欧洲电力部门需求灵活性的价值.pdf

Value of Demand Flexibility in the European Power SectorFinal Report03-10-2023This report explores different scenarios for the European power and district heating system each representing varying degrees of demand flexibility.The scenarios comply with the EUs objective of becoming climate neutral by 2050.When we compare the Reference scenario,which assumes frozen policy with regards to flexibility and minimal advancement in demand response(DR)technologies,with the Flex scenario,where regulatory changes,technological advancements,and heightened consumer awareness enabledemand response,we observe the following advantages:A socio-economicbenefitof 15.5 billion annually by the year 2050.A substantial reduction in consumer costs,amounting to approximately 26 billion annually by 2050.A decrease in averageconsumer power prices(wholesale)from 61/MWh to 55/MWh.The abatement of 40 million tons of CO2 in 2030.A reducedneed for approximately 300 GW of battery capacity and 90 GW less gas peak capacity.Additionally,an integration of 100 GW more solar capacity into the energy mix.Investments in interconnectors between bidding zones decreasedby 21%(61 GW)The modelling considers only benefits of demand response in whole-sale electricity markets including the need for investments in interconnectors between bidding zones.Any positive(or negative)effects of demand response on distribution grid cost and internal transmission grid cost are not considered in the modelling.Possible revenues from selling ancillary services are not considered either.These findings underscore the potential benefits associated with embracing demand response and fostering a flexible energy landscape.Please note that the costs related to realizing the potential for load-shift among certain consumers,including households,services,industries,andelectric vehicle(EV)owners,have not been factored into the analysis.Key findingsIntroduction4Project context5Danfoss is actively engaged in assessing the role of demand-side flexibility within the forthcoming European power system landscape.Against this backdrop,we have prepared a long-term analysis spanning the milestone years of 2025,2030,and 2050.The primary objective of this analysis is to quantify the holistic value that various forms of demand flexibility can contribute.Our evaluation hinges on a set of key metrics that encompass socioeconomic impact,monetary advantages for consumers,reductions in CO2 emissions and fuel consumption,and power prices.To gain a thorough understanding,these critical aspects will be investigated through the lens of three distinct scenarios,each representing varying degrees of demand flexibility.The analysis will be conducted by utilizing the Balmorel power system model to examine European day-ahead markets.This approach will focus on optimizing the intricate interplay between supply and demand dynamics,with the primary aim of minimizing costs for the overall system solution.Note,that the modelling considers only benefits of demand response in whole-sale electricity markets including the need for investments in interconnectors between bidding zones.Any positive(or negative)effects of demand response on distribution grid cost and internal transmission grid cost are not considered in the modelling.Possible revenues from selling ancillary services are not considered either.Balmorel is a fundamental partial-equilibrium model of the power and district heating system.The model finds least-cost solutions based on assumptions such as the development of fuel prices,demand development,technology costs and characteristics,renewable resources and other essential parameters.The model is capable of simultaneoussimultaneous investmentinvestment andand dispatchdispatch optimisationoptimisation,showing optimal solutions for powerpower generationgeneration andand interconnectorinterconnector capacity,capacity,dispatch,dispatch,transmissiontransmission flowflow andand electricityelectricity pricesprices.Prices are generated from system marginal costs,emulating optimal competitive bidding and clearing of the market.Model developed to support technical and technical and policy analysespolicy analyses of power systems.Optimization of economical dispatch and economical dispatch and capacity expansion capacity expansion solution solution for the represented energy system.Characteristics:Characteristics:open-source,customizable,scalable,transparentBalmorel energy system modelling toolModel dimensionsMain evaluation measuresMain evaluation measuresPower prices and market valuesGeneration&capacity balancesCO2 and pollutant emissionsSocio-economic system costsTemporal scopeTemporal scope Selected optimization years Time aggregated investment optimization Hourly dispatch optimizationGeographical scopeGeographical scope Nordics(bidding zones)Germany(4 regions)Baltics Central Europe,UK and Italy Iberian peninsulaNoteNote:Oval shapes in the North and Baltic seas represent existing&future offshore wind locations in an aggregated matter.Illustrated lines represent the options of transmission capacities.Nomenclature8AcronymAcronymTermTermAcronymAcronymTermTermCAPEXCapital costsInd.HIndividual HeatingCHPCombined Heat and PowerLDCLoad Duration CurveDHDistrict HeatingOPEXOperation expendituresDSRDemand Side ResponsePDCPrice Duration CurveEUEuropean UnionPtXPower to XEVsElectric VehiclesPVPhotovoltaicsFLHFull Load HoursTYNDPTen Year Development PlantH2HydrogenV2GVehicle to GridHSDCHyper Scale Data CentersVRESVariable Renewable Energy SourcesPower System Expectations2Electricity demand in Europe10The envisioned electrification of heating,industry and transport sectors is expected to increase electricity twofold towards 2030.The following sources are used for demand projections:REPowerEU for hydrogen production targets towards 2030.REPowerEU has been developed in the wake of Russias invasion of Ukraine and assumes 10 mill.ton domestic hydrogen production(330 TWh)in the EU already by 2030.The EU Commission MIX-scenario have been used for the long-term hydrogen demand.TYNDPs Global Ambition scenario for the development of total demand for classic demand,electric vehicles and individual heating.Electricity use for district heating is subject to model optimisation.01.0002.0003.0004.0005.0006.0007.000202520302050TWhTotal Electricity DemandElectricity consumption:Classic demandElectricity to district heatingElectricity consumption-HSDCsElectricity to individual heatingElectricity to industrial electrificationElectricity consumption:Electric VehiclesElectricity to P2XDemandDemandbucketbucket DescriptionDescriptionAssociatedAssociated costcost ofof flexibilityflexibilityClassicClassic electricity demand mainly for households,the industry and service sector.Contains demand types not explicitly covered under the other categories.EU 2021 mix(approx.):43%industry28%service26%households3%agricultureNo direct costs.The model includes an inertia which ensures that demand flexibility is only activated when there is a price difference of 15/MWh.ElectricvehiclesDemand includes all electricity for road transport.Initial profile is based on charging patterns matching transport demand(Estimated for individual countries based on empirical data from Norway)No direct costs.The model includes an inertia which ensures that demand flexibility is only activated when there is a price difference of 15/MWh.V2G activities face the occurring market costs(market clearing spot prices),essentially obtaining revenues from power arbitrage.No direct costs.The model includes an inertia which ensures that demand flexibility is only activated when there is a price difference of about 55/MWhIndividualheatingIncludes electricity consumption for space heating in buildings.The demand is supplied by heat pumps and electric boilers.No direct costs.The model includes an inertia which ensures that demand flexibility is only activated when there is a price difference of 10/MWh.DistrictheatingHeat demand for district heating is included.Heat pumps and electric boilers are among the options to supply the district heating demand.Other options are fuel-based district heating generation from heat only boilers or CHP.Depending on the scenario the model may invest in steel tanks and pit storagesInvestment and operational cost for additional electric boilers or heat pump capacity.Using alternative options for heat generation yields additional cost.Investment cost and operational costs of steel tanks and pit storages.Power-to-XDemand for production of e-gasses,e-liquids and hydrogen based on EU commission scenarios.Modelled as electricity consuming generation facilities(electrolysers).Depending on scenario model optimised hydrogen storages can be installed to enable flexible use of electrolysers,while demand is modelled constant.Investment and operational cost for electrolysers and cavern storages included.Demand buckets in the modelThe development in new capacity is driven by demand development,technology costs and resource assumptions.Moreover,important political targets are taken into account,including minimum buildout for renewable energy,coal phaseout plans and nuclear plans.WindWind andand solarsolar:As a minimum level for renewable energy,countries are expected to fulfil the levels of wind and solar power set out in ENTSO-E TYNDP-scenario National trends towards 2030.Key national are included as well,Germany for example,is expected to pursue higher targets for wind and solar power as set out in the Governments Easter Package from April 2022,aiming for 215 GW solar power and around 120 GW of onshore wind in 2030.Additionally,80%of the ambitious 30 GW offshore wind target by 2030 is assumed realised.Beyond 2030,investments are based on model optimisation.For onshore wind and solar PV,country specific caps are employed to reflect a realistic deployment that considers planning and grid constraints at the local level.These constraints are gradually relaxed over time.NuclearNuclear