考虑需求差异化和配电网运行风险的充电站规划
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引用本文:杨景旭,张勇军.考虑需求差异化和配电网运行风险的充电站规划[J].电网与清洁能源,2020,36(8):9~20
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作者单位
杨景旭 华南理工大学 电力学院 
张勇军 华南理工大学 电力学院 
基金项目:广东省自然科学基金项目(2017A030313304)
中文摘要:针对电动汽车充电站规划与用户需求及配电网运行的适配性问题,在采用EV空间转移概率模型来模拟用户出行不确定性时考虑充电站规划对用户充电行为的影响;综合建设成本、用户充电体验和配电网运行风险等需求建立充电站规划目标;建立空间权重来反映不同功能区域对充电站需求的差异,提出计及空间权重的两级加权Voronoi图进行充电站服务范围分区;分别基于粒子群优化算法和循环支路替换法提出充电站选址定容和充电负荷接入节点优化方法。以一个规划区为例,通过不同充电站数下规划方案对比选出最优方案,结果表明,考虑空间权重的TWVD分区方法比加权Voronoi图具有更好的分区效果。
中文关键词:充电站  Voronoi图  空间权重  空间转移  运行风险
 
Planning of Charging Stations Considering Differentiation of Demand and Operation Risk of Distribution Network
Abstract:In view of the adaptability of the planning of electric vehicle(EV) charging stations to the demand of users and the operation of the distribution network, the influence of the planning of charging stations on the charging behaviors of users is considered when the probability model of the spatial transfer of EVs is applied to simulate the uncertainty of users’ travel. Considering the demands of construction costs, user charging experience and the operation risks of the distribution network comprehensively, the goal of the planning of charging stations is established. The spatial weight is built up to reflect the difference of the demands for charging stations of various functional areas, based on which a two-level weighted Voronoi diagram(TWVD) is put forward to partition the service scope of charging stations. Based on particle swarm optimization algorithm and cyclic branch replacement method, the methods of the optimization of location and capacity of charging stations and access nodes of charging loads are proposed respectively. Finally, taking a planning area as an example, the optimal scheme is selected by comparing the planning schemes under different number of charging stations, and the effectiveness of the charging station planning method in this paper is analyzed. The results show that the TWVD partition method considering spatial weights has better partition effect than the weighted Voronoi diagram.
keywords:charging station  Voronoi diagram  spatial weight  spatial transfer  operation risk
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