Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 753-758.doi: 10.11896/jsjkx.210700225

• Interdiscipline & Application • Previous Articles     Next Articles

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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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

CLC Number: 

  • TP391
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