印计及光伏的电动汽车多目标协同优化  

Multi-objective Coordinated optimization Considering Electric Vehicles and Photovoltaic

作　　者：包广清[1] 李伟生[1] 张贝 

机构地区：[1]兰州理工大学电气工程与信息工程学院,甘肃兰州730050 [2]国网乌鲁木齐供电公司,乌鲁木齐830011

出　　处：《自动化与仪器仪表》2016年第2期100-102,共3页Automation & Instrumentation

基　　金：国家自然科学基金(51267011)

摘　　要：大规模电动汽车无序充电以及可再生能源渗透率的不断提高,给电力系统安全经济运行带来巨大挑战。本文在城市情况下,考虑了电池容量约束、充放电功率约束及网络约束等约束条件和电动汽车行为特性,以减小配电网等效负荷峰谷差和降低配电网有功网损为目标,建立了计及光伏的电动汽车多目标协同优化模型,利用改进了的粒子群优化算法对所建模型进行求解。最后以IEEE33节点配电网为例进行了分析,结果表明优化入网电动汽车充放电功率可降低等效负荷峰谷差,减小了调峰备用容量,同时降低了配电网网损,提高了配电网运行的经济稳定性。The out-of-order charging of electric vehicles and increasing of renewable energy penetration will provide a major challenge to the safe and economic operation of the power grid. In urban environment,considering the constraints of the electricity quantity stored in the battery,the charging / discharging power and distribution power flow and electric vehicles driving characteristics,to mitigate the peak-to-valley ratio of equivalent load and decrease active power losses of distribution grid,a multi-objective coordinated scheduling model,in which the electric vehicles and photovoltaic generation are taken into account simultaneously,is built. The proposed model is solved by modifiled particle swarm optimization. Finally,with the IEEE 33-bus case as the test system,simulation results indicate that through reasonably optimizing the charging / discharging power of electric vehicles,the method can lower the peak-to-valley ratio of equivalent load,reduce reserve capacity adjusting peak,optimize the active power losses and improve the economy and security of distribution network operation.

关 键 词：电动汽车 光伏 等效负荷 有功网损 粒子群优化算法 

分 类 号：U469.72[机械工程—车辆工程] TP18[交通运输工程—载运工具运用工程]