Electric Vehicle Charging Station Planning Based on Travel Probability Matrix
Jiang Xin1, Feng Yongtao1, Xiong Hu2, Wang Jinfeng1, Zeng Qingshan1
1. School of Electrical Engineering Zhengzhou University Zhengzhou 450001 China; 2. State Grid Hubei Electric Power Research Institute Wuhan 470032 China
Abstract：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.
姜欣, 冯永涛, 熊虎, 王金凤, 曾庆山. 基于出行概率矩阵的电动汽车充电站规划[J]. 电工技术学报, 2019, 34(zk1): 272-281.
Jiang Xin, Feng Yongtao, Xiong Hu, Wang Jinfeng, Zeng Qingshan. Electric Vehicle Charging Station Planning Based on Travel Probability Matrix. Transactions of China Electrotechnical Society, 2019, 34(zk1): 272-281.
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2019, Vol. 34 
