电力系统自动化Issue(14)：75-81,104,8.DOI:10.7500/AEPS20140825008
计及电动汽车充电站作为黑启动电源的网架重构优化策略
An Optimization Strategy for Network Reconfiguration with Charging Stations of Electric Vehicles as Black-start Power Sources
摘要
Abstract
Supported by large-scale centralized charging stations of electric vehicles (EVs),the battery swapping mode with battery leasing is a commercially competitive way for the development of EVs. Given this background, a network reconfiguration strategy taking the EV charging stations into account is presented.First,the capacity provided by the batteries in an EV charging station is modeled,and thus the capacity for restarting the non-black-start units can be obtained whenever a power outage occurs.Then,a bi-level optimization based model for the network reconfiguration is proposed.In the upper-level optimization model,the recovery time of a generating unit is determined by maximizing the restored generation capacity,while in the lower-level the restoration path is optimized by minimizing the charging capacitance of the recovered lines.A chance-constrained programming method is employed to address the risks arising from uncertain factors during the system restoration, and then a bi-level optimization model for the network reconfiguration based on chance-constrained programming is presented. An improved particle swarm optimization algorithm is employed to solve the model developed.Finally,a modified New England 10-unit 39-bus power system is employed to demonstrate the basic characteristics of the model and method developed.关键词
电力系统恢复/电动汽车/充电站/机会约束规划/双层优化Key words
power system restoration/electric vehicle/charging stations/chance-constrained programming/bi-level optimization引用本文复制引用
孙磊,张璨,林振智,福拴,吕浩华,李波..计及电动汽车充电站作为黑启动电源的网架重构优化策略[J].电力系统自动化,2015,(14):75-81,104,8.基金项目
国家重点基础研究发展计划(973计划)资助项目(2013CB228202) （973计划）
国家自然科学基金资助项目(51177145,51377005) （51177145,51377005）
国网浙江省电力公司科技项目(5211DF13500M)。@@@@ This work is supported by National Basic Research Program of China (973 Program)(No.2013CB228202),National Natural Science Foundation of China(No.51177145,No.51377005) and a project from State Grid Zhejiang Electric Power Company(No.5211DF13500M) （5211DF13500M）
