Temporal and Spatial Distribution Simulation of EV Charging Load Considering Charging Station Attractiveness

被引:0
|
作者
Cao F. [1 ]
Li S. [1 ]
Zhang Y. [1 ]
机构
[1] School of Electrical and Electronic Engineering, North China Electric Power University, Changping District, Beijing
来源
关键词
Charging load; Charging station attractiveness model; OD matrix; Temporal and spatial distribution; Traffic time-consuming index;
D O I
10.13335/j.1000-3673.pst.2020.0165
中图分类号
学科分类号
摘要
The charging load randomness of the temporal and spatial distribution of electric vehicles (EV) poses a challenge to the planning and operation of the power system. Aiming at this problem, a simulation method of the temporal and spatial distribution of EV charging load considering the charging station attractiveness and the traffic time-consuming index is proposed. Firstly, the charging station attractiveness model is constructed to describe the users' regularity of selecting the charging stations. Secondly, the traditional OD matrix is modified so that it can be used to describe the driving and distribution rules of the EVs. Thirdly, the concept of time-consuming index is proposed to quantify the driving time consumed. Then, the charging station attractiveness model will take full account of the various space-time factors. By simulating the EV state of charge and driving paths and combining the charging station attractiveness, the temporal and spatial distribution matrix of the charging load of a single EV is calculated, which is further extended to the EV groups with the Monte Carlo simulation. Finally, taking a typical urban area as an example, the charging load patterns of taxis and private EVs and the impact of the attraction of charging stations and the traffic situations on the charging loads are compared and analyzed, which verifies the correctness and effectiveness of the proposed model and method. © 2021, Power System Technology Press. All right reserved.
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页码:75 / 85
页数:10
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  • [1] Sun Qiang, Xu Fangyuan, Tang Jia, Et al., Study on modeling of aggregated charging load of electric vehicles and control strategy by adjusting capacity boundaries based on demand response, Power System Technology, 40, 9, pp. 2638-2645, (2016)
  • [2] Zhang Qian, Tang Fei, Liu Dichen, Et al., A static voltage stability assessment scheme of electric power systems considering charging state of plug-in electric vehicles and load fluctuation limits [J], Power System Technology, 41, 6, pp. 1888-1895, (2017)
  • [3] Hu Zechun, Song Yonghua, Xu Zhiwei, Et al., Impacts and utilization of electric vehicles integration into power systems, Proceedings of the CSEE, 32, 4, pp. 1-10, (2012)
  • [4] Figueiredo Antonio, Chen Lidan, Zhang Yao, Figueiredo Antonio, Overview of charging and discharging load forcasting for electric vehicles, Automation of Electric Power Systems, 43, 10, pp. 177-197, (2019)
  • [5] Chen Zhong, Duan Ran, Huang Xueliang, Et al., Collaborative planning of distribution network and EV charging stations considering active charging management, Electrical Measurement & Instrumentation, 56, 20, pp. 17-23, (2019)
  • [6] Peng Liu, Yu Jilai, Identification of charging behavior characteristic for large-scale heterogeneous electric vehicle fleet[J], Journal of Modern Power Systems and Clean Energy, 6, 3, pp. 567-581, (2018)
  • [7] Yu Haidong, Zhang Yan, Pan Aiqiang, Medium and long term evolution model of charging load for private electric vehicle, Automation of Electric Power Systems, 43, 21, pp. 80-93, (2019)
  • [8] Jia Long, Hu Zechun, Song Yonghua, An integrated planning of electric vehicle charging facilities for urban area considering different types of charging demands, Power System Technology, 40, 9, pp. 2579-2587, (2016)
  • [9] Hu Cheng, Liu Yujun, Xu Qingshan, Et al., Optimal scheduling strategy for electric vehicles in buildings with wind power, Power System Technology, 44, 2, pp. 564-572, (2020)
  • [10] Cao Fang, Li Sai, Zhang Yao, Optimization of floating charging service fee based on prospect theory to quantify charging utility[J], Electric Power Construction, 40, 9, pp. 107-115, (2019)