Anderson, John E.

Gils, Hans Christian

Hoyer-Klick, Carsten

Steck, Felix

van den Adel, Bent

Wulff, Niklas

Institute of Transport Research:Publications

Research question & setup Niklas Wulff1*, Felix Steck2, Hans Christian Gils1, Carsten Hoyer-Klick1, Bent van den Adel3, John Anderson2 Effects of EV fleet charging representation on power system flexibility provision How do user-oriented EV fleet charging decisions affect the flexibility of future EV fleets and what implications does this have on cost-optimal power system results? Results Profiles for user-oriented (blue and pink) and power system oriented (green) EV charging modeling 1 Department of Energy Systems Analysis, Institute of Engineering Thermodynamics, German Aerospace Center, Pfaffenwaldring 38-40, 70569 Stuttgart, Germany  Outlook • Detailed analysis of interplay between weather years and EV battery capacity available for load shifting • More insights into the role of dual variables  merit order of dual variable values  • Fast charging and reduced BEV fleet battery capacities in S1 reduce flexibility provision from 24 TWh to 8 TWh  • Curtailment (+31%) and gas power plants (+5% in capacity additions) compensate for lower flexibility • Gas turbine additions in S2 are twice as high in northern Germany due to the absence of inter-day flexibility  • Installed capacities are approximately at 214-224 GW in 2030 with 153-159 GW RES installations and t. 0501001502002501 3 5 7 9 11 13 15 17 19 21 23BEV-M fleet battery SOC CURRENT (TU) SOC max CURRENT (TU) SOC minCURRENT (SA) SOC max CURRENT (SA) SOC minVencoPy SOC max VencoPy SOC min0.00.51.01.52.02.53.03.54.01 3 5 7 9 11 13 15 17 19 21 23Electric demand for driving in GWh/h VencoPy CURRENT - Tuesday CURRENT - Saturday0.00.51.01.52.02.53.03.51 3 5 7 9 11 13 15 17 19 21 23Uncontrolled Charging in GWh/h 05101520251 3 5 7 9 11 13 15 17 19 21 23Fleet grid connection in GWh /h 100th percentile75th percentile50th percentile25th percentileUncontrolledcharging-500% -400% -300% -200% -100% 0% 100% 200% 300% 400% 500%Total system cost, base: -0.5 Bn. € Shifted load by German BEV fleets, base: +15.8 TWhRE capacity additions, base: +2.7 GWGas power plant capacity additions, base: -1.7 GWRES share in power generation, base: +1.1 %Annual RE curtailment, base: -0.8 TWhImports to Germany, base: -0.3 TWhExports from GER-N to GER-S, base: +2.9 TWhSensitivity of differences (S1x-S2x ) / (S1-S2) b GHG 80 MT c GHG 50 MTd GHG 0 MT e Data year 2006f Data year 2007 g Data year 2008h Data year 2009 i Data year 2010j Data year 2012 k CAPEX set1l CAPEX set2 m CC 30%SOC in GWh (different scales) Marginal value of equation in k€/GWh and k€/GW Marginal value of variable in k€/GWh and k€/GW Demand and supply of electricity in GW • Lower BEV fleet battery capacity available for load shifting significantly reduces charging variability • Higher daytime charging peak through public charging infrastructure, fast charging and a non-choice for charging at home • Accounting for differences between weekend and workday results in higher daytime peaks at the weekend (+40% in Northern and +12% in Southern Germany) 2 Department of Passenger Transport, Institute of Transport Research, German Aerospace Center, Rudower Chaussee 7, 12489 Berlin, Germany; felix.steck@dlr.de (F.S.); john.anderson@dlr.de (J.E.A.)  3 Department of Vehicle Systems and Technology Assessment, Institute of Vehicle Concepts, German Aerospace Center, Pfaffenwaldring 38-40, 70569 Stuttgart, Germany; bentvdadel@googlemail.com   *corresponding: niklas.wulff@dlr.de https://creativecommons.org/licenses/by-nc/4.0/legalcode This poster is based on a journal paper publication available as open access in the energies special issue on Model Coupling and Energy Systems:  https://www.mdpi.com/654148 Scenario definitions Results Scenario Annual electricity demand from BEV fleet in TWh Controllable share in % Total system costs in bn. € Shifted load by German BEV fleets in TWh Peak load in GW Fluctuating RES capacity additions in GW Gas power plant capacity additions in GW Annual fluctuating RES power generation in TWh VRE share in total power generation in % Annual VRE curtailment in TWh Imports to Germany in TWh Exports from northern G to southern G in TWh S0 0 - 68.4 0 83.9 46.2 31.3 279 55.7 2.9 45.9 64.7 S1a 27 0 71.7 0 91.1 49.0 39.0 284 54.1 3.6 50.3 62.9 S1 27 66 71.2 24.2 86.3 51.5 35.5 291 55.3 2.6 51.3 65.1 S2a 27 0 71.7 0 93.5 48.8 37.9 284 54.2 3.5 51.6 62.4 S2 27 30 71.7 8.4 87.6 48.8 37.2 284 54.2 3.4 51.6 62.2 – Minimum SOC constraint - SOC (optimization result) -- Maximum SOC constraint -  Battery level -  Maximum controlled charging   - Max battery level - Min battery level - Controlled charging   ■ Curtailment of wind power plants ■ Imports to Germany ■ RES electricity generation ■ Gas & coal electricity generation ■ Controlled charging of BEV fleet ■ Uncontrolled charging of BEV fleet 

Effects of EV fleet charging representation on power system flexibility provision

https://elib.dlr.de/135071/1/Wulff%20et%20al.%20UserBasedCharging_final.pdf

Effects of EV fleet charging representation on power system flexibility provision

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