Electric vehicle fast charging with energy storage and generation capabilities - Simulations based on real charging data

Abstract

The increasing use of electric vehicles (EV) brings up the need to invest in the charg- ing infrastructure and extend the number of charging sites and stations. Especially the integration of fast charging sites increases the convenience for the user. The growing utilization of charging sites is also a chance to learn about charging be- haviour and future needs. In this thesis, usage data of a charging site in Norway is processed by a self-developed modelling tool, to create charging profiles based on the measured energy data. Additionally an optimized peak-shaving approach is examined. The capabilities and influence of an integrated battery electric storage (BES) system and a photovoltaic (PV) system on the charging profiles are anal- ysed. The peak-shaving reaches values between 30% and 60% depending on the BES and PV configuration. Based on the results, differences and patterns in the charging behaviour are visible on a weekly and monthly basis. The results of the peak-shaving indicate a correlation of higher peak-shaving with a increasing BES capacity. The PV system introduces more flexibility to the charging site that implies more independence of the grid.