Impact of shifting electric passenger car charging to public infrastructure on aggregated load profiles

The preferences of electric passenger car drivers need to be taken into account when modelling the charging demand using an agent-based simulation. Drivers today are assumed to prefer charging at home due to lower costs compared to public charging. In the future, drivers may be able to take their home charging rates to public charging infrastructure, leading to a shift in their preferences and therefore charging behaviour. This potential shift from private to public charging needs to be modelled and the effects analysed. This paper presents an improvement to a previously developed bottom-up approach for the modelling of the charging demand of electric passenger cars by introducing different driver types with individual preferences as well as charging infrastructure operator types, which allows for a more realistic simulation of charging behaviour. A case study examines the effects on the aggregated charging load in Baden-Wuerttemberg. Results show that there is a visible shift of the total charging load during the day, which may lead to a better integration of renewable energies and a reduced evening load peak. The presen ted method allows for grid operators to take this anticipated shift into account when forecasting load in the context of grid planning.