Volume 2: Innovative Solutions for Energy Transitions: Part I

Genetic Algorithm for Optimal Location of Electric Vehicle Charge Station Cheng Wang, JianWei Li, Peng He, Weiping Cui, Xin DaLi

Abstract

With increasing number of Electric Vehicles (EVs), more attention is being paid to EV’s charge stations. These stations play an essential role in EV industry chain. Choosing the optimal locations for these stations is becoming vitally important. Not only for power loss reduction, but also for power system security. In this paper a novel optimal charge station location method is informed based on active and reactive power flow analysis by using Genetic Algorithm (GA) in terms of power loss minimization. Results for the 36-bus Distribution Network (DN) are presented. It is demonstrated that installing three stations in optimal locations in the tested network, power loss reduces by 0.088 MW, compared with the situation with two stations.

Keywords charge stations’ location, EVs, active and reactive power flow analysis, GA optimisation, power loss reduction