Journal of Lanzhou University of Technology ›› 2022, Vol. 48 ›› Issue (6): 81-87.

• Automation Technique and Computer Technology • Previous Articles     Next Articles

Study on strategy of electric vehicle charging power allocation based on fair weight

MAO Yun-juan1, ZHU Yue-yang2, LI Heng-jie2,3, ZHOU Yun3, XIA Qiang-qiang2   

  1. 1. Shanxi Vocational and Technology College of Electric Power, Taiyuan 030021, China;
    2. School of Electrical Engineering and Information Engineering, Lanzhou Univ. ofTech., Lanzhou 730050, China;
    3. Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Shanghai Jiaotong University, Shanghai 200240, China
  • Received:2021-06-29 Online:2022-12-28 Published:2023-03-21

Abstract: In order to meet the diverse charging needs of large-scale electric vehicle users, a charging power allocation strategy for electric vehicles based on fair weight is proposed. Firstly, the priority penalty mechanism is added to the M/M/C/N queuing model to preliminarily optimize the user waiting time and charging power. Secondly, aiming at the problem of user satisfaction during charging, a user satisfaction function based on penalty factor is proposed. Finally, using the optimized entropy weight method, on the premise of meeting the needs of users, the charging fairness factor between users is involved in the power distribution in the form of weight to realize the fair distribution of available loads in the area, and the user satisfaction function is used to evaluate the power distribution method. The simulation results show that the adding of the charging mode distribution algorithm and the power distribution strategy based on fair weight can further optimize the waiting time and charging power of the users. The proposed user satisfaction function can also effectively evaluate the user’s attitude towards the charging stations, which is helpful to improve the service of each charging station and further optimize the user experience.

Key words: electric vehicle charging, power allocation strategy, service mechanism, user satisfaction

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