%0 Journal Article
%T 基于信息交互的大规模电动汽车充电路径规划<br>Large-scale electric vehicle charging path planning based on information interaction
%A 张书玮
%A 冯桂璇
%A 樊月珍
%A 万爽
%A 罗禹贡
%J 清华大学学报（自然科学版）
%D 2018
%R 10.16511/j.cnki.qhdxxb.2018.25.008
%X 随着电动汽车的不断普及，在充电高峰时段大规模电动汽车聚集充电，将会导致充电站附近局部交通拥堵，带来用户充电等待、电网负荷大幅波动等问题。该文基于实时的信息交互系统，提出了综合考虑交通网、充电站、配电网信息的大规模电动汽车充电路径规划方法。设定包括路段通行、车辆充电需求、充电站负荷、电网运行等约束条件，建立考虑路段通行时间、充电站车辆数目、充电负荷等因素的多目标优化函数，采用改进的Dijkstra方法对该优化问题进行求解。仿真分析结果表明：该充电路径规划方法在保证配电网正常运行的前提下，可缓解充电站附近的交通拥堵，减少电动汽车用户充电等待时间，提高充电设施的利用率。<br>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.
%K 智能交通系统
%K 路径规划
%K 信息交互
%K 电动汽车
%K 交通拥堵
%K &lt
%K br&gt
%K intelligent transportation
%K path planning
%K information interaction
%K electric vehicle
%K traffic congestion
%U http://jst.tsinghuajournals.com/CN/Y2018/V58/I3/279