Modeling Probabilistic Driving and Charging Profiles of Commercial Electric Vehicles

Abstract

The electrification of road transport requires a massive integration of charging infrastructure into the electrical distribution grids. In order to investigate their impact on the grid expansion demand or to develop optimization methods for charging management, it is necessary to model the uncertainties of the driving and charging behavior of electric vehicles in the form of probabilistic time series but also as a simultaneity factor. Most scientific papers focus on modeling privately owned electric vehicles. However, the influence of commercial electric vehicles has hardly been considered so far, even though high electric loads are to be expected here as well in the future. In this paper we present our method for modeling the driving and charging behavior of commercially owned electric passenger cars and light commercial vehicles. In our evaluation, we show the plausibility for a fleet of 5000 vehicles in terms of average annual mileage, weekday-dependent trips, and seasonal energy demand, among others. Finally, we determine the maximum simultaneity of the charging power.