance(EnEV)helpedpromoterenewableheatingandheatingefficiencyupgrades.The2020BuildingEnergyAct(GEG)supplantedthesetwomeasures.Fornewbuildingsaswellasrenovationsofexistingbuildings,theseregula-tionsfocusonenergyefficiency,whilealsosettingbindingtargetsfortheshareofrenewableenergiesforheatingandcooling.TheGEGbansoilheatinginnewheatingsystemsinnewbuildingsorrenovationsafter2026.15In2021,theBuildingElectricMobilityInfrastructureAct(GEIG)cameintoforce,whichsupportstheexpansionofthecharginginfrastructureforelectricmobility.Allthesepolicyinstru-mentspromotetheenergytransitioninGermany.16Germanyalsoincentivisestheenergytransitionvianu-merousfundingopportunitiesthatsupportthedevelop-mentandexpansionofrenewableenergy.TheinstallationorupgradingofheatingsystemsthatarefullyorpartiallypoweredbyrenewableenergiesissubsidisedbytheFederalOfficeofEconomicsandExportControl(BAFA)withupto€60,000.Oilheatingsystemsareexcludedfromthisfund-ing.AnotherBAFAfundingprogramsupportselectricmo-bility.Forthepurchaseorleaseofanelectriccar,thecus-tomerreceivesanenvironmentalbonusofamaximumof€6,000.TheReconstructionLoanCorporation(KfW)pro-videsfurthersubsidies,withfinancialsupportofupto€75,000fortherenovationornewconstructionofenergyefficienthouses.Whenitcomestoexpandingrenewableenergy,winden-ergyalsoplaysanimportantrole,eventhoughthisstudydoesnotconsideritforthecaseofSchwaig,whichislo-catedimmediatelyadjacenttotherunwaysofoneofEu-rope’sbusiestairports.Germanyhasinrecentyearsfacedchallengesinexpandingwindenergy.Themainreasonsarelengthyandcomplexpermittingproceduresthatcantakemanyyearstofinish,lackofspaceforbuildingpro-jects,andlackofacceptancefromthelocalresidents,whichoftenconcernsthenoiseorappearanceofwindtur-bines.Thesechallengeshaveseverelyhamperedtheex-pansionofwindenergyinGermany,uptothepointofthreatingtheexistenceoftheindustryinGermany.An-otherconsiderablechallengeistheavailabilityofareasfortheconstructionwindenergyturbines.Often,statesinGermanyhaveinstatedregulationsforminimumdis-tancesbetweenwindturbinesandresidentialbuildings.Forexample,inBavaria,thedistancebetweenawindtur-bineandaresidentialbuildingmustbetentimesitsheight(2kmfora200mhighturbine).DuetothehighpopulationdensityofGermany,thisdrasticallyreducesspacefornewwindturbinesandimperilsrepoweringofmanyoldtur-bines.17PoliciesinChinaChina’s13thFive-YearPlanforEnergyDevelopment,pub-lishedinDecember2016,emphasisedelectrificationofbothhouseholdandindustrialenergy,particularlyinpol-lutedregionsintheBeijing,Tianjin,Hebeiandsurround-ingareas.Theplanmentionedsubstitutingelectricheatingforcoal,promotingtime-of-useelectricitypricing,andrenovationofruralpowerdistributiongrids.Theplanin-cludedmeasuresforpromotingrenewableenergyinruralareas,mentioningsolar,wind,smallhydro,agricultural14waste-to-energy,andgeothermalenergy.Theplanalsoemphasisedruralpowersystemreliability,targetingtoachieve99.8%reliablepowersuppliesinruralareasby2020,withaveragehouseholddistributionlinecapacityofatleast2kVA.18The14thFive-YearPlanforaModernEnergySystem,is-suedinearly2022,alsoprominentlymentionsruralen-ergydevelopment.Theplantargetsasecondphaseofpowergridconstructionandupgradingtoimproveelec-tricityreliabilityandsecurityinruralarea.Thisincludespromotingruralmicrogridpilotsaswellassupplyofre-newableelectricitytoruralareas.UndertheThousandsofVillageHouseholdsPVandWindPowerActionPlan,ChinapromotesdistributedPVandsmall-scalewindpower.TheplanalsolistsagriculturalPV,biomassenergy,andgeo-thermalaspriorities.Theplanincludesmeasurestoin-creasegassupplyinruralareas,reduceuseofloosecoalforheating,increaseadoptionofenergy-efficientagriculturaltechnologies,andcreatezero-carbonvillagepilots.19TheChinesegovernmenthasrepeatedlyemphasisedstrengtheningruralpublicinfrastructure,especiallyintheenergysector.InthetraditionalannualDocument#1onruralpolicyin2021,policymakerstargetedruralcleanen-ergyprojects,enhancementofruralpowergrids,andim-provedruralelectricityreliability.Thedocumentalsopro-motesruralgasdistributioninfrastructureandgasstor-age,aswellasruralbiomassenergyandcleaneruseofcoal.20Inthe2022editionofDocument#1,thecentralgov-ernmentagainemphasisesupgradingruralpowergridsandpromotingcleanenergysuchasPVandbiomassinru-ralareas.21The2021OpinionsonPromotingGreenDevelopmentofUrbanandRuralConstruction,issuedbyChina’sStateCouncil,listedvariousprioritiesforhelpingcreateagreen,ecological,andbeautifulcountryside,whileimprovingru-rallivelihoods.Theseincludedimprovingwater,electricity,gas,andsewagefacilities;strengtheningtheenergyeffi-ciencyoffarmbuildings;improvingthetownandvillagefacilities;andpromotingruralgarbage,sewage,andma-nuretreatment.22ShandongprovincialpoliciesShandongProvinceispromotingagreen,ecological,andbeautifulShandong,andthisincludesthedevelopmentofruralgreenenergyonagoodfoundation.Overall,thelevelofruralelectrificationhassignificantlyimproved:Theaveragehouseholddistributioncapacityinruralareashasreached2.71kVA,andtheannualpercapitaelectricityconsumptionis427kWh,reachingmorethan80%oftheaveragelevelincitiesandtowns.Theowner-shipofrefrigerators,washingmachines,andaircondi-tionershasincreasedsignificantly,whileinductioncook-ersandelectricricecookershavebecomecommoncookingtools.Motorcyclesandagriculturalvehiclesarebeinggraduallyreplacedwithelectricvehicles.Thecleanlinessofenergyusehasimproved.Forcookingenergy,methanegas,liquefiedpetroleumgas,andbiogasaccountedforacombined48.2%,electricityaccountedfor29.1%,coalaccountedfor8.2%,woodandother14.5%.Forheating,Shandonghad5.1millionruralcleanheatinghouseholds,accountingfor40%ofthetotalnumberofhouseholds.Ofthese,2.65millionhouseholdsareheatedbymethanegas;1.55millionhouseholdsareheatedbyelectricity;whilebiomass,solarenergyandotherheatingaccountfor900,000households.RuralcleanenergyuseinShandonghasalsoexperiencedrapidgrowthinrecentyears.Theprovincehas585,000householdswithdistributedPV,withaninstalledcapacityof10.41GW,morePVcapacitythanmostnations.Agricul-turalandforestrybiomasshaveinstalledelectricgenera-tioncapacityof1.83GW;theannualuseofcropstrawandforestryresiduesismorethan18milliontons.Shandonghas95MWofbiogaspowergeneration,ofwhichlivestockandpoultrymanuresystembiogaspowergenerationhasinstalledcapacityof25MW.Theseconsume5.57milliontonsannuallyinlivestockandpoultrymanure.2315MethodsandanalysisTheGermanenergytransitionhasalreadyhadasignifi-cantimpactonruralregions,giventhewidespreadadop-tionofwindandsolarinmanyofGermany’sruralareas.24InourapproachtotheenergytransitioninSchwaig,wesoughttoexamineboth(1)howfartheruralenergytran-sitionhasproceededtodate,and(2)whatmedium-termruralenergytransitiondevelopmentsarelikely,withaparticularemphasisonelectrificationofkeysectorsforruralhouseholds,suchasheatingandpersonaltransport.Toanswerthesequestions,thestudyemployedpubliclyavailabledataaswellasavillage-levelsurveyincoopera-tionwithWuppertalInstitutetocalculatethecurrentsta-tusofruraldevelopmentanddevelopscenariosforthefu-tureruralenergytransition.Thestudydeployedathree-stepprocess,firstbydefiningascenarioframework,thenapplyingthescenariodatatovillagelevel,andfinallypro-cessingtheresultingenergydatatogetherwiththeresultsofthesurveytogenerateenergyflowdiagramsandfutureenergyscenariooutputs.ScenarioFrameworkforGermanyTodeterminefutureruralenergyconsumptionandgener-ation,wefirstidentifiedvariousscenariosforkeytechnol-ogies.Thisstudyparticularlyfocusesonthefuturepene-trationofEVs,heatpumps,andPV.Forthedevelopmentofthescenarios,weevaluatedvariousexistingstudiesonthetrendsineachoftheseindividualcategories.Asanexam-ple,weshowourprocessofscenariodevelopmentforEVsasfollows.Figure:EVscenariodevelopmentprocessforGermanySource:WuppertalUniversityWeperformedameta-analysisofavailablestudiesinGer-manytoelaboratepessimistic,moderate,andoptimisticEVadoptionscenarios.Tomakethestudiesmorecomparable,weusedinterpolationmethodstoachieveafive-yearres-olution.ThestudyappliedasimilarapproachforbothEVandheatpumpdevelopment.GiventhealreadywidespreadadoptionofPV,wedevelopedPVscenariosbasedonthealreadywell-establishedsce-nariosofthegriddevelopmentplan(GDP)publishedbythefourtransmissionsystemoperatorsatregularintervalsandreviewedbytheFederalGridAgency.25Thegriddevel-opmentplanidentifiesthreedevelopmentpathsforPVinGermany,whichdifferonlyminimally:From2019on-wards,annualPVinstallationsshouldrangebetween3.8GWand4.4GWacrossthescenarios.GiventhenewfederalgovernmentthattookofficeinGermanyafterthe2021GDPreport’spublication,higherannualinstallationsappearlikely.Accordingtothecurrentcoalitionagreement,Ger-manyshouldreachaninstalledPVcapacityofover200GWby2030.2616ThefirststepbeginswiththedevelopmentdataforthewholeofGermany,asshowninthetablebelow,andthenbreakingthesenationaldatadowntotheindividualfederalstates,andthentocommunitylevelbasedonpopulationdensityandbuildingstock.Table:OverviewofunderlyingEV,heatpumpandPVscenariodataforSchwaigscenariosSource:WuppertalUniversity,2022;dena27,Bundesnetzagentur28RegionalisationMethodologyBasedonthescenarioframeworkandtheoverallnationalprojectionsforeachscenario,weextrapolatefiguresdowntotheselectedvillage.Asanexample,wedisplaythemethodforEVs.ThemethodologyforheatpumpsandPVdiffersonlybasedontheinputdata.Thefigurebelowshowsthegeneralprocessofregionalisationmethodology.Figure:PrincipleoftheregionalisationmethodologywiththeexampleofEVsSource:WuppertalUniversityTechnologyScenarioYear20302035ElectricVehiclesPessimistic3.53Mio7.35MioTrend4.16Mio8.65MioOptimistic5.4Mio11.25MioHeatPumpsDenaTM-953.9Mio4.775MioDenaEL-957.9Mio10.1MioPVGDPScenarioA90.8GW110.1GWGDPScenarioB96.3GW117.8GWGDPScenarioC97.4GW120.1GW17Whenitcomestoheatpumps,theregionalisationproce-dureconsideredthebuildingstructureofafederalstateoracommunitytoestimatethediffusionofheatpumps,withdetachedandsemi-detachedhousesasmostsuitablebuildingtypes.Giventheabsenceofdetaileddatainclud-ingparameterssuchastheactualbuildingageorthede-greeofinsulation,theanalysisassumesauniformdegreeofbuildingefficiency,sopossiblyvariationsinbuildingcharacteristicshavenoeffectonourestimateofthedistri-butionofheatpumps.Forthestudy,weweightedthenumbersofEVsandheatpumpsfromthecommunityofOberdingamongthediffer-entvillagesbasedonpopulationandhouseholdsize.Oberdingpublishesitspopulationdistributiononitspublicwebsite.29WeassumedthedistributionoffuturePVinstal-lationsbasedonthecurrentlyinstalledcapacityinthevil-lages,providedbythegridoperatorE-WerkSchweigeroHG.SimulationAssumptionsforGermanyTotranslatethescenariodataforOberdingintoenergyandpowervaluesforEVcharginginfrastructureandheatpumps,theenergyflowmodelsmustaccountforthestrongseasonalfluctuationsinPVsystemoutputandheatpumpenergyconsumption.ForEVchargingloads,weonlyconsiderprivatecharginginfrastructure,andthusonlyfo-cusonACchargingtechnology.WeassumemostEVcharg-ingtakesplaceatpowerlevelsofeither11kWor22kW.GiventheimportanceofestimatingchargingbehaviourincalculatingtheenergydemandforEVs,weemployedsto-chasticdataonuserbehaviourfromtheMobilityinGer-manyStudy2017actasinputparameterstocreatecharg-ingprofilesviastudy’sparkingprofiles.30Thisenablesde-velopmentofindividualchargingprofilesforeachEVinthecommunityforanentireyear,sowecanestimatetheenergydemandforanEVdowntotheminute.IncontrasttoEVs,whichhaveunpredictableloadpatterns,heatpumpsgenerallyshowverysimilarconsumptionbe-haviourandarestronglyaffectedbyseasonalinfluences.Theenergyconsumptionbehaviourisstronglydependentontherespectiveoutsidetemperature,whichdoesnotdif-fersignificantlywithinacommunity.Thesimulationas-sumesthreepowerclassesforheatpumpsbasedonWintzeketal.,31consideringbuildingheatdemandandhotwaterdemand:3KW,6.5kW,and9kW.Tomapseasonalinfluences,thesimulationusesdifferentnormalisedheatpumptimeserieswitharesolutionofoneminute.Thetimeseriesreflecttheloadprofileofaheatpumpforanolderhouseandamodernisedhouse,aswellasthebehaviourwithandwithoutblockingperiodsinwhichgridoperatorsswitchofftheheatpumpstoreducesystemload.Theanalysisemploystimeseriesdatatodeterminetheen-ergyfedintothegridbythePVsystems.Arepresentativetimeseriesissufficient,sincetheweatherconditionswithinthecommunityorinthevillagesunderconsidera-tiondonotshowanysignificantdifferences.E-WerkSchweigeroHGprovidedameasuredtimeseriesfromtheyear2020witha15-minuteresolution,whichwenormal-isedandusedasabasisforfurtherconsiderationinthedistributionofPVpower.Inaddition,wecomparedandvalidatedthegeneratedscenariodataagainstinformationfromtheEnergyAtlasofBavaria.32InadditiontothenewloadsofEVsandheatpumps,typicalhouseholdandcommercialloadsneedtobemodelledforaholisticviewoftheenergyflows.Therearenodataavaila-bleonthespecificconsumptionofhouseholds,sothemodellingreliedonthepublishedaverageconsumptionofdifferenthouseholdsizesandderivedpowerconsumptionperhouseholdfromthepublishedhouseholdsizesofOberdingcensusdata.33Theaverageelectricityconsump-tioncanbedividedintolow,medium,andhigh.Thecon-sumptionoftypicalhouseholdsisalsoinfluencedbysea-sonalfactors.Inordertotaketheseintoaccount,thesim-ulationusedrandomlyassignedhouseholdprofilesbasedontimeseriesfromTjadenetal.34Giventhelimitedinformationavailable,thisstudydoesnotgointothesamelevelofdetailonindustrialconsump-tionorloadprofiles.Generally,priorstudieshaveshownthatGermany’sindustrialandcommercialloadsapproxi-matelyresemblehouseholdelectricityconsumption.35Sincetherearenolargeindustrialoperationsintheregion,weincorporatedtheoverallestimateoflocalindustrialloadsintothesimulationoftheannualhouseholdenergyconsumption.36Thetotalenergyrequiredbytheindustrialandcommercialsectorsisdividedintoindustryandagri-culture.Agricultureinparticularformsalargepartoftheindustrialloadinruralregionscomparedtourbanareas.Forthemodellingoftheenergyflows,weusedsyntheticelectricityloadprofilesforagricultureandindustryadaptedfromAPCSPowerClearingandSettlementdata.37Withthisapproach,wecreatedvarioustimeserieswithenergyflowsmodelledin15-minuteintervals.Wealsoin-corporatedtheheatingsectorbymeansofanannualanal-ysis.Averageheatdemandsforbuildingtypesfromdiffer-entyearsofconstructionorrenovationcanreflectthehouseholdconsumptionforthehouseholdsinthesimula-tion.38Wedevelopedsimulationsforlow,medium,andhighheatingdemand,andmatchedtheseagainsttypicalapart-18mentorhousesizesforthecorrespondingbuildingstruc-ture.Asbefore,weusedacomparisonfactortoincorporatethelocalindustrialheatingdemand;thisfactorrepresentstheratiooftheindustrialheatdemandtohouseholdheatdemand.Theindustrialdemandishigherthanthehouse-holdheatdemandbyafactorof0.38.39SurveyDesignforSchwaigThefinalstepinmodellingtheenergyflowsisasurveyofthepopulation.Afterobtainingtheformalapprovalofthelocalcommunity,weadministeredthesurveyinthevillageofSchwaiginthecommunityofOberding.Wedesignedthreedifferentsurveyformstocollectdatafromhouse-holds,localbusinesses,andthelocaladministration.Thesurveydesignsweretailoredtohelptoevaluatetheprevi-ousandfuturedevelopmentofsectorcouplingandtheen-ergytransitioninSchwaigandtocompareandpotentiallyadjustscenarioassumptions.Thesurveysrequesteddataandattitudesonthreekeysub-areas:mobility,heating,andelectricityuse.Forfurtherclassificationandvalidation,additionalsocio-demographiccharacteristicswerealsocollected.Thehouseholdsurveydiffersfromthebusinessandadministrationsurveyinthatitincludesmoreques-tionsrelatedtothesubjectiveopinionsoftheparticipants.Thebusinessandadministrationsurveysonlyrequestconcretedata,withtheprovisothatrespondentsshouldnotgotospecialeffortstoretrievesuchdata.Thehouse-holdsurveydoesnotrequestconcreteenergyconsumptiondataduetoconcernsthatthiswouldrequireasignificanttimeburdenandlikelyreducethewillingnesstopartici-pate.Part1ofthequestionnairelooksatthemobilitysector,re-questinginformationaboutexistingvehicles,fuel,andan-nualmileage.Usingtheresultsofthesequestions,wede-velopedanestimateofthecurrentnumberofEVsinthevehiclestock.ThesurveyalsoaskedparticipantswhethertheycouldimaginebuyinganEVinthefutureandwheretheywouldchargeit.Part2ofthesurveydealswithheatingandpower.Toap-proachthisissuewithoutrequestingprivatedata,thesur-veyrequestedparticipantsevaluatetheirhouseholdde-mandforheatingandpowerusingthecategorieslow,nor-mal,andhighforeach.Thesurveyaskedrespondentsabouttheircurrentheatingfuelsandtechnologies,andwhethertheycouldimagineconvertingtheirheatingandcoolingsystemintoanelectricsystemlikeaheatpump.WeusedthesequestionstodevelopbothenergyflowdiagramsforcurrenthouseholdconsumptionaswellastorefinetheheatingandcoolingscenariosforSchwaig.Thesurveyalsoaskedwhetherrespondentsowntheirhomeorarerenters,andrequestedthatownersevaluatewhethertheycanim-agineheatingwithrenewableenergyinthefuture.Lastly,thesurveyrequestedsomesocio-demographicdataonhouseholdsize,numberofemployedpersons,agestructure,andhousetype.Thisallowedustoestimatewhatpercentageofthepopulationthesurveyrepresentedandtheemploymentanddemographicstructureofthepartic-ipants.SurveyresultsinSchwaigThesurveyinSchwaigtookplaceoveraperiodofthreeweeksinJune2021andwasconductedbyWuppertalInsti-tute.Atotalof18companieswithnoconnectiontoMunichAirportwerecontactedbuttheirresponseratewastoolow;therefore,thispartofthesurveyisnotconsideredfurther.Theresponseforthehouseholdsurveyreachedthetargetofabout20%,whichprovidesagoodfoundationforfur-therevaluation.WhenscaledupandappliedtotheentirevillageofSchwaig,thesurveyresultsenablegeneralisa-tionsaboutthecurrentandfutureenergytransition:19Table:SummaryofSchwaigsurveyresultsCategoryResultMobilityCarownership98.9%ofrespondentsownatleast1car,73.3%ownatleast2carsand11.5%own3carsAveragedistancedrivenperyearpervehicle13,000kmEVownership5%,mostlychargingathome35%canimaginepurchasinganEVinthefuture,87%ofwhichwouldchargeathome28%areundecided,40%ofwhichwouldchargeathomeiftheyhadanEVEnergysupplyandcon-sumptionPowerconsumptionself-assessmentLow:10%,Normal:62%,High:28%Heatconsumptionself-assessmentLow:13%,Normal:69%,High:18%HeatingtechnologiesandfuelsOil47%,Gas15%,Heatpump14%,Biomass5%,Other19%,Nightstorage1%Attitudestowardsre-newableenergySolarthermal:Alreadyowning27%,Considering27%,Notconsidering30%,Undecided15%SolarPV:Alreadyowning23%,Considering33%,Notconsidering26%,Undecided18%Heatpump:Alreadyowning13%,Considering30%,Notconsidering44%,Undecided14%CHP:Alreadyowning0%,Considering25%,Notconsidering52%,Undecided23%PopulationandbuildingpropertiesHouseholdsize1person13%2persons39%3persons27%4persons18%5persons1%6persons2%EmploymentAtleastoneperson:74%ofhouseholdsTwopersons:62%ofhouseholdsAgeHouseholdswithoutchildren(personsagedunder18):74%Source:WuppertalUniversity,2022Thefirstpartofthesurveycoveredmobility.InSchwaig,almostallthesurveyedhouseholdshaveatleastonecar.Intotal,98.9%ofrespondentsownatleastonecar,73.3%ownatleasttwo,and11.5%ownthreecars.Eachvehicledrivesbetween12,000-14,000kmperyearonaverage.Asof2021,about5%ofSchwaigvehicleownershaveanEV.ThemajorityofEVownerscanchargeathome,onlyonerespondentchargesexclusivelyatpublicchargingpointsoratwork.35%ofrespondentscanimaginebuyinganEVinthefuture,whileanother28%arestillundecided.OfthosewhowouldbuyanEV,87%indicatetheywould20chargeathome,whereas40%oftheundecidedstatethattheywouldchargeathome.Thesecondpartofthesurveycoveredthetopicofenergyproductionandenergyconsumption,includingboththeelectricityandheatsectors.Forreasonsofprivacy,andtoencourageresponses,thesurveydidnotattempttogatherinformationonpreciseconsumptionfigures;instead,thesurveyaskedrespondentstoevaluatetheirownconsump-tionofelectricityandheatashigh,normal,orlow.Whilethesecategoriesmayseemimprecise,andexcessivelydif-ficultforrespondentstoobjectivelyevaluate,webelieveaskingforprecisedatawouldresultinmostrecipientsde-cliningtofillinorreturnthesurvey.21Figure:SubjectiveassessmentofpowerandheatconsumptionPowerConsumptionHeatConsumptionSource:WuppertalUniversity，2021Forbothpowerandheatconsumption,perhapsnotsur-prisingly,mostparticipantsevaluatetheirconsumptionasnormal.Respondentsshowedagreaterpropensitytoeval-uatetheirhouseholdashavinghighelectricityconsump-tionratherthanhighheatconsumption.Only10%to13%ofrespondentsratetheirconsumptionaslow.Thisdistri-butionisusedinthefurtheranalysisforthedeterminationofthehouseholdpowerconsumption.Figure:CurrentheatingtechnologiesinSchwaigSource:WuppertalUniversity,2021Thesurveyalsorequestedinformationonhouseholdheat-ingsources.HeatinginSchwaigreliesonadiverserangeoffuels,withoilheatingpresentlythemostcommonwithashareof43%.Electricheatpumps,naturalgasheating,andothertypesofheatingnotexplicitlylistedarefairlyevenlydistributedwithsharesbetween15%and19%.Bio-massandnightstorageheatershavethelowestsharesof5%and1%.76%ofrespondentsowntheirapartmentor28%10%62%highlownormal18%13%69%highlownormal19%15%5%43%1%17%OtherGasBiomassOilNightstorageHeatpump22houseandcouldthereforedecideforthemselvestoadoptheatpumpsand/orrenewableenergy.Figure:PresentdistributionofhousingtypesinSchwaigSource:WuppertalUniversity,2021Figure:AttitudestowardsenergytransitiontechnologiesinSchwaigSource:WuppertalUniversity,2021Almost23%ofrespondentsalreadyownaPVsystem,forexample,andanother33.3%canimaginegeneratingtheirownelectricityinthefuture,whereas26%arestillunde-cidedonthesubject.Intermsofhomeheating,solarther-malalreadyhasahighshareamongownersat27%,an-other27%canimagineachangeinthefuture,and15%arestillundecided.Thecurrentshareofheatpumpsislowerat13%,butanother30%canimagineusingtheminthefu-tureand14%arestillundecided.25%wouldconsideracombinedheatandpowergenerationandfurther23%arestillundecidedonthetopic.Giventhesesurveyresults,weclassifiedrespondentsbygroupandrefinedtheassumptionsofeachscenario,par-ticularlyregardingadoptionofPV,heatpumps,andEVs.In0%10%20%30%40%50%60%70%80%90%100%SolarthermalCHPHeatPumpPhotovoltaicsAlreadyownYesNoUndecided5%49%16%30%OthersSinglefamilyhouseApartmenthouseTwo-familyhouse23thecaseofbothtechnologies,surveyrespondentsex-pressedinterestinbothtechnologies,andapartofthepopulationhasalreadyadoptedheatpumps.RespondentsarealsowillingtoconsidergeneratingelectricitywithPVsystems,andmanyalreadyhavePVsystemsinstalled—indeed,thecommunityofOberdinghasatotalof6,820MW,animpressivelyhighrateforacommunityofthissize.Figure:HouseholdsizeinSchwaigSource:WuppertalUniversity,2021Overall,thesurveyresultsshowthattheresidentsofSchwaighaveahighlevelofopen-mindednesstowardsenergytransitiontechnologies.Thisbecomesparticularlyclearwhenwescaleupthesurveyresultstoestimatetech-nologypenetrationamongallSchwaigresidents.Weesti-matethatSchwaigalreadyhas20EVsand40heatpumps.Toforecastfuturedevelopment,inthissectionwegener-alisethesurveyresultstothetotalpopulationinSchwaig.SincethesurveydidnotfurtherspecifythetimehorizonforquestionsaboutthefuturepurchaseofanEVorheatpump,itisstillassumedthatthepurchasewilloccurby2030.Ayesmeansacquisitionby2030,andthoseunde-cidedareassumedforanoptimisticapproachtoalsode-cidetopurchaseby2030.Basedonthislogic,forthetargetyear2030,weestimate175EVsand135heatpumpsinSchwaigforthetrendscenarioand300EVsand180heatpumpsfortheoptimisticscenario.Itisnoticeablethatthecalculatedramp-updatafortheselectedscenarios(seeAnnex)fortheyear2030aremorepessimisticthanthesurveyresultsforthesameyear.Thisanalysisemployedthefiguresfor2035duetotheirgreaterconsistency.Thematchingscenariostothesurveyevaluationsarecon-trastedinthetablebelow.Table:ScenarioselectionbasedonthesurveyNumberofEVsNumberofheatpumpsScenarioSelectionSurveyMatchingScenarioSurveyMatchingScenarioCurrent2040TrendScenario175157135102Trendscenario2035,dena-TM952035OptimisticScenario300204180216Optimisticscenario2035,dena-EL952035Source:WuppertalUniversity,202113%39%27%18%1%2%1Person2Persons3Persons4Persons5Persons6Persons24Weselectedtwoscenariosforfurtheranalysis.Thefirst,calledtheTrendscenario,incorporatesthetrendscenario2035,thedenaTM-95scenario2035,andtheGDPscenarioA2035.Ingeneral,theTrendscenariorepresentsmoreconservativeassumptionsaboutelectrificationandPVex-pansionandanextrapolationoftrendsaround2020.Thesecond,theOptimisticscenario,consistsoftheoptimisticscenario2035,thedenaEL-95scenario2035andtheGDPscenarioC2035.40Thesetwoscenariosenableestimationofoverallelectricitydemand,giventhattheyincorporateinformationaboutincreasingelectrificationinthemobil-ityandheatingsector,aswellasthefutureelectricitygen-erationprimarilybyPVsystemsandtheassociatedpoten-tialforself-supply.Weassumenochangeinthetotalheatdemand,withonlythesourceoftheheatingdemandchangingovertime.Duetotheincreasingelectrificationintheheatingsectordescribedaboveandtheprogressivesubstitutionofoilheating,whichisalsodescribedinthedenascenarios,thedistributionofheatingdemandin2030willbesignificantlydifferentfromthecurrentsituation.TheresultingdistributionisshownasanexampleforthedenaEL95scenariointhefigurebelow.Figure:HeatingsituationinSchwaigwithdenaEL95Scenario2035Source:WuppertalUniversity，2021Theshareofoilheatingwilldecreasedrasticallyandeven-tuallydisappearcompletely.Biomass,methanegas,andothertechnologieswillalsoaccountforasmallershareofheatgeneration.Accordingtothestudy’sfindings,electricheatpumpsin2030couldmeetmorethan62%ofheatingandcoolingdemand.Basedontheseresults,andincorporatinglow,normal,andhighpowerconsumptionestimates,wecandevelopesti-matesforhouseholdandcommercialelectricityconsump-tionforthewholevillageofSchwaig,excludingEVsandheatpumps,of1,234MWh.Basedontheassumptionsusedforthisstudydiscussedinmoredetailbelow,weassumethesameelectricityconsumptionforthecommercialsec-tor.Analysis–SchwaigOuranalysisemploysacombinationofenergysurveyre-sults,publicdata,utilitydata,andvariousforecastsfortheadoptionofenergytransitiontechnologiessuchasEVs,heatpumps,andPV.Usingthesedataandforecasts,wehavedevelopedaseriesofenergyflowdiagramsforSchwaignowandinthefuture,andsimulatedmonthlyandhourlyenergyproductionandconsumptionatthevillageandhouseholdlevels.Overall,wefindthatSchwaighashighpotentialforenergyself-sufficiency,butwithhighdailyandseasonalvariability,implyingtheneedforthevillagetoremainhighlyconnectedinthemediumtermandthepotentialtoincreasetheadoptionofenergystoragetechnologiesinthelongerterm.10%9%1%18%62%OtherGasBiomassOilHeatpump25TheresultsfortheTrendandOptimisticscenariossuggestthatSchwaig’sannualenergyconsumptionwilldifferminimallybetweenthetwoscenarios.TheOptimisticsce-nariohasahighershareofheatpumpsandEVs,butsincewedonotincludeoilconsumptionintheenergyflowmod-elsforsimplicity,thisimpliesthatEVadoptionincreasesnetconsumption,offsettingtheefficiencygainsfromheatpumpadoptionintheOptimisticscenario.Figure:AnnualenergyflowsinSchwaigfortheTrendscenarioSource:WuppertalUniversityAsimplifiedSankeydiagramdisplaystheresultsfortheTrendscenario,measuredinMWh.Theinputsideshowshowenergyproductionmainlytakestheformofelectric-ity—fromthegridandfromPVinstalledlocally.Overall,electricalenergyaccountsforaround63%oftotalenergyrequiredinthisscenario.WeassumeenergyprovidedbysolartakestheformofelectricityfromPV;wegroupanysolarthermalintothecategoryother.IntheTrendscenario,fossilfuelsmaintainarelativelyhigh25%shareofenergysupply.Notethatthefossilfuelsincludedinthismodelonlyrepresentthoseusedinheatsector,nottheoilusedfortransport.The25%figurealsoexcludesanyfossilfuelsusedforgridelectricity.Heatdemandrepresentsthelargestshareofenergycon-sumption,accountingfor56%ofthetotaldemand.Heatpumpsprovideonlypartoftheheatdemand.Electricitydemandforindustryandhouseholdsisidentical,asal-readydescribedintheassumptions.Intheenergyflowdi-agrams,thehouseholdcategoryexcludesanyheatpumpormobilityenergyconsumption.Overall,theindustryandhouseholdcategoriesaccountfor35%oftotalenergyde-mand.Themobilitycategoryexclusivelyreferstoelectric-itydemandforchargingEVs.Overall,EVshaveashareof8%ofthetotalenergydemand.Overtheyear,Schwaigachievesaself-sufficiencyrateof30%intotalenergycon-sumptioninthetrendscenarioonlywhenconsideringPVfeed-in.26Figure:AnnualenergyflowsinSchwaigfortheoptimisticscenarioSource:WuppertalUniversityThenextfigureshowstheenergyflowsfortheOptimisticscenario,whichlookquitesimilarontheoutputsidetotheTrendscenario.Themaindifferenceisintheenergyre-quirementsfortheEVs,whichisduetothesignificantlyhighernumberofEVsintheOptimisticscenario.About11%oftotalenergydemandisusedforchargingEVsinthissce-nario.Ontheinputside,therearegreaterdifferencesver-sustheTrend.TheOptimisticscenariofeaturesasignifi-cantlylowershareoffossilfuelsatonly15%,versus25%fortheTrendscenario.TheshareofPVis32%intheOpti-misticscenario,versus30%intheTrendscenario.Thisrel-ativelysmalldifferenceisduetothesmalldeviationsbe-tweentheGridDevelopmentPlan(GDP)scenarioAandGDPscenarioC.At46%,thesupplyfromthegridcoversthelargestshareofenergydemand.Thisisduetothein-creasingnumberofEVsandtothehighelectrificationoftheheatingsectorinthedenaEL-95scenario.IntheOpti-misticscenario,Schwaigachievesanannualself-suffi-ciencyrateof32%.Figure:AnnualpowerflowforSchwaiginthetrendscenarioSource:WuppertalUniversity27Ifweconsideronlytheelectricalenergyflows,theself-sufficiencypictureisquitedifferent.Sinceheataccountsforover50%ofelectricalenergydemand,anexclusiveconsiderationofelectricityshowsclearlydifferentself-supplyrates.TheabovefigureshowstheelectricalviewforSchwaigofthetrendscenario.TheannualelectricalenergydemandforSchwaigis3,757MWhintheTrendscenario.Thehouseholdandindustrycategorieseachaccountfornearlyone-thirdofdemand.EVcharginghasashareofabout16%andheatpumpsabout19%ofthetotalelectric-itydemand.Ontheinputside,only44%oftheelectricitydemandstillhastobeprovidedbythegrid.PVsystemscanprovide56%oftheelectricityloadoverthecourseoftheyear.ThefigurebelowshowstheelectricalviewforSchwaigoftheOptimisticscenario,whichfeaturesmuchhigherde-mandforelectricity.Overall,demandincreasesbyaround25%,duetohigherelectrificationofheatingandtransportintheOptimisticScenario.Althoughconsumptionbytheindustryandhouseholdcategoriesremainsunchanged,theshareofelectricityprovidedbythegridrisestomeettheaddeddemandfromheatingandEVcharging.PVsystemsprovide49%ofelectricity,andconsequently,thedegreeofself-sufficiencyintheOptimisticscenarioisslightlylowerthanintheTrendscenario.GiventhesignificantlyhigherelectrificationintheOptimisticscenarioandtherelativelysmalldifferencesinPVoutputbetweenthetwoscenarios,thelowerself-sufficiencyrateisunsurprising.Figure:AnnualpowerflowforSchwaigintheoptimisticscenarioSource:WuppertalUniversityHowever,theself-sufficiencyratesforthetrendandopti-misticscenarioscanvarysignificantlywithinayear.Inparticular,thePVoutputandtheelectricitydemandforheatingdisplayanegativecorrelation,withPVoutputgreatestinthesummerandheatingrequiredinthewinter.TheseasonalimbalancebetweenelectricitydemandandPVoutputisgreaterinthecaseofSchwaigthaninthecaseofDongqiaotou,China.28Figure:ComparisonofmonthlyelectricitydemandforSchwaiginthetrendscenarioSource:WuppertalUniversityAsthefigureaboveshows,heatpumpelectricitydemandincreasessignificantlyduringtheheatingseasonbetweenNovemberandMarch.BetweenAprilandSeptember,householdsmainlyuseheatpumpsforwaterheating—weestimatelittlecoolingdemandforthetypicalhouseholdintheregionassummersinGermanyaremostlymild,mak-ingairconditioningunnecessarymostofthetime.TheEVchargingdemanddisplayslittleseasonalvariation.(AswithEVload,industrialdemandexhibitsrelativelylowseasonalvariation.)Overall,duetoheatingloadsaswellasdemandforlighting,householdshavehigherelectricityconsumptionduringthewintermonths.Theseasonalvar-iabilityismostobviousinthecaseofPVfeed-in.Whilethefeed-inbetweenMarchandSeptemberisquitehigh,thefeed-inbetweenOctoberandFebruaryistinyincompari-son.Monthlyelectricityconsumptionvariesbetween230MWhand415MWh.Thisresultsinahighoverallrangeofself-sufficiencyratesfortheindividualmonths.InDe-cember,ahouseholdcanreachself-sufficiencyofonly6%,whileinJulyahouseholdcouldreachself-sufficiencyof130%.-400-300-200-1000100200300400500JanFebMarAprMayJunJulAugSepOctNovDecPhotovoltaicHouseholdIndustryHeatPumpEVs29Figure:ComparisonofmonthlyelectricitydemandforSchwaigintheoptimisticscenarioSource:WuppertalUniversityIntheOptimisticscenario,thePVoutputisquitesimilartotheTrendscenarioacrosstheindividualmonths.Forheatpumps,thedifferencebetweenthesummerandwintermonthsismuchmoresignificantthanintheTrendsce-nario.AsintheTrendscenario,EVchargingvarieslittleduringtheyear.However,EVelectricityconsumptiondif-ferssharplyacrossscenarios,withtheOptimisticscenarioshowingmonthlyEVconsumptionof14MWhhigherver-sustheTrendscenario.Overall,theOptimisticscenariodisplaysmuchgreatersea-sonalvariationinconsumptionthantheTrendscenario,mainlyduetohigheradoptionofheatpumpsandcorre-spondingincreasesinwinterelectricityconsumption.IntheOptimisticscenario,therearedifferencesofupto270MWhbetweendifferentmonths,whichcorrespondstoaboutonefifthoftheannualconsumptionofallhouse-holds.IntheTrendscenario,themaximumdifferencebe-tweensummerandwintermonthsislessthanhalfashigh.Asnoted,PVoutputintheOptimisticscenarioissimilartothatinthetrendscenario,withonlyaslightlyhigherover-allfeed-in.IntheOptimisticscenario,theself-sufficiencyratefortheindividualmonthsalsovariesgreatly,rangingfromaminimumof5%inwintertoamaximumof128%insummer.Hence,theself-sufficiencyrateintheTrendsce-narioisslightlyhigherthanintheOptimisticscenario.Ifwelookfurtherattheself-sufficiencyratesoftheindividualmonthsofthetwoscenarios,inthetrendscenariofivemonthshaveaself-sufficiencyrateofatleast100%.Intheoptimisticscenario,onlythreemonthsachieveself-suffi-ciencygreaterthan100%.Lowerself-sufficiencyrelatesmainlytogreaterheatpumpadoptionand,consequently,greatermismatchbetweenseasonalPVproductionandheatpumpconsumption.NotonlydoesSchwaigfeaturestrongseasonalvariationinPVoutputandhouseholdheatingloads,butintradaycon-sumptionalsoshowshighvolatility.Thefollowingchartsdisplaysimulationresultsforthetwoscenariosduringanillustrativewinterweek.