An optimal charging and Vehicle-to-Grid management system for the integration of EVs into low voltage distribution networks

The increasing adoption of electric vehicles (EVs) brings about the need for effective integration into energy distribution networks. However, this integration poses challenges such as increased demand for electricity, grid congestion, and power quality issues. To address these challenges, this paper presents a distributed EVs’ energy management system for low-voltage energy distribution networks. The system leverages multi-agent systems (MAS) and fuzzy cognitive maps (FCMs) to manage EV charging and power supply using vehicle-to-grid (V2G) technology. The objectives of the system that are examined is the minimization of the cost burden on EV owners caused by battery degradation from V2G usage and the minimization of EVs charging time. By optimizing the weights of the energy management system, by using the Fuzzy - particle swarm optimization (PSO) algorithm, the proposed approach aims to achieve these objectives. The system’s significance lies in cost reduction, battery life preservation, efficient charging, and grid congestion management. The IEEE European Low Voltage test feeder is enabled in order to evaluate the proposed energy management system. The results showed that V2G technology in combination with energy management systems can be a promising solution for distribution system operators (DSOs).