Method to synthesis energy demand time series and identify charging demand of electric vehicles

The transition to electric vehicles poses challenges for power system planning, particularly in distribution grids. This paper introduces a novel method for simulating electric vehicle driving trips at scale to model realistic driving behaviours. By incorporating empirical mobility patterns into the simulation environment, the approach enables detailed analysis of temporal and spatial charging demand. Integration with the SIMONA framework facilitates co-simulation with the electric power system, allowing power flow calculations and load management strategies. Validation against real-world data demonstrates high accuracy in predicting parking duration across various states while identifying deviations affecting energy consumption profiles. An exemplary scenario highlights significant grid impacts from electric vehicle charging infrastructure. The presented open-source MobilitySimulator supports forecasting charging demands, optimizing grid investments, and evaluating smart charging strategies to mitigate negative grid effects and enhance renewable integration. This scalable methodology advances research on grid interactions with electric vehicles and sustainable power systems planning.