Large-scale electric vehicle charging path planning based on information interaction
ZHANG Shuwei1, FENG Guixuan1,2, FAN Yuezhen2, WAN Shuang1,2, LUO Yugong1
1. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China; 2. School of Engineering, Beijing Forestry University, Beijing 100083, China
Abstract：With the increasing numbers of electric vehicles, electric vehicle charging can result in traffic congestion near the charging stations during peak charging times with long wait times, power grid load fluctuations and other issues. Real-time information communication systems can be used in a charging path planning method for electric vehicles based on traffic network, charging stations and distribution network information. The system constraints include the traffic conditions, vehicle charging requirements, charging station loads, and grid loads. The multi-objective optimization function includes the travel time, number of vehicles in the charging stations, and charging loads with an improved Dijkstra method used to solve the optimization problem. Simulations show that this method improves the distribution operations, relieves traffic congestion around the charging stations, reduces the wait times and improves the usability of the charging infrastructure.
张书玮, 冯桂璇, 樊月珍, 万爽, 罗禹贡. 基于信息交互的大规模电动汽车充电路径规划[J]. 清华大学学报（自然科学版）, 2018, 58(3): 279-285.
ZHANG Shuwei, FENG Guixuan, FAN Yuezhen, WAN Shuang, LUO Yugong. Large-scale electric vehicle charging path planning based on information interaction. Journal of Tsinghua University(Science and Technology), 2018, 58(3): 279-285.
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2018, Vol. 58 
