电动汽车充电站最优规划的两阶段方法

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摘要计及道路网络对电动汽车充电需求的影响,提出了充电站最优规划的两阶段方法。该方法的第一阶段基于电动汽车行驶特性,综合考虑电动汽车日剩余电量以及电动汽车动态运行状态和位置,采用随机模拟技术和最短路径法,获得道路网络上电动汽车充电需求在时间和空间上的分布;第二阶段以第一阶段获得的电动汽车充电需求为基础,以充电需求不可达率、不满足率和投资限额等为约束,充电站运行成本和投资成本综合最小为目标,建立充电站最优选址定容数学模型。针对该模型的复杂性,采用遗传算法求解混合整数非线性规划问题。通过对某区域的电动汽车充电站规划的模拟分析,表明了所提方法的有效性。

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	舒隽
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关键词 ：电动汽车, 充电站规划, 随机模拟, 最短路径法, 遗传算法

Abstract：Considering the impact of the road network on the charging demand of electric vehicles, this paper presents a two-stage method to solve the optimal planning of charging station problem. In the first stage, stochastic simulation technique and the shortest path method are applied to determine the distribution of charging demand in time and space of electric vehicles on road network based on the driving characteristics, the battery residual capacity, as well as the dynamic state and location of electric vehicles. The second stage, based on the charging demand of electric vehicles derived from the first stage, proposes a mathematical model of optimal location of charging station with the objective of minimizing investment and operation costs, of which the electric vehicle charging rate constraint, arriving rate constraint and the total investment limitation are examined to ensure the feasibility of the solution. To overcome difficulties in solving the mixed-integer nonlinear optimization problem, genetic algorithm is introduced. The effectiveness of the proposed approach is validated by numerical case studyingon the electric vehicles charging station that planning of a certain area.

Key words： Electric vehicle charging station stochastic simulation shortest path method genetic algorithm

收稿日期: 2015-09-20 出版日期: 2017-02-27

PACS:

TM72

基金资助:国家自然科学基金资助项目(51347003)。

通讯作者: 唐刚男,1991年生,硕士研究生,研究方向为新能源、电力系统规划。E-mail:tg02040057@163.com(通信作者)

作者简介: 舒隽男,1974年生,博士,副教授,研究方向为电力市场、电力系统运行优化、电力系统规划等。E-mail:junshu2000@sina.com

引用本文:

舒隽, 唐刚, 韩冰. 电动汽车充电站最优规划的两阶段方法[J]. 电工技术学报, 2017, 32(3): 10-17. Shu Jun, Tang Gang, Han Bing. Two-Stage Method for Optimal Planning of Electric Vehicle Charging Station. Transactions of China Electrotechnical Society, 2017, 32(3): 10-17.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2017/V32/I3/10

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