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Capacity configuration of fast charging stations based on EV path simulation under dynamic model of transportation network

被引：0
|
作者：
Cao F. [1 ]
Hu J. [1 ]
Luo J. [1 ]
Zheng J. [1 ]
机构：
[1] School of Electrical and Electronic Engineering, North China Electric Power University, Beijing
来源：
Dianli Zidonghua Shebei/Electric Power Automation Equipment | 2022年 / 42卷 / 10期
关键词：
capacity configuration; charging demand; Dijkstra algorithm; dynamic congestion model; electric vehicles; fast charging stations; path simulation; transportation network;
D O I：
10.16081/j.epae.202205003
中图分类号：
学科分类号：
摘要：
With the development of rapid charging technology，fast charging method is favored by more and more electric taxi drivers. So，scientific planning of fast charging stations is needed to meet the growing demand for fast charging. Therefore，a capacity configuration model of fast charging stations based on EV （Electric Vehicle） path simulation results under the dynamic model of transportation network is proposed. The dynamic congestion model of transportation network is established according to the characteristics of transportation network congestion changing with time. An EV path simulation method based on the dynamic congestion model of transportation network is proposed，which is improved on the basis of Dijkstra algorithm to simulate the EV travel path with the goal of minimizing time consumption. Considering the relationship between the charging demand of electric taxis and the driving demand of passengers，the judgment method of electric taxis’charging demand is proposed，and combined with the path selection method aiming at the least time consumption，the fast charging stations are selected for electric taxis. On the premise of satisfying the operation constraints of distribution network，the capacity configuration model of fast charging stations is established with the objective function of the maximum comprehensive benefit including fast charging stations’income and EV users’income，and is solved by the particle swarm optimization algorithm. Taking the transportation network in a city as an example，the driving and charging behaviors of EVs are simulated to verify the correctness and effectiveness of the proposed model and method. © 2022 Electric Power Automation Equipment Press. All rights reserved.
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页码：107 / 115
页数：8
相关论文
共 21 条
  • [1] YU Dongmin, YANG Chao, JIANG Linru, Et al., Review on safety protection of electric vehicle charging［J］, Proceedings of the CSEE, 42, 6, pp. 2145-2164, (2022)
  • [2] Qiang YANG, Siyang SUN, Shuiguang DENG, Et al., Optimal sizing of PEV fast charging stations with Markovian demand characterization［J］, IEEE Transactions on Smart Grid, 10, 4, pp. 4457-4466, (2019)
  • [3] YANG Hongming, LI Ming, WEN Fushuan, Et al., Route selection and charging navigation strategy for electric vehicles employing real-time traffic information perception［J］, Automation of Electric Power Systems, 41, 11, pp. 106-113, (2017)
  • [4] ZHANG H C, Et al., PEV fast-charging station siting and sizing on coupled transportation and power networks［J］, IEEE Transactions on Smart Grid, 9, 4, pp. 2595-2605, (2018)
  • [5] ZANG Haixiang, FU Yuting, CHEN Ming, Et al., Dynamic planning of EV charging stations based on improved adaptive genetic algorithm［J］, Electric Power Automation Equipment, 40, 1, pp. 163-170, (2020)
  • [6] CHEN Lixing, HUANG Xueliang, Ordered charging strategy of electric vehicles at charging station on highway［J］, Electric Power Automation Equipment, 39, 1, pp. 112-117, (2019)
  • [7] MENG Xuyao, ZHANG Weige, BAO Yan, Et al., Optimal configuration of charging facility for electric vehicle fast charging station considering charging power［J］, Electric Power Automation Equipment, 38, 7, pp. 28-34, (2018)
  • [8] JIANG Xin, FENG Yongtao, XIONG Hu, Et al., Electric vehicle charging station planning based on travel probability matrix ［J］, Transactions of China Electrotechnical Society, 43, pp. 272-281, (2019)
  • [9] CAO Fang, Sai LI, ZHANG Yao, Temporal and spatial distribution simulation of EV charging load considering charging station attractiveness［J］, Power System Technology, 45, 1, pp. 75-87, (2021)
  • [10] ZHAO Shuqiang, ZHOU Jingren, LI Zhiwei, Et al., EV charging demand analysis based on trip chain theory［J］, Electric Power Automation Equipment, 37, 8, pp. 105-112, (2017)
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