capacitycapacity is determined exogenously.The capacity based on plans from World Nuclear Association for decommissioning but with new plants being built in the UK,Finland and Poland.The total capacity declines from around 100 GW in 2021 to 90 GW in 2050.ThermalThermal capacitycapacity:Current plans for decommissioning of coal-fired capacity are considered.Other than that,decommissioning of and investments in thermal power capacity is determined by the model.Investment in biomass capacity(wood chips,wood pellets,straw)is constrained at 30 GW by 2030(corresponding to a fuel input of approx.1.900 PJ)to reflect that the current pipeline of new biomass capacity is limited.Towards 2050,the biomass constraint is lifted to 40 GW.Generation capacity in Europe12Buildout requirements and levels in the model areaBuildout requirements and levels in the model area05001.0001.5002.0002.50020252030203520402050GWMin onshoreOnshore capMax onshoreMin offshoreOffshore capMax offshoreMin solarSolar capMax solarNoteNote:oMin and max show assumptions on minimum and maximum possible buildout pathways.oNo difference between the two means,means that a exact capacity is installed.o“Cap”shows capacity as a result of model optimisation.oSpain and Portugal are not included in the present graph.FuelFuel pricespricesFutures(April 2023).Until and including 2026Long term.Prices expected to converge to long term equilibrium prices in 2030IEA World Energy Outlook 2022 Announced Pledges scenarioNatural gas:LNG import price(Japan).Current high gas prices expected to normalise over time,but outlooks are difficult in current situation.Towards 2030,reduced dependence on natural gas and high global buildout of renewables lowers demand for fossil fuels and thus pricesCOCO2 2-pricespricesForward prices(April 2023).Until and including 2026Long term.Prices expected to converge to Announced Pledges scenario from WEO2022 in 2030 and onwards.High CO2-prices also going forward to 2030.However,current prices are also to some extent affected by high gas prices.Fuel and CO2 prices13050100150200250ETS price(EUR22/ton)ETS priceETS price0102030405060EUR22/GJFuel pricesFuel pricesCoalLightoilNatural gasWood chipsWood pelletsStudy structure14Analysed scenarios15Ea Energy Analyses reference projection towards 2050 will be utilised as a basis for the present study,with key flexibility aspects varying across three scenarios.I.A“Reference”scenario reflecting frozen policy and limited development of DR technologies.The reference displays relatively low levels of flexibility,including inflexible electricity consumption patterns among a certain portion of the PtX capacity.II.The PtX sector is expected to provide the highest level of flexibility in the system in upcoming years,due to its demand magnitude but also characteristics.Therefore,an intermediate scenario(“PtX Flex”)will be analysed to shed light on the value that PtX related flexibility brings to the system on top of reference case.III.Finally,the most flexible scenario(“Flex”),will reflect the addition of further demand-side flexibility actions in each demand category,showcasing the overall emerged value from the deployment of different flexibility measures.An overview of the varying aspects between scenarios can be seen in the following slide:Definition of scenarios16DemandDemandbucketbucketReferenceReferenceReferenceReference +PtXPtX flexibilityflexibility (“PtX(“PtX Flex”)Flex”)FlexibilityFlexibility scenarioscenario (“Flex”)(“Flex”)Classic2,5%fuel-shift(permanent reduction in demand)5%load-shift(up to 2 hours).25%realised in 2025,50%in 2030,100%by 2050.As Reference10%fuel-shift(permanent reduction in demand)20%load-shift(up to 2 hours).25%realised in 2025,50%in 2030,100%by 2050.Electricvehicles20%of total load for electric road transport will participate in flexible charging and be able to move planned charging by up to 4 hours.15%of total load V2G“fit”.25%realised in 2025,50%in 2030,100%by 2050.As Reference65%of total load for electric road transport will participate in flexible charging and be able to move planned charging by up to 4 hours.50%of total load V2G“fit”.25%realised in 2025,50%in 2030,100%by 2050.IndividualheatingFixed consumption pattern.As ReferenceFlexible heat generation by adjustments to initial demand profile.Average demand can be moved 3 hours.25%realised in 2025,50%in 2030,100%by 2050.Districtheating utilitiesFlexibility consistsof the option to fulfilthe heat demand by electricity or other heat generation,dependingon the power prices.The model may invest in steel tanks only.As ReferenceAs Reference plus:The model may invest in steel tanks and pit storages.Load-shift among district heating consumers:2025:4 hours flex,25%realised2030:5 hours flex,50%realised2050:6 hours flex,75%realisedPower-to-X75%of PtX demand operates flexible25%of PtX demand follows a fixed load curve(flat throughout the year).100%flexible PtX load.Model optimised hydrogen storages can be installed to enable flexible