Electric Vehicle Charging Station Planning Based on Travel Probability Matrix

被引：4
|
作者：
Jiang X. [1 ]
Feng Y. [1 ]
Xiong H. [2 ]
Wang J. [1 ]
Zeng Q. [1 ]
机构：
[1] School of Electrical Engineering, Zhengzhou University, Zhengzhou
[2] State Grid Hubei Electric Power Research Institute, Wuhan
来源：
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2019年 / 34卷
关键词：
Electric vehicle charging station planning; Queuing theory; Spatial-temporal distribution; Travel probability matrix; Voronoi diagram;
D O I：
10.19595/j.cnki.1000-6753.tces.L80131
中图分类号：
学科分类号：
摘要：
The rapid growth of electric vehicles requires more fast charging stations to provide service. This paper proposes a charging station planning model based on the characteristics of urban road network and electric vehicle travel probability matrix. Firstly, the driving characteristics of electric vehicles are simulated based on the topological structure of urban roads and improved speed-flow relationship model. On this basis, the Monte Carlo method is used to predict the spatial-temporal distribution of fast charging demands by constructing the electric vehicle travel probability matrix. From the perspective of user-friendly charging, based on comprehensive consideration of charging station construction costs and minimizing driving costs for drivers, a constant volume model for the location of electric vehicle charging stations is established based on the trip probability matrix; and the charging station service areas are divided by Voronoi diagram. The scope, through the improved particle swarm algorithm to determine the optimal location of the charging station, the use of queuing theory to optimize the capacity of each charging station, a statistically more reasonable result is obtained. Finally, a simulation analysis of an electric vehicle charging station planning in a downtown area has been conducted to verify the feasibility and effectiveness of the model and method. © 2019, Electrical Technology Press Co. Ltd. All right reserved.
引用
收藏
页码：272 / 281
页数：9
相关论文
共 15 条
  • [1] Xiao X., Wen J., Tao S., Et al., Study and recommendations of the key issues in planning of electric vehicles' charging facilities, Transactions of China Electrotechnical Society, 29, 8, pp. 1-10, (2014)
  • [2] Guo G., Design difficulties analysis and solution of electric vehicle charging station, Electrical Engineering, 19, 5, (2018)
  • [3] Ma X., Wang H., Li Y., Et al., Optimal planning of charging stations for electric vehicle based on weight-changed Voronoi diagram and hybrid particle swarm optimization algorithm, Transactions of China Electrotechnical Society, 32, 19, pp. 160-169, (2017)
  • [4] Ge S., Zhu L., Liu H., 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)
  • [5] Ding D., Dai K., Zhang X., Et al., Network planning for electric vehicle charging based on fuzzy multi-objective optimization, Power System Protection and Control, 46, 3, pp. 43-50, (2018)
  • [6] Shu J., Tang G., Han B., Two-stage method for optimal planning of electric vehicle charging station, Transactions of China Electrotechnical Society, 32, 3, pp. 10-17, (2017)
  • [7] Hu Y., Pi Y., Cui J., Et al., Research on electric vehicle charging station modeling, Power System Protection and Control, 45, 8, pp. 107-112, (2017)
  • [8] Zhang C., Ding M., Zhang J., A temporal and spatial distribution forecasting of private car charging load based on origin-destination matrix, Transactions of China Electrotechnical Society, 32, 1, pp. 78-87, (2017)
  • [9] Chen L., Nie Y., Zhong Q., A model for electric vehicle charging load forecasting based on trip chains, Transactions of China Electrotechnical Society, 30, 4, pp. 216-225, (2015)
  • [10] Shao Y., Mu Y., Yu X., Et al., A spatial-temporal charging load forecast and impact analysis method for distribution network using EVs-traffic-distribution model, Proceedings of the CSEE, 37, 18, (2017)
12