A Spatio-Temporal Microsimulation Framework for Charging Impact Analysis of Electric Vehicles in Residential Areas: Sensitivity Analysis and Benefits of Model Complexity

Stefan Schmalzl, Michael Frey () and Frank Gauterin
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Stefan Schmalzl: Institute of Vehicle System Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany
Michael Frey: Institute of Vehicle System Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany
Frank Gauterin: Institute of Vehicle System Technology, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany

Energies, 2025, vol. 18, issue 13, 1-30

Abstract: The increasing share of electric vehicles (EVs) offers many advantages, including a reduced CO 2 footprint over the vehicles’ lifetime and improved resource efficiency through the recycling of high-voltage batteries. At the same time, the growing EV share presents challenges, such as ensuring sufficient power supply for the simultaneous charging of EVs within existing distribution grids. The scientific community has conducted numerous studies on the interaction between EVs and distribution grids, employing increasingly complex modeling techniques. However, the benefits of more complex modeling are rarely quantified. This study aims to address this gap by evaluating the impact of modeling complexity on transformer peak loads and busbar voltage for three communities with real-world distribution grid data. Since numerous stochastic factors influence EV charging patterns, this paper introduces a modular framework that accounts for the interconnection of these factors through microsimulation. The framework models charging events of battery electric vehicles (BEVs) and comprises modules for synthetic population generation, weekly mobility pattern assignment, and energy demand modeling based on vehicle class and ambient conditions. The findings reveal that cost-optimized charging strategies and seasonal factors, such as cold weather, have a significantly greater impact on the distribution grid than the detailed modeling of sociodemographic mobility patterns or detailed modeling of a diversified vehicle fleet.

Keywords: microsimulation; electric vehicle charging; Battery Electric Vehicle; sensitivity analysis; charging behavior; charging strategy; cost optimized charging; transformer; voltage; synthetic population; distribution grid; electric vehicle charging impact; model complexity; cold weather (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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