Optimization of charging infrastructure usage under varying traffic and capacity conditions

Abstract

In the future energy landscape, high attention will be paid to the intelligent management of the balance between generation and demand. The shift of transportation towards electrification is a crucial part of the future efforts, but also a great challenge regarding the alignment with renewable energy supply. In this paper, we investigate the EV charging capacity management, with a focus on sustainable electric vehicle (EV) charging capacity for long-distance traffic on highways. The proposed method is based upon the concept of an Intelligent Dynamic Charging Assignment which takes various parameters of traffic information, user information and charging facility information into account in order to optimize charging facility usage by increasing its utilization and maximizing the energy usage, enable higher EV throughput in given traffic conditions and comply with user preferences and EV car characteristics. The optimization results have been validated in a simulation environment with different parameter variations. With the dynamic assignment, an increase of 30% of the utilization of the infrastructure with equal charging station deployment at each location can be reached. This is also reflected in an increase of the throughput of the EVs which is limited by waiting times. The given studies show a 30% higher throughput efficiency through the proposed dynamic assignment method. A reshuffling of the charging infrastructure is also considered. While the energy utilization itself increases to a small extend, the improvement on user experience regarding waiting times has a greater impact towards user satisfaction.