Infrastructure linking for placement of Charging stations using Monte Carlo simulation

Abstract

Germany plans to invest in the charging station's infrastructure to meet the 50,000 charging points by 2022. For a smooth transition from traditional to electrical vehicles, several electric vehicle charging stations must be planned. Rigorous placement of public charging stations may lead to stability problems in the power network grid. This can be avoided by intelligent Electric vehicle charging stations (EVCS) placement with consideration of traffic and grid planning. The stability problems associated with the electric vehicle charging due to high load may be solved by the expensive grid expansion. Another way to handle the situation is to place EVCS by planning algorithms to avoid the grid expansion for the coming years. In this paper, the authors present a new EVCS placement algorithm based on Monte Carlo simulation considering traffic model and grid modeling. The algorithm determines the optimal EVCS connection nodes taking into account different amounts/configurations of EVCS. Furthermore, the electric vehicles charging power of several EVCS has been scheduled optimally for the resulted configuration to reduce power losses. The input for the algorithm, the daily charge requirement, the amount of EVCS, and the number of electric vehicles has been determined by traffic modeling. The methodology has been implemented and tested in a low voltage network based on real data.