-400-300-200-1000100200300400500600JanFebMarAprMayJunJulAugSepOctNovDecPhotovoltaicHouseholdIndustryHeatPumpEVsMWh30Figure:LoadcurveforanexemplarywinterweekinbothscenariosTrendScenarioWinterOptimisticScenarioWinterSource:WuppertalUniversityInatypicalGermanwinterweek,PVsystemsgeneratelit-tleoutputrelativetootherseasons.Indeed,thoughSchwaiginGermanyandDongiaotouinChinahavesimilarsolarinsolationinthesummermonths(JunethroughAu-gust),insolationinSchwaigisjust40%thatofDongqiao-touduringthemonthsofDecemberthroughFebruary.InSchwaig,PVpanelsonlyproducepowerbetween9amand4pminthebestcase,andwinterenergyproductionexhib-itshighvolatilityduetovariablecloudcoverandweatherconditions.Maximumoutputpeaksdifferbyuptoafactorofthree.PVoutputrarelyexceedsminimalvillageload.Intheoptimisticscenario,PVloadissignificantlyhigherthaninthetrendscenario,andthisappliesbothintheloadpeaks,whichareupto70kWhhigherintheoptimisticsce-nario,andintheminimumload,whichdiffersbyupto40kWh.Furthermore,loadpeakstypicallyprecedeorfollowpeakPVoutput.Thispatterncanleadtoquitehighself-sufficiencyrateseveninwinter,butonlyinafewtimepe-riods.TheOptimisticscenarioachieves91%self-suffi-ciencyratio,whiletheTrendscenario(withlowerloadforheatpumpsandEVs)achieves115%self-sufficiencyintimeperiodswithpeaksolaroutput.Overtheentiresampleweek,however,theenergyloadsignificantlyexceedstheenergyfedintothegrid,sothattheself-sufficiencyratesfortheoptimisticscenarioare9%andforthetrendsce-nario11%.0.40.410.420.430.440.450.460.470.480.490.5-200-1000100200300400shaderPhotovoltaicHeatPumpEVHouseholdIndustryTotalLoadkWhWedThuFriSatSunMonTue00.10.20.30.40.50.60.70.80.91-200-1000100200300400shaderPhotovoltaicHeatPumpEVHouseholdIndustryWedThuFriSatSunMonTuekWh31Figure:LoadcurveforanexemplarysummerweekinbothscenariosTrendScenarioSummerOptimisticScenarioSummerSource:WuppertalUniversityAsimilarsituationholdsforsummermonths,whichfea-turelongerandmoreconsistentsunlighthours.Theex-amplewinterweekhassevenhoursofsunlight,thesum-merweekhasalmosttwiceasmanywith13hoursofsun-light.Thedailyfeed-inpeaksdifferonlyminimallycom-paredtothewinterweekandaresometimesmorethanthreetimeshigherthaninwinter.Whileinthewinterex-amplethesummedloadcurvesshowsignificantdiffer-encesbetweenthetwoscenarios,theminimumandmax-imumloadsinthesummerweekarealmostidenticalinbothscenarios.Thisismainlyduetothefactthatinsum-merheatpumpsareusuallyusedonlyforhotwater,andcoolingloadsinBavariaremainlow.Theaveragesummer(July)temperatureinSchwaigis16.5°C,withtheaveragehighat23°Candtheaveragelowat12°C.Thehighernum-berofEVsintheoptimisticscenarioalsodoesnotneces-sarilyleadtolargerloadpeaks,sinceEVsdonotneedtochargesimultaneouslywiththeloadpeaks.Winterheatpumploadsaccountforalargepartofdailypeakloadsandthereforecoincidewithpeakloadnearly100%ofthetime,producingamuchgreaterloadpeakintheOptimisticscenarioduringwinter.Thesignificantlylowerloadandhigherandlongerfeed-inisclearlynotice-ableintheself-sufficiencyrates.Forbothscenarios,intheweekshown,theself-sufficiencyrateisgreaterthanorequalto100%formostofthetimethatPVelectricityisproduced.Insomecases,theenergyfedintothegridex-ceedstherequiredenergybyafactorof6to7.Fortheweek,thetwoscenariosyieldfairlysimilarself-sufficiencyratesinthetrendscenarioat138%andintheoptimisticscenarioat137%.Overall,thecomparisonsinaboveFigureshowtheneedforstorageofPVoutput.Especiallyinsummer,theelectricitygeneratedbyPVsignificantlyexceedsbothtotalelectricityconsumptionanddaytimepeakelectricitydemand,sothatstoragecouldkeepthesurpluspoweravailableduringthenightandotherperiodswithlackingPVoutput.Eveninsometimeperiodsininwinter,householdswouldneedenergystoragetomakethebestuseoftheenergygener-ated.InadditiontothestudiesfortheentirevillageinSchwaig,individualhouseholdscanalsobeanalysedfortheirdegreeofself-sufficiency.Bymodellingtheenergyflowswiththetimeseries-basedsimulations,wecanexamineahouse-holdin2030withregardtoelectricitydemand.Hereweconsideranillustrativefour-personhouseholdwithoneEV,aheatpump,andaPVsystem.Thehouseholdenergydemandissetatanormalconsumptionforfourpersons.Thisresultsinaconsumptionof3,800kWh.Thehouse-holdoperatestheirEVforabout13,000kmperyear,thehousehold’sheatpumphasaninstalledpowerof3kW,anditsPVsystemhasaninstalledcapacityof12kW.ThePV00.10.20.30.40.50.60.70.80.91-500-400-300-200-1000100200ShaderPhotovoltaicHeatPumpEVHouseholdIndustryTotalLoadWedThuFriSatSunMonTuekWh0%10%20%30%40%50%60%70%80%90%100%-500-400-300-200-1000100200Shader2PhotovoltaicHeatPumpWedThuFriSatSunMonTuekWh32systemisdesignedtotheoreticallycovertheentireelec-tricitydemandofayearforthehousehold,intermsofkWhconsumed.Acomparisonofmonthlyelectricitydemandandgenera-tionisshownbelow.Strongseasonaldifferencesinde-mandandgenerationarealsoevidentforindividualhouseholds.Theheatpumpisthemaindriverofhouseholdelectricityconsumption.Especiallyinthewintermonths,theheatpumpaccountsforthemajorityoftheelectricitydemand.Ontheotherhand,thenormalhouseholdcon-sumptionandtheenergyrequiredtochargetheEVisquiteconstantthroughouttheyear.However,thisisfartoosmalltocompensateforthestrongfeed-ininsummer.Thisleadstothefactthatinthesummermonthsupto4timesmoreenergyisproducedthanisconsumed.Inwinter,ontheotherhand,thefeedisnotsufficienttocoverthede-mand.Intheshownexample,thiscircumstanceresultsinaminimumself-sufficiencyrateof9%.Overtheentireyear,thehouseholdcouldbecompletelyself-sufficientonanetenergybasis.Theannualconsumptionisabout11,000kWhandalsoalittlemorethan11,000kWhofelectricityisgeneratedbythePVsystem.Comparedtothehouseholdin2021,theelectricitydemandforthehouseholdin2030in-creasesbyalmostafactorofthree,butthehouseholdin2030couldbecompletelyself-sufficientovertheyearonanetenergybasis.Figure:Monthlyenergyconsumptionofa4-personhouseholdin2030Source:WuppertalUniversityResearchquestions,assumptionsandmeth-odologies–DongqiaotouResearchframeworkTheresearchinthevillageofDongqiaotoufocusedonfol-lowingresearchquestions:Howlargearetheflowsofenergybetweenvariouslo-calsubsystems?Whataretheenergyconsumptionpatternsandenergyflowsofanaveragehousehold?Whichlocalrenewableenergyresourcesexistandhowhighistheself-sufficiencypotentialofthevillage?Whichdirectioncouldtheenergysystemdevelopmenttakeuptotheyear2030?Thestudytakesavillageastheresearchunitandexaminedenergyconsumptionactivitieswithinitsadministrativegeographicalboundary.Theframeworkmainlyincludes:Inputandoutputofenergyconsumption,thecalculationandidentificationofenergypro-ductionpotential,energymixandservicesatthevillagescale,energytransformationwithinthevillagesystem,-2000-1500-1000-500050010001500JanFebMarAprMayJunJulAugSepOctNovDecHouseholdEVsHeatPumpPhotovoltaickWh33theflowsofenergyconsumptionwithinthevil-lage.Coveringthecharacteristicsofproductionandlivingac-tivities,themodeldividesthewholeenergysystemintosixsubsystems:HouseholdsPublicspacesandsystemsFarmingLivestockIndustryEnvironmentThemodelexplorestheflowsofenergy,people,andmate-rials/products(withregardtoenergy,biomassinparticu-lar)withintheadministrativeboundaryofthewholevil-lage.Energyflowsaremeasuredinkilogramsofcoalequivalent(kgce).Regardingtheinputsection,themainsourcesofenergyavailableattheregionalscalearecon-sidered.Inadditiontothematerialflowinindividualsys-tems,itincludestheinteractionsbetweenthesubsystems.Theproducts,servicesandwastegeneratedintheprocessofinteractionarepartlyusedtomeetthelocalproductionandlivingneedsortheyarebeingdirectlydischargedintothelocalenvironment,whiletheremainderentersthemarketinthesocio-economicsystemoutsidethevillagetogeneratemorerevenue.Thewastegeneratedisfurthertransportedandconsumedthroughtheinteractionwiththeenvironmentalsystemoutsidethevillage.Figure:SchematicdepictionoftheenergyflowmodelSource:InstituteofAppliedEcologyattheChineseAcademyofSciences34Questionnaire-basedsurveyandsemi-structuredinterviewinDongqiaotouThequestionnairedesignandresearchreliedonacombi-nationoftop-downandbottom-upapproaches.Thetop-downapproachdevelopedtheframeworkanddeterminedtherelevantenergyindicatorsthroughdiscussionswithexpertsandresearchers.Thebottom-upapproachreliedonvillageinhabitantsandlocalcadrestounderstandtheinformationonhouseholdattributesandresourceutilisa-tionfromtheperspectiveofthemostbasicsocialunits,thusenablingtheirparticipationintheresearchprocess.Throughcommunicationwithtownshipcadres,research-ersunderstoodthelocaldevelopmentlevelandfromvil-lagecadres,theylearnedaboutthebasicsituationandfu-turedevelopmenttrendsofthewholevillage.Interviewingvillagershelpedtheresearchteamgaininsightintothecurrentdevelopmentstatusoffamilies.Lastly,theelderlyprovidedinformationonthedevelopmenthistoryofthewholevillage.Figure:OverviewofsurveytargetgroupandsurveyedinformationSource:InstituteofAppliedEcologyattheChineseAcademyofSciencesTheobjectivesofdatacollectionaredividedintosocio-economicinformation,villagepublicspaceandinfra-structure,andenergyuseandfutureplanning.Atthelevelofpublicspaceandinfrastructureinthevillage,thefocusisontransformationofthespatialtypeofthevillagefromtheperspectiveofproductionspace,livingspace,andeco-logicalspace.Acomprehensiveanalysisexaminedtheconfigurationofhouseholdspaceandpublicspaceandex-trapolatesthechangeintheuseofpublicinfrastructuresuchasstreetlights,roads,andgarbagedisposalpoints.Concerningenergyuseandfutureplanning,theanalysisalsoexploresthetransformationofthevillage’senergydemandintermsofenergyproductionandconsumption.Theanalysisexaminesresourceusedevelopmentinrela-tiontotheavailabilityoflocalresourcestoassessthepo-tentialtomaximiseutilisationoftheseresources.35FigureDongqiaotousurveyandinterviewprocessSource:InstituteofAppliedEcologyattheChineseAcademyofSciencesScenariosandassumptionsToanalysethepotentialfutureenergysupplyandcon-sumptionstructureinthevillage,thestudyusesthreesce-nariosbasedonthecurrentsituationinthevillageregard-ingPV,mobility,andheating.Regardingmobility,thereareabout1,010electricvehiclesinthevillagein2020.Mostofthese,however,aresmall-scaletwo-orthree-wheeledvehiclesforshorterdistances.Thisismadeupof560two-wheeledelectricvehicles,400three-wheeledelectricvehicles,and50four-wheeledelectricvehicles.Includinginternalcombustionenginecars,thereare220four-wheeledvehicles.Two-wheeledelectricvehiclesarelightandfast,andaresuitableforshort-distancetravelforoneortwopeople.Three-wheeledelectricvehiclesaremoresuitableforfamiliesorforhouseholdsthatneedtotransportgoodsorlargeitems.Atthesametime,withthepromotionofurbanisation,theagingofthepopulationinruralareasisprogressing.Olderpeopleoftenpreferthree-wheeledelectricvehicles.Four-wheeledelectricvehicleshavebecomethemeansoftrans-portationforsomefamiliesinthevillageunderthepro-motionofnewenergyvehiclesandhavebecomemorepopulargiventheirhigherspeedandcomfort.Weassumetwo-wheeledelectricvehiclesandthree-wheeledelectricvehiclesonaveragechargeduringsixhourseverythreedaysandthatfour-wheeledelectricvehicleschargeforeighthourseveryfivedays.Currently,thevillagereliesoncoalforheating,andonlyasmallnumberofhouseholdsuseelectricityforheating.TheheatingseasoninDongqiaotoutypicallylastsfourmonths,frommid-Novembertomid-March.RegardingsolarPV,atotalof32householdsinthevillagehadsolarPVinstalledasof2020.Householdswhoseroofareasarespaciousandsuitableforsolarpanelscanrenttheirrooftopstothepowersupplycompany.Communica-tionwithvillagersshowedthatmoreandmorefamiliesre-portawillingnesstoinstallPVpanelsandexpecttobenefitfromit.Thispapersetsupthreefuturescenariosbasedonthecur-rentdevelopmentstatusofthewholevillage:scenario1(baselinescenario),scenario2(moderategrowthscenario)andscenario3(optimisticscenario).Scenario1(baselinescenario):Thefuturedevelopmentofvariousenergy-usingdevicesinhouseholdsintheinves-tigatedvillageisbasedonthecurrenttrendsinthewholevillage.Thetotalnumberofelectricvehiclesinthevillagewillreach1,058by2025,and1,110by2030.Thenumberofair-sourceheatpumpswillbe10in2025and30in2030.ThenumberofhouseholdswithPVpowergenerationwillbe80in2025and145in2030.Scenario2(moderategrowthscenario):Thenumberofvariousenergy-usingdevicesinthesurveyedvillagehouseholdsshowsamoderategrowthtrend.Intermsoftheuseofelectricvehicles,thetotalnumberofelectricve-hicleswillbe1,115in2025and1,231in2030.Thenumberofair-sourceheatpumpswillbe25in2025and60in2030.ThenumberofhouseholdswithPVpowergenerationwillbe130in2025and250in2030.36Scenario3(optimisticscenario):Variouscleanenergytechnologiesinthevillageshowarapidgrowthtrend.Intermsoftheuseofelectricvehicles,four-wheeledelectricvehicleshavehugedevelopmentspaceinthefuture,sothetotalnumberofelectricvehicleswillbe1,229in2025and1,495in2030.Thenumberofairsourceheatpumpswillbe50in2025and110in2030.ThenumberofhouseholdswithPVpowergenerationinstalledwillbe200in2025and400in2030.Figure:TotalnumberofelectricvehiclesunderthreescenariosinDongqiaotouSource:InstituteofAppliedEcologyattheChineseAcademyofSciencesFigure:TotalnumberofhouseholdswithsolarPVunderthethreescenariosinDongqiaotouSource:InstituteofAppliedEcologyattheChineseAcademyofSciences32801453213025032200400050100150200250300350400450202020252030Scenario1Scenario2Scenario31010105811101010111512311010122914951000110012001300140015001600202020252030Scenario1Scenario2Scenario337Figure:Totalnumberofair-sourceheatpumpsunderthethreescenariosinDongqiaotouSource:InstituteofAppliedEcologyattheChineseAcademyofSciencesSurveyresults-DongqiaotouOverallenergystructureofthevillageIn2020,thewholevillageconsumed626,196kgceofen-ergy(5,106MWh),madeupof192,849kgceofelectricityfromthegrid(1,570MWh,30.7%oftotalenergyconsump-tion),208,960kgceofcoal(1,701MWh,33.3%oftotal),93,644kgceofliquefiedgas(762MWh,14.9%oftotal),and39,494kgceofgasolineanddiesel(322MWh,6.3%oftotal)fromthesocialandeconomicsystemsoutsidetheregion.StrawandhouseholdPVaccountforthebulkoftheenergyproducedlocally.HouseholdPVyielded90,030kgce(733MWh,14.4%oftotal)andstrawaccountedfor2,218kgce(18MWh,0.03%oftotal).Intheuseofenergy,electricityismainlyconsumedinthehousehold,publicfacilities,andindustrialdevelopmentsubsystems,ofwhichthehouseholdsubsystemisthelarg-estcategoryofelectricityconsumption,accountingforabout90.06%ofthetotal.Thehouseholdsubsystemisalsowherevirtuallyallcoalandliquefiedgasconsumptionoccurs.About97.93%ofthefueloilconsumptionoccursinthehouseholdlivingsubsystem,andlessthan3%isusedfortheagriculturalplantingsubsystem.Mostofthelocallyproducedstrawreturnstothefields.Thequantitiesusedforthehouseholdsubsystemare739kgce(6MWh),and1,479kgce(12MWh)inthelivestockandpoultrybreedingsubsystem.Overall,about70%ofthevillage’senergyinputcomesfromexternalpurchases,andabout30%ofitsenergyisproducedlocally.0103002560050110020406080100120202020252030Scenario1Scenario2Scenario338Figure:FlowsofenergyandmaterialinDongqiaotouinkgofcoalequivalent(2020)Source:InstituteofAppliedEcologyattheChineseAcademyofSciencesHouseholdenergyconsumptionstructureandcharacteristicsElectricityisthemainsourceofenergyforhouseholdap-pliancesinthehomeandactsasasupplementaryenergysourcefordailycookingandheating.Coalisthemostcom-montypeofenergyusedforhomeheatingandcoalalsoactsasasupplementarysourceofcookingenergy.Gasolineanddieselarethemostcommontypesoftransportationenergyusedinhouseholdsandserveasfuelsformecha-nisedfarming.About300householdsinthevillageuseso-larwaterheatersforactivitiessuchasdailybathwater,withapenetrationrateof67.26%.Duetothenegativeim-pactofburningstrawontheenvironment,localresidentsmostlyapplywastestrawtofields,andlessthan5%ofhouseholdsusestrawasahouseholdenergysource.Residentsmeetenergydemandthroughpurchasesandownproduction.In2020thepurchasedenergyaccountedfor89.46%ofthetotalenergyuse,and10.54%oftheen-ergycamefromthestrawproducedbyitself.Theuseofen-ergyathomeismainlyreflectedinhouseholdappliances,heating,cookingandtransportation.Cookinghasthelarg-estshareinhouseholdenergyconsumption,with48.42%ofthetotalenergy.Thisenergycomesfromelectricity,coal,liquefiedpetroleumgas(LPG),andstraw.Heatingisthesecondlargestenergyconsumingactivityinthesur-veyedvillages,accountingfor29.26%oftotalenergyuse,mostlyfromcoalandtoasmallpartfromelectricity.Transportationenergyuseincludeselectricvehicles,in-ternalcombustioncars,andmotorcycles,whichconsume10.81%ofthetotalenergy.39Figure:AveragehouseholdenergyconsumptionstructureinDongqiaotou(2020)Source:InstituteofAppliedEcologyattheChineseAcademyofSciencesFigure:EnergyandmaterialflowsinanaverageDongqiaotouhousehold(2020)Source:InstituteofAppliedEcologyattheChineseAcademyofSciencesAnalysis-DongqiaotouSelf-sufficiencypotentialInthehouseholdsubsystem,thetotalenergyconsumptionofthewholevillageis514,812kgce(theenergyequivalentto4,191MWh).Giventhattherearealreadyabout350householdsandfamiliesinthevillageusingsolarwaterheaters,iftheheatcollectedbythesolarwaterheaterscanbeusedmoreefficiently,theenergyproductionpotentialthatcanberealisedis406,634kgce(3,310MWh),whichmeansthattheexternaldependenceofenergyinthehouseholdcanbereducedby78.99%.Inthepublicfacilitiessubsystem,theenergyconsumptionmainlycomesfromtheelectricityconsumptionofstreet-lights,villagecommitteeandthevillagehealthroom,to-talling1,697kgce(14MWh).Consideringtheeconomic29%42%13%10%6%1%ElectricityCoalLPGStrawGasolineDiesel40benefitsandusagecostsoftheexistingstreetlights,iftheyarereplacedwithsolarstreetlights,thetotalannualelec-tricitygenerationwillbe11,455kgce(93MWh).Besidessolvingtheenergyconsumptionprobleminthissystem,PVstreetlightscanalsosupplementotherenergyusesub-systems.Intheagriculturalplantingsubsystem,theamountofcropstrawproducedis7,394,465kgce(60,198MWh).Asmen-tionedabove,mostofthestrawisappliedtothefields,andonlyasmallportionisusedforfeedandhouseholdfuel.Ifthestrawisutilisedasaresource,theusablepotentialofstrawis3,459,821kgce(104,832,576MJ),whichwouldmeettheenergysupplydemandinthissystem.Inthelivestockbreedingsubsystem,thetotalamountoflivestockmanureproducedbylarge-scalebreedingandretailbreedingis89,851kgce(2,722,485MJ).Specialisedinstitutionsdirectlypurchasemuchofthelivestockma-nureproducedbylarge-scalebreeding,whilethelivestockmanureproducedbysmall-scalebreedingismostlydumpeddirectlyaswaste.Collectingitinaunifiedmannerwouldyieldafertilisationandenergypotentialfromlive-stockmanureof798,142kgce(24,183,703MJ).Intheindustrialdevelopmentsubsystem,thetotalenergyconsumptionbroughtbycoldstorageis18,281kgce(553,914MJ),andfortheshort-andmedium-term,nore-sourcepotentialhasyetbeenidentifiedandweassumethiswillcontinuetorelyonexternalenergysupply.Throughthecomprehensiveanalysisofeachsubsystem,itcanbeseenthatintheentirevillagesystemtheenergyconsumptionis7,484,280kgce(226,773,684MJ),andtheproductionpotentialis4,727,071kgce(143,230,251MJ).Iftheenergyineachsystemisreasonablydeveloped,theen-ergyself-sufficiencywillriseto63.16%.Figure:UtilisedandunutilisedenergypotentialsinDongqiaotou(2020)Source:InstituteofAppliedEcologyattheChineseAcademyofSciencesSeasonalenergyconsumptioncharacteristicsofDongqiaotouEnergyconsumptionofthevillagesubsystemsvariesacrosstheyear.Forhouseholds,energyconsumptionchangesrelativelymuchthroughouttheyear.HotsummerweatherfromJunetoAugustleadstoanincreaseinenergyconsumptionforairconditioningandrefrigeration.Dur-ingtheChineseNewYearholidays,workersandstudentsreturnhometoruralareas,whichincreaseshouseholden-ergyconsumptionduringthisperiod.Intermsofhouse-holdenergyproduction,thereisnosignificantdifferenceintheamountofenergyproducedintherestofthemonths,exceptduringthewintermonths,whencoldtemperaturescauseadropinsolarwaterheating.Streetlightsandvillagecouncilsessionsaccountsforthemajorityofthepublicspaceenergyconsumption.Thereisnonoticeabledifferenceinusagethroughouttheyear.In4727306748428063.16%4,727,3067,484,280utilizedpotentialunutilizedpotentialkgce41theagriculturalsubsystem,thelocalcropsofpotatoesandcornareplantedinJanuary-Februaryforpotatoes,andcorninMay.Mechanisedtoolsintheplantingprocesscausesanincreaseinfuelandotherenergyuseduringtheseperiods.TheharvestseasonisMay-JuneforpotatoesandSeptember-Octoberforcorn.Thereisanincreaseinagriculturalwasteduringthesemonths.Inthelivestockfarmingsystem,forfarmsraisingalargenumberofpoultrytheelectricityconsumptionforventila-tionandtemperaturemanagementisrelativelyhigherinJune-August.ScenarioResultsforDongqiaotouScenario1(baselinescenario):Theannualelectricitycon-sumptionforchargingofthethreetypesofelectricvehi-clesis384,182kWh(onaverage861kWhperhousehold)in2025and609,365kWh(onaverage1,366kWhperhouse-hold)in2030.Theuseofairsourceheatpumpsinheatingcanreplace12tonsofcoalin2025and36tonsofcoalin2030.RegardingPVpowergenerationonrooftoptypicalhouseshaverooftopareadimensionsofaround14metersby19meters.TherooftopareaavailableforPVisabout112m2.Dongqiaotouhas1,982sunlighthoursperyearonav-erage,implyingthemaximumpotentialrooftopoutputinthisscenariois1,829.875MWhin2025(225,075kgce)and3,316.648MWhin2030(407,948kgce).Scenario2(moderategrowthscenario):Electricitycon-sumptionforEVchargingis418.267MWhin2025(onav-erage938kWhperhousehold)and693.471MWhin2030(onaverage1,555kWhperhousehold).Theuseofairsourceheatpumpsinheatingcanreplace30tonsofcoalin2025and72tonsofcoalin2030.Thetotalamountofelec-tricitythatPV-poweredhouseholdscangenerateis2,973,547kWh(365,746kgce)in2025and5,718,359kWh(703,358kgce)in2030.Scenario3(optimisticscenario):Intheenergysubstitu-tioneffectunderthisscenario,theelectricityconsumptionofEVchargingis513.154MWhin2025(onaverage1,151kWhperhousehold)and112.937MWhin2030.Theuseofairsourceheatpumpsinheatingcanreplace6,000kgofcoalin2025and132,000kgin2030.ThetotalamountofelectricitythatPV-poweredhouseholdscangenerateis562,687kgce(4,574.687MWh)in2025and1,142,254kgce(9,286.616MWh)in2030.42Figure:EnergyandmaterialflowsinDongqiaotou(Scenario1,2025)Source:InstituteofAppliedEcologyattheChineseAcademyofSciencesFigure:EnergyandmaterialflowsinDongqiaotou(Scenario1,2030)Source:InstituteofAppliedEcologyattheChineseAcademyofSciencesUndertheexistingdevelopmentmodel,theenergyself-sufficiencyrateofthesurveyedvillagesin2020is16.83%.InScenario1(baselinescenario),theself-sufficiencyrateofthewholevillageis36.81%in2025and57.48%in2030.Consideringonlytheelectricityproductionandusageofthewholevillage,thevillage’sself-sufficiencyrateoftheelectricitysupplyin2020is46.68%,anditcanreach