智能电动车辆最优充电路径规划方法

摘要

未来交通环境下，大规模的智能电动车辆将与城市智能交通网和智能配电网相互作用并相互影响。本文将三者有机结合起来，建立了“车-网-路”智能交互系统模型。该模型包括城市中压配电网模型、道路交通网模型和以快速充电方式充电的大规模智能纯电动汽车模型。在此基础上，基于 Dijkstra最短路径算法，提出了具有实时电网和交通信息反馈的智能电动车辆最优充电路径规划方法。最后，通过 MATLAB和 MATPOWER联合仿真系统对该规划方法进行了仿真评价。仿真评价结果表明，本文提出的最优充电路径规划方法，相比目前广泛采用的最近充电路径规划策略，将能有效降低大规模智能电动车辆快速充电对道路交通网和中压配电网的不利影响。%In the future, the intelligent electric vehicle will interact with and influence on the intelligent transportation system and smart distribution grid. In this paper, the large-scale intelligent EVs, intelligent transportation system and the smart distribution grid are combined into one system. The integrated system of medium voltage city distribution grid model containing 3 types of networks, transportation model, and large-scale IEV model is set up. Under this system, an optimal charging route planning method with real-time feedback of transportation and distribution information based on the Dijkstra’s algorithm is raised. On the basis of this method, simulations are carried out using MATLAB and MATPOWER. The simulation results illustrate that, compared to the nearest charging route planning method, the optimal one can decrease the impact of rapid IEV charging on both transportation and distribution.