Computer Engineering and Applications ›› 2023, Vol. 59 ›› Issue (21): 52-65.DOI: 10.3778/j.issn.1002-8331.2302-0021

• Research Hotspots and Reviews • Previous Articles     Next Articles

Review of Intelligent Decision Optimization of Electric Vehicle Charging Stations Location

WEI Guanyuan, WANG Guanqun, RUAN Guanmei, GENG Na   

  1. 1.State Grid Energy Research Institute Co., Ltd., Beijing 102209, China
    2.Sino-US Global Logistics Institute, Shanghai Jiao Tong University, Shanghai 200030, China
  • Online:2023-11-01 Published:2023-11-01

电动汽车充电站选址智能决策与优化研究综述

魏冠元,王冠群,阮观梅,耿娜   

  1. 1.国网能源研究院有限公司,北京 102209
    2.上海交通大学 中美物流研究院,上海 200030

Abstract: A reasonable location of electric vehicle(EV) charging stations plays an important role in promoting the development of EV industry and the strategic layout of urban transportation. The relevant literature of intelligent decision optimization of charging station location is systematically reviewed to provide reference for future planning of charging station. The basic principles and influencing factors of EV charging station location are elaborated. Methods of charging demand estimation based on EV trip simulation and data analysis are summarized. The location model of EV charging station based on point demand, origin-destination pair flow demand, and EV trajectory are introduced. The exact algorithm and heuristic algorithm and deep learning algorithm for solving the EV charging station location model are summarized. Finally, limitations of existing studies are discussed, and future research focuses and directions are prospected.

Key words: electric vehicle, charging station location, intelligent decision, literature review, charging demand

摘要: 电动汽车(electric vehicle,EV)充电站的合理选址对推动EV行业发展以及城市交通战略布局具有重要作用。通过系统梳理充电站选址智能决策和优化的相关文献,为未来充电站选址规划提供参考和借鉴。阐述了EV充电站选址基本原则和影响因素;归纳了基于EV出行模拟和数据分析的充电需求估计方法;分别介绍了基于点需求、基于起讫点对的流量需求、EV轨迹等方面的EV充电站选址模型;总结了求解EV充电站选址模型的精确算法、启发式算法和深度学习算法;对现有研究进行总结,指出存在的不足并对未来研究方向进行展望。

关键词: 电动汽车, 充电站选址, 智能决策, 研究综述, 充电需求