84.22%in2025.By2030,theannualelectricityproductionfromlocalresourceswouldbeat115.84%ofannualdemandandthuswouldexceedthetotalannualelectricityconsump-tionofthewholevillage.InScenario2(moderategrowthscenario),theself-suffi-ciencyrateofthewholevillageis56.98%in2025and89.94%in2030.Ifonlytheelectricityproductionandus-ageofthewholevillageisconsidered,theannualelectric-ityproductionin2025exceedstheelectricityconsumptionofthewholevillage,at122.85%ofconsumption;and165.69%ofconsumptionin2030.InScenario3(optimisticscenario),theself-sufficiencyratesofthewholevillageare80.70%in2025and126.16%in2030.Ifonlytheelectricityproductionandusageofthewholevillageisconsidered,theannualelectricityproduc-tionin2025and2030exceedstheelectricityconsumptionofthewholevillage,at159.33%in2025,and208.50%ofconsumptionin2030.ThescenarioanalysisshowsthatDongqiaotoucanproducemorepowerthanitneedsoverayear.However,asinthecaseofSchwaig,energyconsumptiondoesnotalwaysco-incidewithsolarPVoutputtimes.Thismeansthatwithoutsignificantenergystoragecapacities,duringthedaytimethevillageanditshouseholdswouldbemorelikelytofeedinsurpluspowerintothegrid(asfarasgridcapacityper-mits),thusgeneratingrevenue,whilepurchasingpowerduringthenight.Thisanalysisfocusedontheself-sufficiencypotentialofDongqiaotouwithregardtosolarPVandassuminginten-43sifyingelectrificationinheatingandmobility.Solarther-malsolutionsalreadyarebeingusedinDongqiaotouandthevillagestillcanextendtheirapplication.Theycanmakeanadditionalcontributioninhotwatergeneration.More-over,theself-sufficiencymodellingdidnotconsiderin-depththepotentialfromthebiomassproducedinandaroundthevillage.Thisbiomasscouldbeprocessedfur-therandeitherutilisedtosupplementheatingenergyandpowerthroughsmallcombined-heat-and-powerplantsifnosolarenergyisavailableorsoldtolargercentresintheregion.Householdself-sufficiencypotentialundercontinu-ingelectrificationIncontrasttotheresearchconductedinSchwaig,limiteddataavailabilityinChinacomparedtoGermanyrequiredadifferentapproachtomodellingandassessingself-suffi-ciencypotentialswithanincreasingamountofPVpowergenerationandadoptionofEVsandheatpumps.Therefore,themodellingfocusesonthesituationofahypotheticalhouseholdthathasrooftopPV,anair-sourceheatpump,a(four-wheeled)electricvehicle,andahouseholdenergyconsumptioninlinewiththesurveyfindings.Thisrepre-sentsahouseholdconfigurationthatislikelytobecomeincreasinglycommonupto2030.Themodelsimulatesthehousehold’sPVpowergeneration,thepowerconsumptionofelectricvehiclesandairsourceheatpumps,andhouseholdelectricityconsumptionofatypicalhouseholdintheweekof1January2020to7Janu-ary2020.Thediagrambelowshowstheenergyconsump-tionloadofasinglehousehold.Thetotalenergyconsump-tionofasinglefamilyforaweekis962kWh,andthenetloadis523kWh.MostofthehousesinDongqiaotouVillagearefree-stand-inghouses.TheaverageroofareaforinstallingPVpanelsis112squaremeters.ThetotalPVpowergenerationofahouseholdinaweekisabout439kWh.ThedailyPVpowergenerationtimegenerallyis9hours.Onaverage,thedailyPVpowergenerationcapacityofonehouseholdisrela-tivelystable,maintaininganoutputmostlybetween50-70kWh.Theaveragedailyoutdoortemperatureselectedunderwhichtheairsourceheatpumpoperatesis-3.03°C,theminimumis-11.3°C,andthemaximumis5.7°C.Thether-malcoefficientofperformance(COP)oftheairsourceheatpumpunitsystemisbetween2.2-2.9.Theaveragedailypowerconsumptionofthesystemis92kWh,withamaxi-mumpowerconsumptionof5.25kWperhourandamini-mumof2.36kW.Thedailychargingpeakperiodofelectricvehiclesismainlyfrom5pmintothenight.Theaveragedailychargingcapacityis3.95kWh,thedailymaximumchargingcapacitycanreach4.46kWh,andtheminimumis2.74kW.Theaveragedailyelectricityconsumptionofthehouseholdforotheractivitiesis42.13kWh.Becausecook-ingandothertoolsmostlyrelyonelectricity,thedailypeakhoursofelectricityconsumptionaremostlyinthemorn-ing,noonandevening.44Figure:EnergygenerationandconsumptionofahypotheticalhouseholdwithrooftopPV,air-sourceheatpumpandanEV,inwinterweek(2020)Source:InstituteofAppliedEcologyattheChineseAcademyofSciencesTheenergyconsumptionloadofatypicalhouseholdinthesummerof2020(July1,2020-July7,2020)isshowninthefigureabove.Thetotalenergyconsumptionofasinglehouseholdforaweekis311kWh,withanetloadof-191kWh.ThetotalPVgenerationofahouseholdforaweekinsummerisabout502kWh,withaproducingperiodfrom6a.m.to7p.m.,intotalofabout13hours.ThedailyPVgen-erationismaintainedatabout60-80kW.Thetotalenergyconsumptionofheatpumprefrigerationis95.2kWhandtheaveragedailyenergyconsumptionis13.6kWh.Theusetimeismostlyconcentratedinthedaytimefrom10:00amto2:00noonandatnight.RegardingtheloadofEVs,themodelassumesthesamefiguresasinthewinterweek.Theaveragedailyelectricityconsumptionofthehouseholdforotheractivities26.49kWh,withamaximumdailycon-sumptionof27.54kWhandaminimumof21.71kWh.0%10%20%30%40%50%60%70%80%90%100%-15-10-5051015ShaderPhotovoltaicHeatpumpsEVHouseholdTotalload(HP+EV+HH)WedThuFriSatSunMonTuekW45Figure:EnergygenerationandconsumptionofahypotheticalhouseholdwithrooftopPV,air-sourceheatpumpandanEV,insummerweek(2020)Source:InstituteofAppliedEcologyattheChineseAcademyofSciencesThesemodellingresultsforonehouseholdshowthatusu-allysolarPVoutputexceedstheloadduringtheday,givingthehouseholdtheopportunitytogeneraterevenuefromfeedingpowerintothegridduringthedayor,ifbatterystorageispresent,toreduceexpendituresforpurchasingpowerfromthegridduringthenight.DiscussionofdifferencesbetweenthetworesearchapproachesDuetodifferentsituationsregardingdataavailabilityandeconomicdevelopmentstatus,researchactivitiesinSchwaigandDongqiaotoufolloweddifferentapproachesandmethodologies.Whereasbothcasesincludedasurveyofresidents,thestudyofSchwaigalsoemployedlocalgriddataandaregionalisationmethodologytocomplementthesurveydataandvalidatetheresults.InDongqiaotou,nolocalgriddatawereavailable,andthenationalandpro-vincialdataandstatisticsavailabledidnotenableacom-parableregionalisationmethodology.TheChinesere-searchteamhadexploredtheviabilityofapplyingare-gionalisationmethodologytoDongqiaotou,however.Duetothegooddataavailability,theresearchconductedinSchwaigcouldproducemodellingresultsfortheentirevil-lageduringsummerandwinter.DuetothemorelimitedavailabilityofdatainDongqiaotou,thiskindofmodellingwasnotviable.However,basedonsurveydata,scenarios,andweatherandinsolationdata,itwaspossibletomodelthesituationofahouseholdwithsolarPV,aheatpump,andanelectricvehicleoverawinterweek.Acomparablehouseholdwouldbecomeincreasinglycommonby2030underthescenariosdevelopedinthisstudy.Whiletheag-gregateofhouseholdsandconsumersinDongqiaotouislikelytoshowcertaindifferencesforindividualhouse-holds,householdsstillmakeupmostofDongqiaotou’sen-ergyconsumption,thereforeevenmodellingasingletyp-icalhouseholdprovidesmeaningfulinformationabouttheentirevillageandgivesinsightsintoitsself-sufficiencypotential.Itshouldbenotedthatduetothedifferencesinmethodol-ogiesandmodelsthatthetworesearchteamsappliedandduetodifferentkindsofinputdata,theself-sufficiencyestimatesthatresultedforthetwovillagearenotdirectlycomparable.Nevertheless,thetwodifferentapproachesstillpointtocertainsimilaritieslikeexcessgenerationofsolarpoweratcertaintimesandshortfallsatothers.0%10%20%30%40%50%60%70%80%90%100%-12-10-8-6-4-20246kWWedThuFriSatSunMonTue46AvillageinGermanyandChinaintheyear2030SchwaigTheanalysisinthisstudyshowsthathouseholdsinSchwaig,andthevillageasawhole,haveahighpotentialforself-sufficiencyinthesummer,providedeitherenergystorageorV2Gareadoptedlocally,whereaswinterheatingloadsandlowrenewableoutputinthewinterwillentailheavyusageofgridenergyoradditionofsomesortofsea-sonalstoragetechnology.DemandforelectricalenergyinSchwaigwillincreasesig-nificantlyby2030,whileotherenergysourcessuchasoilandgaswillbesubstitutedgradually.InSchwaig,electricalenergyconsumptionmayrisetobetween3,750MWhand4,700MWh,basedonthescenarios.Ifpurelyelectricalhouseholdandindustrialconsumptionisusedasacom-parison,thismeansanincreaseof50%tojustunder90%comparedwithcurrentdemand.Heatpumpsarethemaindriveroftheincreaseindemandforelectricity.Thesere-quirealotofelectricity,especiallyinwinter.Theaddi-tionaldemandfromEVsislesssignificant,especiallywhencomparingtheTrendandOptimisticscenarios.ItcanbeseenthatintheTrendscenariotheenergydemandofEVsandheatpumpsisquitesimilar,whileintheOptimisticsce-nariotheenergydemandofheatpumpsexceedstheenergydemandofEVsbyalmostafactorof2x.Ontheenergysupplyside,PVwillplayacentralrole.Thereisalreadyacomparativelyhighinstalledcapacitythere,whichwillmorethandoublebytheyear2030.Inbothscenariosdescribedabove,PVcanprovidearound30%oftotalenergyconsumptionoverthecourseofafullyear.Ifconsideringonlythedemandforelectricity,PVcanpro-videasmuchas49-56%ofthetotalannualelectricityconsumption.Iftheelectricitysupplyisbrokendownbymonth,self-sufficiencyratesdifferwidelyfromthean-nualmeanvalue.Inthewintermonths,onlyaboutatenthofthedemandcanbecoveredbyPV,whileinthesummermonthsmorethan100%ofthedemandcanbecovered.Forthisreason,long-termstoragesystemssuchasbatterystorageorhydrogenstoragewouldhavetobeconsideredforSchwaigtoachievegreateroverallself-sufficiencyin2030.Whenconsideringenergysupplyanddemandover15-mi-nuteintervals,twopointsstandout.Firstisthenecessityofdailyenergystoragecapacity.Especiallyinsummer,whenthereisasignificantoverproductionofPVpower,storagecanleadtohighself-sufficiencyrates.Second,itisunnecessaryforSchwaigtoinstalllargeamountsofstand-alonestorageiftheresidentsadoptEVswithV2Gtechnology,sinceatnight,whenthevehiclesarestation-ary,vehicle-to-grid(V2g)technologycouldmakeamajorcontributiontohighself-sufficiencyrates.Insummary,inSchwaig2030,alargepartoftheenergywillbeprovidedbyPVandthedemandforelectricalenergywillkeepincreasingduetoheatpumpsandEVs.Ifseasonalenergystoragesystemsbecomeavailable,theexcesselec-tricityproductioninthesummercanalsobeusedinthewintermonthsandahighself-sufficiencyratecanbeachievedforSchwaigoverall.Furthermore,fordailyloads,V2GoffersthepossibilitytousetheexcessproductionofdailyPVpowerduringthenight.Forlong-termstorage,however,separatestorageunitsmustbeinstalledbecauseEVsarenotapracticalsolutionforlong-termstorage,eventhoughtheyarestationaryformuchofthetime.DongqiaotouThesimulationsandscenariosusedinthisstudyshowthatrooftopsolarPVcapacityandPVpowergenerationcouldincreasesignificantlyinDongqiaotou,andthatelectrifi-cationoftransportandheatingmayalsoincrease,alt-houghthedegreeofelectrificationdependsontechnologydevelopmentsandpolicysupport.Heatpumpsandelectricvehiclesshouldexperiencesignificantgrowthupto2030,althoughthereisalargevariancebetweenscenariosandadequatepolicysupportwillbenecessarytorealisethispotential.Commontrendsareanincreaseduseoflocallyproducedpowerwhileimportsofpowerandotherfuelsdecrease,thereforeleadingtoanincreasedself-suffi-ciencyrate.ThelocalenergyproductionofDongqiaotouin2020meets16.8%ofallenergydemand.Undertheassumptionthatre-newableenergydevelopmentandelectrificationcontinuessteadilyasforeseeninChina’snationalpolicy,self-suffi-ciencyonanannualbasiscouldincreaseto90%orupto126%in2030,dependingonthescenario.Thismeansthatby2030,Dongqiaotouhasthepotentialtoproducemoreenergythanitconsumesoveroneyear,inprinciple.In-deed,solarenergyproductioninDongqiaotouhaslower47seasonalvariationthaninSchwaig,reducingtheseasonalimbalanceinelectricitysupplyanddemandinahighelec-trificationscenario.However,justasinSchwaig,renewa-bleenergygenerationlargelyoccursduringthedayandsolarpowerisunavailableatnight-timeunlessstorageisavailable.WhileDongqiaotouin2030mighthavethetech-nicalpotentialtoreachcompleteself-sufficiencyinelec-tricity,thecostofrequiredstorageprobablywouldbeun-economical.Asdemonstratedbythesimulationahypotheticalhouse-holdwithPV,heatpump,andanEV,Dongqiaotouin2030couldgenerateasurplusofelectricityduringthedaythatusuallycanmeetallitsdemandduringdaylighthours.Whilesomeoftheexcesspowermaybestoredinbatteriesorheatstorageforuseduringnighttime,themosteco-nomicalapproachforDongqiaotou,andothervillageswithsimilarconditions,likelyentailsavoidinghighpeak-hourpowerpricesviaself-consumptionandexportofsurpluspowerduringtheday,whileimportingpowerduringthenight,benefittingfromlowernighttimepowerprices.48PolicyrecommendationsGermanyOurresearchonenergyflowsandtechnologyadoptioninSchwaigshowsthatsmall,ruralcommunitieshavethepo-tentialtobecomehighlyself-sufficientby2030,atleastonanetbasis.Duetolowbuildingdensityandtheresultinglargeopenspaces,ruraltownshaveroomforlargeamountsofrenewableenergycapacity.Notonlycantheyachievehighself-sufficiency,buttheirenergysurplusescanfeedintothegridandtherebyraisetheshareofCO2-neutralelectricityregionally,compensatingforshortfallsinurbanareaswithlowerrenewablepotential.Sinceruralareasplayacentralroleintheenergytransition,politicalframeworksshouldfacilitateexpansionandfur-therdevelopmentofruralrenewableenergyandstorage,intandemwithelectrificationofruraltransportandheat-inginruralcommunities.ArangeofmeasurescanpromoteanacceleratedexpansionofwindenergyinGermany.Manyexpertsandindustrygroupsthereforehavecalledforpermittingprocedurestobecomeasshortandsimpleaspossiblewhilestillmeetingthelegitimateinterestsofstakeholdersandadequateen-vironmentalprotectionstandards.Proceduresshouldbereorganisedinawaythatprotractedandconsecutivelegalchallengesgivewaytomorecondensedprocessingoflegalclaimswithinashortertimeframe.Moreover,distributedwindandsolarenergyprojectsshouldbecomemorefinanciallyattractiveforthehostingruralcommunity.ThiscanbeachievedbyremuneratingruralcommunitieswithapaymentperkWhproducedandfurtherimproveincentivesforhouseholdrooftopPVthatcombinefeed-intariffsandself-consumption.Thiscancontributetogreateracceptancebyruralresidents.AnotherinstrumentthatGermanyalreadyisusingtoim-proveacceptanceiscomprehensivestakeholderinvolve-mentearlyoninprojectplanning.Germany’snewfederalgovernmenthassetthetargetofmaking2%ofGermany’sareaavailableforwindenergy.Addressingtheseobstaclestorenewableenergyexpansionisofhighimportance.TheGermanFederalGovernmentalreadyhasstartedtoad-dresstheproblemsbasedontheabovesuggestionsin2022,includingnationallyunifiedspeciesprotectionstandards,acceleratedpermitting,andworkingtowardslowermini-mumdistancerequirements.Regardingdistributedsolarenergy,theGermangovernmenthasannouncedthatnewlybuiltbuildingsshouldingeneralincluderooftopso-larandisworkingtowardsmakinghybridfeed-intariffandself-consumptionmodelsmoreattractive.41GermanypresentlylagssomeotherEuropeancountriesinelectricheatpumpadoption.Greaterincentivesforre-placementofolderboilers,andforhomeenergyretrofitsingeneral,arelikelynecessarytopromotetheenergytransitioninruralareas,givenpresentlowratesofenergyretrofitandthecommontendencyofconsumerstoseekthelowest-costreplacementofolderheatingsystems,whichoftenresultsinlostenergysavingsandmissedop-portunitiesforelectrification.Ascrappagepremiumforfossilfuelboilersreplacedwithelectricheatpumps,alongwithapublicinformationcampaignonthehealthbenefitsofeliminatinghouseholdoilandgascombustion,couldhelppushmorehomeownerstomaketheswitch,whilesimultaneouslyencouragingtheindustrytomoveawayfromfossilfueltechnologies.Availabilityofqualifiedtech-niciansandmechanicstoinstallahighnumberofheatpumpsalsocanbeabottleneckthatvocationaltrainingmustaddressinatimelymanner.Giventhehighvariabilityofdailyandseasonalenergyconsumptionandproduction,energystoragewilllikelybecomeanimportantelementoftheruralenergytransi-tion.Policiestopromoteenergystoragesystemsinruralareascanhelpensurethatthesetechnologieskeeppacewithrenewabledeployment.ThecaseofSchwaigsuggeststhatlong-term(seasonal)andshort-term(daily)storagearebothnecessaryinsuchregions.Forlong-termstorage,hydrogenstorageandelectrolysisappeartoofferstrongpotential.Whilewedidnotexplicitlystudyvehicle-to-gridinthismodelling,V2Gofferspotentialforshort-termorintradaystorage,becauseelectricityconsumptionfordailyEVtripsisfarlowerthanthecapacityoftypicalEVbatter-ies.V2Gappearsattractiveevenassumingbatterylife-re-latedconcernslimitV2Gtojust20-30%ofbatterycapacityforbalancingpeakloads.Ofcourse,theeconomicsofdailyandseasonalenergystoragearelikelytobeacriticalfactorindeterminingwhetherhouseholdsorruraltownsshouldopttoinvestinstoragetoachieveself-sufficiencyforgreaterresilienceandattaininglow-carbongoals.Smartmeters,dynamictariffs,andbonusesforparticipa-tioninload-balancingactivitiessuchasvirtualpowerplantsorutilityloadmanagementcouldhelpencouragesuchtechnologiesinGermany.Digitisationwillalsore-quireapoliticalframeworkandcorrespondingincentives49toenableroll-outofinformationandcommunicationtechnology(ICT).Suggestions:1.Encourageruralcommunitiestopursuecomprehen-siverenewableenergyandelectrificationschemes,throughcommunityplanning,informationsharingplatforms,andpubliccampaigns.2.Developnationalandregionalpoliciestopromoteheatpumpadoptionthroughscrappagepremiums,publichealthcampaigns,andsupportfortransformationoflocalheatingserviceproviders.Ensurethatincentivesreachbothhouseholdsandlocalheatingsuppliers.3.AsmoreEVmodelswithV2Gcapabilityreachthemar-ket,explorevillage-levelpilotslinkingV2Gwithlocalexcesssolarproduction.4.Accelerateadoptionofdigitalenergyplatformsandservices,includingsmartmeters,dynamicenergytar-iffs,andrelatedbusinessmodels.ExplorevirtualpowerplantpilotsaimedatthevillagelevelinregionswithhighpenetrationofPV.ChinaInsomerespects,China’sruralenergytransitionisatanearlierphasethanthatofGermany,andthatiscertainlythecasewhencomparingthetwovillagesofSchwaigandDongqiaotou,giventhattheformerhasaconsiderableamountofrooftopPV.ChinaalsohasruralPV,butitmaybemoreconcentratedinpilotvillagesunderthepovertyalleviationsubsidyprogram.Ourparallelanalysesofthetwovillagessuggeststhatthetwovillageshavesimilarpo-tentialforenergytransformation,involvingadoptionofrooftopPV,EVs,andelectricheating/cooling.However,theirpathwaystoachievesuchatransformationarelikelytodiffer.Forexample,therapidlyfallingcostsofsmallEVsinChinacouldenablerelativelyrapidadoptionofthistechnology,whilethelowcostofcoalheatingmayhinderadoptionofheatpumpsandenergyefficiencyretrofitsinlow-income,ruralregions.Giventhesedifferences,poli-ciesandprogramsalsowilldiffer.DistributedenergyinruralareasfacesmorebarriersinChinathaninGermany.Theseincludeslowgridconnec-tions,inadequatedistributiongridsinruralareas,andlowawareness.HouseholdPVcouldhelppovertyalleviationeffortsinShandongbyloweringhouseholdenergyex-pendituresorgeneratingrevenue.Agrivoltaicsanddis-tributedwindenergycouldalsosupplementagriculturalincomes,thoughthiswilllikelyentailchangestopresentlanduseandplanningprocesses.However,enablingthistransformationwillnecessitategridcompanieshaveade-quateincentivestoinvestinupgradingruraldistributiongrids.Giventhecostofsuchupgrades,andthepotentialforEVs,energystorage,andheatpumpstoenableload-shift-ingandpeak-shavingatthevillageandhouseholdlevel,weexpectitwillalsobecomeeconomicaltocreateincen-tivesforhouseholdstopreventovergenerationorexces-sivepeakload.Biomassandbiogaspowerandheatgenerationhasacon-siderablepotential.Dependingonthelocaldemandsitua-tionandinfrastructure,biomassorbiogasplantseithercouldsupplyvillagesthroughsmallheatinggridsorlocalproducerscouldsellbiomass/biogastonearbylargercon-sumptioncentres.Enablingthismayrequireaccessforbi-omassproducerstofinancingandsupportbyregionalgovernmentsinconveningandcoordinatingrelevantac-torsandcreateaconducivebusinessenvironment.Utilisa-tionofbiomassmustbesustainableandshouldnotcom-petewithfoodproductionandshouldensureconservationoflocalbiodiversity.Giventhehighup-frontcostandlowawarenessofPV,ru-ralcollectiveeconomicorganisationsshouldbeencour-agedtojointlyinvestandoperaterenewableenergypowergenerationprojectswithcompaniesbymeansoflanduserightsorjointventures.Germany’scitizencooperativesprovideexperiencesandamodelthatcaninformthede-velopmentofcomparableorganisationsthatsuittheChi-nesecontext.Financialinstitutionsshouldbeencouragedtoprovidefinancingsupportforsmall-scale,villagere-newableenergyprojects.Duetothehighcostofcentralisedheatingsystemsinruralareas,decentralisedsolutionsappearthebetteroptionforreplacingcoal.TheabundanceofsolarPVelectricityinmanyareasinChinacreatesidealconditionsforoperatingheatpumpsinconjunctionwithPV.Incombinationwithheatstorage,PVandheatpumpsintandemcandrasticallyloweroperatingexpendituresforheatingwhileimprovinglocalairquality.However,currentlyheatpumpadoptionstillishamperedbyhighup-frontinvestmentcostswhichcanbeaparticularchallengeforlessaffluentruralhouse-holds.Manybuildingsinruralareashavepoorinsulationandhighheatlosses.Improvingbuildingefficiencyispar-ticularlyeffectiveinconjunctionwithheatpumps,becausethisallowsservicingthebuildingwithsmaller,lessexpen-sivesystems.However,efficiencyimprovementscoveringtheentirebuildingmayexceedthemeansofmosthouse-holds.Thestudydidnotcoversolarthermalsolutionsex-tensively,butthesealsocanmakeanimportantcontribu-50tiontohotwatersupply.Thesesystemsarealreadywide-spreadinmanyruralareasandhavescopeforfurtherex-pansion.Forthesereasons,financialincentivesforhousehold-levelenergyimprovementsarenecessary.Preferentialloansorgovernmentsubsidiesforheatpumppurchaseandinstal-lationcanlowerthefinancialbarriersbybringingcoststoalevelthatisequalorsufficientlyclosetoincumbenttech-nologies.Inaddition,supportschemescouldincentivisetheretirementorreplacementofexistinginefficientheat-ing/coolingsystemswithheatpumpsandcouldcomple-mentpurchasesubsidieswithascrappagepremiumforre-tiringinefficientheatingsystems.Anotheravenueforpro-motingheatpumpinstallationsissettingatargetforelec-trificationofheatinginavillage.Supportschemescouldfocusonselectiveefficiencyim-provementsarelikelynecessarytoencourageenergyret-rofitsofolderbuildings.Higherbuildingenergystandardsshouldbeenforcedforallnewbuildings,withsubsidiesavailabletoensureaffordability.Besidesfinancialsupportinformofpreferentialloans,provincialandlocalgovern-mentsshouldpromotethelocalpresenceofqualifiedex-pertstoassessandselectsuitableenergyefficiencymeasuresandenhancetrainingopportunitiesifnecessary.Presentpoliciesonenergystoragefocusoncentralisedorgrid-sitedstorage.Asthisstudyshows,village-sitedstor-agehasadvantagesinlevellinglocalloadprofilesandre-ducingtheneedfordistributiongridinvestment.Duetoacomparativelysmallloadfromlargerelectricvehiclesintheupcomingdecade,innovativesolutionslikevehicle-to-gridareunlikelytoplayasignificantroleinthistimeframe.However