Title: Multi-objective optimisation method of electric vehicle charging station based on non-dominated sorting genetic algorithm

Authors: Jia Liu; Jin Huang; Jinzhi Hu

Addresses: Department of Mechanical Engineering, Taiyuan Institute of Technology, Taiyuan, Shanxi, China ' Department of Mechanical Engineering, Taiyuan Institute of Technology, Taiyuan, Shanxi, China ' Department of Mechanical Engineering, Taiyuan Institute of Technology, Taiyuan, Shanxi, China

Abstract: There are some problems in the existing objective optimisation planning methods of electric vehicle charging station, such as low accuracy and long optimisation time. By calculating the input cost, combined closure flow and minimum node voltage of the charging station through the objective function, the optimisation objective was determined. According to the determined optimisation objective, the multi-objective comprehensive planning model of the electric vehicle charging station is constructed. After the initial solution setting, coding, decoding and other iterative operations, the multi-objective comprehensive planning model of the electric vehicle charging station is solved and the optimisation result is obtained. The multi-objective optimisation of electric vehicle charging station is realised. The results show that the highest accuracy is about 95%.

Keywords: non-dominated sorting genetic algorithm; electric vehicle charging station; multi-objective optimisation; decoding.

DOI: 10.1504/IJGEI.2022.10049435

International Journal of Global Energy Issues, 2022 Vol.44 No.5/6, pp.413 - 426

Received: 05 Feb 2021
Accepted: 13 May 2021

Published online: 08 Sep 2022 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article