Siting and Sizing Method of Electric Vehicle Charging Station Based on Improved Immune Clonal Selection Algorithm

被引：0
|
作者：
Wu Y. [1 ]
Wang Y. [1 ]
Zhang Y. [1 ,2 ]
Xue H. [1 ]
Mi Y. [1 ]
机构：
[1] College of Electric Power Engineering, Shanghai University of Electric Power, Shanghai
[2] State Grid Shanghai Electric Power Research Institute, Shanghai
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2021年 / 45卷 / 07期
基金：
中国国家自然科学基金;
关键词：
Affinity between antibodies; Electric vehicle; Immune clonal selection algorithm (ICSA); Service range; Siting and sizing;
D O I：
10.7500/AEPS20200812003
中图分类号：
学科分类号：
摘要：
With the increasing penetration of electric vehicles, charging infrastructure planning should be more scientific and rational. A siting and sizing method of electric vehicle charging station based on the improved immune clonal selection algorithm (ICSA) is proposed. Firstly, the relationship between the capacity, location and service range of the charging station is analyzed. Taking the coverage and coincidence of the charging station, the power in the planned region, and the charging power of the charging station as constraints, a siting and sizing model of the charging station with the goal of minimizing the total annual cost of the charging station is established. Then, a method for calculating the affinity between antibodies and the polynomial mutation are proposed to improve the ICSA, making it more suitable for the iterative solution of the siting and sizing model for the electric vehicle charging station. Finally, example analysis is made in MATLAB, and the results verify the effectiveness of the model and the algorithm. © 2021 Automation of Electric Power Systems Press.
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页码：95 / 103
页数：8
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共 28 条
  • [1] UCER E, KOYUNCU I, KISACIKOGLU M C, Et al., Modeling and analysis of a fast charging station and evaluation of service quality for electric vehicles, IEEE Transactions on Transportation Electrification, 5, 1, pp. 215-225, (2019)
  • [2] SU Su, YANG Tiantian, LI Yujing, Et al., Charging route planning for electric vehicles considering real-time dynamic energy consumption, Automation of Electric Power Systems, 43, 7, pp. 136-143, (2019)
  • [3] EL-TAWEEL N A, KHANI H, FARAG H E Z., Analytical size estimation methodologies for electrified transportation fueling infrastructures using public-domain market data, IEEE Transactions on Transportation Electrification, 5, 3, pp. 840-851, (2019)
  • [4] LONG Xuemei, YANG Jun, WU Fuzhang, Et al., Prediction of electric vehicle charging load considering interaction between road network and power grid and user's psychology, Automation of Electric Power Systems, 44, 14, pp. 86-93, (2020)
  • [5] LIU J P, ZHANG T X, ZHU J, Et al., Allocation optimization of electric vehicle charging station (EVCS) considering with charging satisfaction and distributed renewables integration, Energy, 164, pp. 560-574, (2018)
  • [6] RABIEE A, GHIASIAN A, CHERMAHINI M A., Long term profit maximization strategy for charging scheduling of electric vehicle charging station, IET Generation, Transmission & Distribution, 12, 18, pp. 4134-4141, (2018)
  • [7] SIMORGH H, DOAGOU-MOJARRAD H, RAZMI H, Et al., Cost-based optimal siting and sizing of electric vehicle charging stations considering demand response programmers, IET Generation, Transmission & Distribution, 12, 8, pp. 1712-1720, (2018)
  • [8] XU Qingshan, CAI Tingting, LIU Yujun, Et al., Location planning of charging stations for electric vehicles based on drivers' behaviors and travel chain, Automation of Electric Power Systems, 40, 4, pp. 59-65, (2016)
  • [9] FU Fengjie, FANG Yaxiu, DONG Hongzhao, Et al., Optimized allocation of charging stations for electric vehicles based on historical trajectories, Automation of Electric Power Systems, 42, 12, pp. 72-80, (2018)
  • [10] ISLAM M M, SHAREEF H, MOHAMED A., Optimal location and sizing of fast charging stations for electric vehicles by incorporating traffic and power networks, IET Intelligent Transport Systems, 12, 8, pp. 947-957, (2018)
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