,pilottrialsinruralareasthataremoreadvancedwhenitcomestodistributedPVandEVowner-shipcouldbeofinterest.ThepotentialforabundantpowergenerationfromsolarPVinmanyruralareasinChinacreatessynergieswithelectricvehiclesashouseholdswithownPVgenerationcansavespendingonfossilfuelsfortransportation.Similartotheheatingsector,additionalfinancialincentivesmayberequiredtoinducehouseholdstoswitchfromtheincum-bentfossiltechnology.ProvincialorlocalgovernmentscanpurchasesubsidiesorscrappagepremiumswhereownerscanexchangeoldfossilfuelvehiclesforadiscountonanewEVpurchase.Inadditiontothefinancialaspect,in-creasedEVadoptionalsorequiressufficientavailabilityofcharginginfrastructureaswellasskilledtechniciansandservicepointsforrepairsandmaintenanceinthesur-roundingarea.Wealsosuggestthatlocalgovernmentspursuinglocalen-ergytransitionmeasureswillalsorequireacomprehensivenationalframework.Forlocalandprovincialgovernmentstoenactregulatoryandfinancialmeasurestopromotere-newableenergyexpansionandelectrificationinmobilityandheatinginaccordancewithlocalconditions,itisim-portantthattheyhavethenecessaryfinancialmeansandanationallevelframeworkwithcleartargetsandresponsi-bilities,whichrequiressupportandcoordinationfromthecentralgovernment.Suggestions:1.PromoteruralrenewableenergyviaPVandbiomass,withafocusonenablinggreaterself-sufficiencyinruralenergyconsumption.EncourageruralvillagestopursuerenewableenergyintandemwithChina’sna-tionalframeworkofcarbonpeakingandcarbonneu-trality,step-by-stepboostingenergyproductiontosubstitutefossilfuelconsumptioninheating,transport,andgridelectricityconsumption.2.Improveincentivesforgridmodernisationinruralar-easwhilealsoincentivizingpeak-shavingandloadsmoothingatthevillagelevelviatariffs,advancedmetering,andincentivesforlocalenergystorage.3.Developcomprehensivelocalincentivesforelectrifi-cationofheatingandtransport,includingpotentialtargetsforelectrificationaswellascomplementarybuildingenergyefficiencyretrofitstoreducetheover-allcostofelectricheating.4.Stronglyencouragegreenfinancialproductsandlow-costfinancingforvillage-levelrenewableenergypro-jects,energyefficiencyupgrades,andelectrificationofheatpumpsandtransport.51ConclusionsTheresearchinSchwaigandDongqiaotouhasshownthatdespitedifferencesineconomicdevelopmentlevelanddifferentstagesoftheenergytransitioninChinaandGer-many,villagesandruralareasinbothcountrieshavethepotentialtoplaysignificantrolesintheircountries’energytransitions.AnalysisbasedonsurveysandsubsequentscenariomodellingshowedthatbothinGermanyandChina,villagescouldproducemoreelectricityfromrenew-ablesourcesthantheyconsumeovertheyear,evenifelec-trificationinheatingandmobilityacceleratesandleadstoincreaseddemand.Inbothvillages,powergenerationfromsolarPVmodulesusuallyexceedspowerdemandduringtheday,whiledemandthatoccursbeforeoraftersunsetcannotbemetandrequirespowerfromothersources.Themisalignmentofsolarpowerabundanceduringthedayandpowerdemandbeforesunriseandaftersunsetcouldtosomeextentbecompensatedwithstorage,suchasforhotwaterproducedbyheatpumpsduringtheday,orbatterystorageforelectricity.However,atcurrentbatteryenergystorageprices,capturingallthesurpluspowerpro-ductionwouldbeuneconomical,eveniftechnicallyfeasi-ble.Ratherthanaimingforfullself-sufficiencyorislandgridoperation,amorebalancedapproachwouldtargetacom-binationofsteadilyincreasinglocalrenewableenergyout-put,graduallyupgradinglocalgrids,andincentivizingsmoothingpeakloadsviasmartadoptionofheatpumpsandEVsmartcharging.Suchanapproachoffersseveraladvantages.Villagescandrasticallycuttheirdependenceonpowerandfuelimportsingeneralandcanbenefitfromlowerpowerpricesatnightforthedemandtheycannotmeetwiththeirownresources.Thisfreesuphouseholdmeanspreviouslytiedupinenergyspendingforotherpur-posessuchaseducation,investment,ordomesticcon-sumption,thatarebeneficialforruraldevelopmentandstandardofliving–especiallydesirableinpoorerruralag-riculturalcommunitiesinChina.Byexportingtheirday-timerenewablepowersurplusestomoreenergy-hungryregions,likecitiesorindustryclusters,ruralareasinbothcountriescangenerateadditionalrevenuewandplayameaningfulroleintheentirecountry’senergytransition.Realisingthesepotentialstotheirfullestwillrequireaddi-tionaleffortsbothinGermanyandChina.InGermany,operatorsshouldadjustgridstoagrowingin-feedfrommanydistributedinstallationsandstrengthentheirabilitytofeedpowerintohigher-voltagegrids.Thisalsoincludesadvancingdigitalisationofinfrastructure,sothatanincreasinglydecentralandvariablepowersystemcanbemanagedflexiblyandrapidly.IncentivesforownersofdistributedPVshouldpromoteself-consumptionorfeed-induringtimesofpeakload.Incentivestructuresshouldpromotestoragebyreducingorfullyeliminatinganycostsforstoringsurpluspowerandenableownersofstoragetosellbalancingpowerasancillaryserviceintimesofhigh-powerdemand.Theanalysishereshowsthatve-hicle-to-gridcouldplayacertainroletocarryoversurpluspowerintotimeswithoutorwithlowPVpowergeneration.However,vehicle-to-gridrequiresarangeoftechnicalconditionsbothincarsandincharginginfrastructureandwillneedaclearandsupportivelegalandmarketframe-workifitistoestablishitself.Pilotprojectsandpoliticalinitiativescouldpromotethis.InChina,itisimportanttoexpandandadjustdistributiongridstoenablemorefeed-inofdistributedrenewableen-ergy.Gridoperatorsshouldcoordinatetheirplanningwithcommunitiesandjointlydeterminetheexpectedaddi-tionalrenewableenergycapacityintheplanningtimeframe.Ontheonehand,gridexpansionmustkeeppaceatacceptablecost;ontheotherhand,gridcapacitybottlenecksshouldnotimpedefurtherdistributedrenew-ableenergyexpansion.RuralcommunitiesinChinacouldreapsignificanteco-nomicbenefitsfromreducingtheirneedforpowerimportsandbecomingnetpowerexporters.However,duetothesignificantup-frontinvestmentcosts,adequateincen-tivesandmarketconditionsareimportant.Citizencoop-erativesmodelledonGermanexamplesareamodelthatChinacouldexploreinmoredepthandpromoteinlocalpi-lots.Electrificationofheatingviaheatpumpsisanimportantpartoftheruralenergytransitionandisparticularlyat-tractivewhencombinedwithself-producedsolarpowerandadegreeofheatstoragetoprovideheatingatnight.Duetothehigherup-frontcostsofheatpumps,financialsupportandtighterbuildingefficiencystandardswilllikelybenecessarytopromotethetechnology.Inmobility,villagerscouldallbuteliminatetheneedforfuelimportsiftheyadoptelectricvehiclesinvariousforms(two,three,four-wheeled),particularlyiftheychargevehiclesduringdaytimewhenplentyofsolarpowerisavailable.Lastly,ruralenergypotentialsareevenhigherwhenagri-voltaicsareconsidered.Nothavingbeenconsideredinthe52modellingwithinthisstudy,agrivoltaicscanprovideaddi-tionalrevenue,butwillrequiresuitableinvestmentandoperationincentivesandmustbewellcoordinatedwithgridoperatorsandland-useministries.Thisstudydemonstratestheenormouspotentialofruralareastocomplementcentralisedformsofenergyproduc-tionsuchaspowerplantsandlarge-scalerenewablein-stallations.ThisstudylargelyfocusedonthepotentialofrooftopPVinconjunctionwithheatpumpsandelectricve-hicles.Aspectsthatmeritfurtherexplorationandshouldbeaddedtothisframeworkinfutureresearchprojectsareagrivoltaics,distributedwindenergy,andamorecompre-hensiveanalysisofstorage,biomassandbiogaspotential.Theeconomicsofruralcleanenergytechnologyshouldalsobestudiedindetailviascenarioanalysis,takingintoaccountbothtechnologycostsaswellasvariousconsider-ationsrelatedtoupgradingdistributiongrids.53AnnexesOverviewoftheregionalisedscenariodataTechnologyScenarioYearCommunityOberdingVillageOberdingVillageNie-derdingVillageSchwaigEVTrend2030423894275203588118587157Optimistic2030550115549820351146240113204Pessimistic2030360753564203574915774134HeatPumpdena-EL9520309471999316920351211254119216dena-TM952030468984683203557312056102PVScenarioA203012,986kW3,940kW1,933kW1,862kW203515,712kW4,767kW2,338kW2,253kWScenarioB203013,806kW4,188kW2,055kW1,980kW203516,888kW5,123kW2,513kW2,422kWScenarioC203014,044kW4,260kW2,090kW2,014kW203517,244kW5,231kW2,566kW2,473kWOverviewofpopulationandhouseholdsizesinSchwaigHouseholdsizeCommunityOberdingVillageOberdingVillageNiederdingVillageSchwaigOverall2,1764562143881Person614129611102Persons613129601093Persons4188841754Persons3607535645Persons1302713236andmorepersons4494854BreakdownofannualelectricityconsumptioninGermanyfordifferenthouseholdsizes42HouseholdsizeAnnualelectricityconsumptioninkWhLowMediumHigh1Person1,3001,9002,5002Persons2,0002,7503,5003Persons2,5003,5004,5004Persons2,6003,8005,0005Persons3,0004,5506,1006andmorepersons5,8006,4507,100DistributionoftheheatdemandHouseholdheatdemandinMWhIndustryheatdemandinMWhCommunityOberding15,9706,069VillageOberding3,3481,272VillageNiederding15,7485,984VillageSchwaig2,8481,08255Householdsurveyquestionnaire(German)Source:WuppertalInstitute56References1“KyotoProtocolontheUnitedNationsFrameworkConventiononClimateChange,”originalpublishedinGerman“Proto-kollvonKyotozumRahmenübereinkommenderVereintenNationenüberKlimaänderungen,”FederalMinistryfortheEnvi-ronment,NatureConservation,NuclearSafetyandConsumerProtection,01April2022,athttps://www.bmuv.de/ge-setz/protokoll-von-kyoto-zum-rahmenuebereinkommen-der-vereinten-nationen-ueber-klimaaenderungen.2“2020climate&energypackage,”EuropeanCommission,accessedon10May2022athttps://ec.europa.eu/clima/eu-ac-tion/climate-strategies-targets/2020-climate-energy-package_en.3“FederalGovernmentdecidesphasingoutnuclearpowerby2022,”originalpublishedinGerman“Bundesregierungbes-chließtAusstiegausderKernkraftbis2022,”GermanFederalGovernment,19December2011,athttps://www.bundesregier-ung.de/breg-de/suche/bundesregierung-beschliesst-ausstieg-aus-der-kernkraft-bis-2022-457246.4“Finaldecisiontolaunchthecoal-phaseout–aprojectforageneration,”FederalMinistryforEconomicAffairsandCli-mateAction,03July2020,athttps://www.bmwk.de/Redaktion/EN/Pressemitteilungen/2020/20200703-final-decision-to-launch-the-coal-phase-out.html#:~:text=Said%20Federal%20Minister%20Altmaier%3A%20%E2%80%9CTo-day's,an%20entire%20generation%20to%20complete.5“DisposableIncome,”originalpublishedinGerman“VerfügbaresEinkommen,”BavarianStateMinistryforEconomy,StateDevelopmentandEnergy,October2021,athttps://www.landesentwicklung-bayern.de/daten-zur-raumbeobach-tung/wirtschaft/verfuegbares-einkommen/#prettyPhoto.6Shapedatasource:“GeodatenBayern”BayerischeVermessungsverwaltung,accessedon10May2022atwww.geo-daten.bayern.de;Landusedatasource:“OpenStreetMap,”OpenDatabase1.0License,www.openstreetmap.org;imagesource:BUW.7“Oberdingpopulationdata,”citypopulation.de,08January2022,athttps://www.citypopulation.de/en/germany/bay-ern/erding/09177133__oberding/.8“3000G-1009:Building:apartmentsinthebuilding,”2011Census,ZensusDatenbank,9May2011,athttps://ergebnisse2011.zensus2022.de/datenbank//online?operation=table&code=3000G-1009&bypass=true&levelin-dex=0&levelid=1652152506387#abreadcrumbe=GEBWG3&werteabruf=Werteabruf#abreadcrumb.9“CompanyLocations,”IHK-StandortportalBayern,accessedon10May2022athttps://standortportal.bayern/en/standort-suche/index.jsp#sortField=&start=1&q=Oberding&addr=&addrLabel=&f=geo_0_coordi-nate:[48.33247446606478+TO+48.34425616975366]&f=geo_1_coordi-nate:[11.8261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