Location of electric vehicle charging stations based on INSGA2

Ye Chang; Wei Xiao; Chunlei Ji; Lin Liu; Yuanfeng Hao

doi:10.1117/12.2627002

14 February 2022 Location of electric vehicle charging stations based on INSGA2

Ye Chang, Wei Xiao, Chunlei Ji, Lin Liu, Yuanfeng Hao

Proceedings Volume 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021); 121611F (2022) https://doi.org/10.1117/12.2627002
Event: 4th International Conference on Informatics Engineering and Information Science, 2021, Tianjin, China

Abstract

The location of electric vehicle charging stations is a hot issue in the development of electric vehicles (EVs). How to determine the locations and scales of EV charging stations are the main research problems. For this purpose, an improved Non-dominated Sorting Genetic Algorithm II(NSGA2) based on double-layer coding is proposed, which is named INSGA2. The INSGA2 adopts a multi-objective optimization for the locations of EV charging stations. Taking the comprehensive cost of charging stations and users as the two objective functions, and the service scope and scale of charging stations as the constraints, a multi-objective optimization model is established. The results reveal that it has better effectiveness and practicable in solving the locations and scales of the EV charging stations.

Citation Download Citation

Ye Chang, Wei Xiao, Chunlei Ji, Lin Liu, and Yuanfeng Hao "Location of electric vehicle charging stations based on INSGA2", Proc. SPIE 12161, 4th International Conference on Informatics Engineering & Information Science (ICIEIS2021), 121611F (14 February 2022); https://doi.org/10.1117/12.2627002

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