Coordinated charging strategy of electric bus considering driving plan

被引：0
作者：
Cai Z. [1 ]
Shu H. [1 ]
Yang B. [1 ]
Shan J. [1 ]
机构：
[1] Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2021年 / 41卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Charging strategy; Coordinated charging; Driving plan; Electric bus; Time-of-use electricity price; Vehicle chain;
D O I：
10.16081/j.epae.202106022
中图分类号：
学科分类号：
摘要：
In order to improve the economy of electric bus and take into account the benefits of public transport and power grid, the charging strategy and driving plan of electric bus should be considered comprehensively. Firstly, feasible vehicle chains satisfying the constraints of time connection relationship and battery capacity are generated, and the coordinated charging stage 1 model of feasible vehicle chain with the minimum charging cost as its optimization objective and the optimal vehicle chain selection model with the minimum total operation cost as its optimization objective are established. Then, with the minimum fluctuation of charging load during the day and night as the optimization objective, the coordinated charging stage 2 model and the quadratic programming model of night charging for the feasible vehicle chain are established respectively. Finally, taking a bus line as the example to verify the proposed model, the results show that the proposed model and method can meet the demand of bus companies to make driving plans, achieve the goal of the lowest total operation cost of electric buses, and achieve the purpose of reducing charging cost and suppressing charging load fluctuation through coordinated charging, which has important reference value for guiding electric buses to make charging strategy and driving plan. © 2021, Electric Power Automation Equipment Press. All right reserved.
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页码：45 / 52
页数：7
相关论文
共 17 条
  • [1] LIU Wenxia, LONG Rishang, XU Xiaobo, Et al., Forecasting model of short-term EV charging load based on data freshness and cross entropy, Automation of Electric Power Systems, 40, 12, pp. 45-52, (2016)
  • [2] WANG Haolin, ZHANG Yongjun, MAO Haipeng, Charging load forecasting method based on instantaneous charging probability for electric vehicles, Electric Power Automation Equipment, 39, 3, pp. 207-213, (2019)
  • [3] SUN Qian, XU Shan, ZHU Shuyu, Et al., Distribution network planning considering DG timing characteristics and EV spatiotemporal characteristics, Electric Power Automation Equipment, 40, 10, pp. 30-38, (2020)
  • [4] WANG Yi, CHEN Jin, MA Xiu, Et al., Interactive scheduling strategy between electric vehicles and power grid based on group optimization, Electric Power Automation Equipment, 40, 5, pp. 77-85, (2020)
  • [5] GE Shaoyun, ZHU Linwei, LIU Hong, Et al., Optimal deployment of electric vehicle charging stations on the highway based on dynamic traffic simulation, Transactions of China Electrotechnical Society, 33, 13, pp. 2991-3001, (2018)
  • [6] MENG Xuyao, ZHANG Weige, BAO Yan, Et al., Optimal configuration of charging facility for electric vehicle fast charging station considering charging power, Electric Power Automation Equipment, 38, 7, pp. 28-34, (2018)
  • [7] YANG Jianwei, DONG Hongzhi, LIAO Kai, Et al., Joint optimization of load frequency control considering auxiliary frequency regulation of electric vehicles, Electric Power Automation Equipment, 39, 3, pp. 200-206, (2019)
  • [8] LI Bin, LIU Chang, CHEN Huimiao, Et al., Coordinated charging of plug-in electric buses in fast charging stations based on mixed-integer programming, Power System Technology, 40, 9, pp. 2623-2630, (2016)
  • [9] YANG Shaobing, WU Mingli, JIANG Jiuchun, Et al., Optimal stra-tegy for economic operation of electric bus battery swapping station, Power System Technology, 38, 2, pp. 335-340, (2014)
  • [10] YANG Jianwei, YANG He, ZHANG Xialin, Et al., A charging optimization strategy on charging and swapping station for electric buses based on optimization of switching rules and matching of buses and batteries, Proceedings of the CSEE, 39, 8, pp. 2337-2347, (2019)
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