Comparing Power-System and User-Oriented Battery Electric Vehicle Charging Representation and Its Implications on Energy System Modeling

Energies

Niklas Wulff¹  HansChristian Gils¹  Carsten Hoyer-Klick¹  Felix Steck²  JohnE. Anderson²  Bent van den Adel³ 

[1] Department of Energy Systems Analysis, Institute of Engineering Thermodynamics, German Aerospace Center, Pfaffenwaldring 38-40, 70569 Stuttgart, Germany;Department of Passenger Transport, Institute of Transport Research, German Aerospace Center, Rudower Chaussee 7, 12489 Berlin, Germany;Department of Vehicle Systems and Technology Assessment, Institute of Vehicle Concepts, German Aerospace Center, Pfaffenwaldring 38-40, 70569 Stuttgart, Germany;

关键词: electric vehicles;    sector coupling;    energy system optimization;    renewable energy integration;    remix;    charging behavior;    marginal values;   

DOI  :  10.3390/en13051093

来源: DOAJ

【 摘 要 】

Battery electric vehicles (BEV) provide an opportunity to balance supply and demand in future power systems with high shares of fluctuating renewable energy. Compared to other storage systems such as pumped-storage hydroelectricity, electric vehicle energy demand is highly dependent on charging and connection choices of vehicle users. We present a model framework of a utility-based stock and flow model, a utility-based microsimulation of charging decisions, and an energy system model including respective interfaces to assess how the representation of battery electric vehicle charging affects energy system optimization results. We then apply the framework to a scenario study for controlled charging of nine million electric vehicles in Germany in 2030. Assuming a respective fleet power demand of 27 TWh, we analyze the difference between power-system-based and vehicle user-based charging decisions in two respective scenarios. Our results show that taking into account vehicle users’ charging and connection decisions significantly decreases the load shifting potential of controlled charging. The analysis of marginal values of equations and variables of the optimization problem yields valuable insights on the importance of specific constraints and optimization variables. Assumptions on fleet battery availability and a detailed representation of fast charging are found to have a strong impact on wind curtailment, renewable energy feed-in, and required gas power plant flexibility. A representation of fleet connection to the grid in high temporal detail is less important. Peak load can be reduced by 5% and 3% in both scenarios, respectively. Shifted load is robust across sensitivity analyses while other model results such as curtailment are more sensitive to factors such as underlying data years. Analyzing the importance of increased BEV fleet battery availability for power systems with different weather and electricity demand characteristics should be further scrutinized.

【 授权许可】

Unknown