Regionalization of the location-dependent charging demand of electric passenger cars at the grid square level using an agent-based mobility simulation

Abstract

The charging demand of electric passenger cars needs to be considered during the planning and operation of the electric power grid, especially at high penetration rates. It is not sufficient to simply quantify these additional loads, but rather time- and location-dependent modeling of these loads is required, so that grid operators can precisely predict the magnitude and location of the additional load. For this purpose, an agent-based modeling approach was developed that calculates, locates, and aggregates the charging demand of electric passenger cars per 100 m by 100 m grid squares in an observed area. The mobility of individual vehicles is simulated by efficiently finding destinations in the form of grid squares for generated trips using a k-d tree and parking space data. In a case study, the developed approach is applied to regionalize the charging demand of electric passenger cars at the transmission grid level within the federal state of Baden-Wuerttemberg, Germany. The resulting charging demand can be determined for each individual node of the transmission grid. The analysis shows that the developed approach can be used to quantify regional differences in charging demand and can therefore be used to improve grid planning and operation.