计算机科学

计算机科学 ›› 2022, Vol. 49 ›› Issue (6A): 753-758.doi: 10.11896/jsjkx.210700225

• 交叉&应用 • 上一篇    下一篇

基于模糊双目标规划的充电站布局模型

阙华坤1, 冯小峰1, 郭文翀1, 李健1, 曾伟良2, 范竞敏2   

  1. 1 广东电网有限责任公司计量中心 广州 518049
    2 广东工业大学自动化学院 广州 510006
  • 出版日期:2022-06-10 发布日期:2022-06-08
  • 通讯作者: 曾伟良(weiliangzeng@gdut.edu.cn)
  • 作者简介:(quehuakun@126.com)
  • 基金资助:
    中国南方电网有限责任公司科技项目(GDKJXM20185800);国家自然科学基金(61803100)

Development of Electric Vehicle Charging Station Distribution Model Based on Fuzzy Bi-objective Programming

QUE Hua-kun1, FENG Xiao-feng1, GUO Wen-chong1, LI Jian1, ZENG Wei-liang2, FAN Jing-min2   

  1. 1 Metrology Center of Guangdong Power Grid Corporation,Guangzhou 518049,China
    2 School of Automation,Guangdong University of Technology,Guangzhou 510006,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:QUE Hua-kun,born in 1986,senior engineer.His main research interests include metering automation and charging strategy.
    ZENG Wei-liang,born in 1986,Ph.D,associate professor.His main research interests include routing problem in complex network,traffic simulation and big data visualization for smart city.
  • Supported by:
    Science and Technology Project of China Southern Power Grid Co. Ltd (GDKJXM20185800) and National Natural Science Foundation of China(61803100).

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摘要： 随着电动汽车的推广,公共充电站的数量难以满足日益增长的充电需求。充电站建设通常需要进行多周期、多等级的战略规划,同时受政策、经济环境等因素的影响。每个充电站各建设周期的充电需求量、各等级充电站的建设成本以及运营成本都存在很大的不确定性。在考虑充电站服务能力以及服务半径约束的情况下,构建了以全建设周期电动汽车用户充电满意度最大化、充电站总成本最小化为双目标的模糊规划模型,并设计基于自适应和反向搜索机制的多种群遗传算法求解该问题。案例分析对比了改进与标准遗传算法的结果,验证了改进算法及所提模型的有效性,并分析了不同置信水平和充电站服务半径对目标函数的影响。

关键词: 充电站布局, 电动汽车, 满意度, 模糊多目标规划

Abstract: With the popularization of electric vehicles,the number of public charging stations in cities cannot meet the growing demand for charging.Charging station construction usually requires multi-cycle and multi-level strategic planning,which is also affected by policies,economic environment and other factors.There are great uncertainties in the charging demand,the construction cost and operation cost in each charging station construction cycle.Considering the limited-service capacity of charging stations and the constraints of service radius,this paper develops a bi-objective fuzzy programming model that maximizes the charging satisfaction of electric vehicle users in the full cycle and minimizes the total cost of charging stations.Furthermore,a modified genetic algorithm based on adaptive and reverse search mechanisms is proposed to solve this problem.The results of the improved genetic algorithm and the standard genetic algorithm are compared in a case study.The performance of the model with different confidence levels and service radius of charging stations on the objective function are also verified.

Key words: Charging station distribution, Electric vehicle, Fuzzy bi-objective programming, Satisfaction

中图分类号: 

  • TP391
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