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作 者:刘航 吕思雨 宗倩 吴寒松 LIU Hang;LV Siyu;ZONG Qian;WU Hansong(State Grid Wuxi Power Supply Company,Wuxi Jiangsu 214000,China)
机构地区:[1]国网江苏省电力有限公司无锡供电分公司,江苏无锡214000
出 处:《自动化与仪器仪表》2025年第3期112-116,共5页Automation & Instrumentation
基 金:国网无锡供电公司2024年电动汽车与区域配网的交互影响与互动机制研究(B21030247395)。
摘 要:针对电动汽车大规模接入下的区域配电网优化控制,研究构建了电动汽车充电负荷预测模型。同时,提出了充放电优化调度模型,采用改进麻雀搜索算法与北方苍鹰算法的结合算法对模型进行求解。结果显示,私家车的充电负荷集中在18:00-22:00,曲线呈“单峰状”,在20:00时,慢充电负荷达到顶峰。同时,出租车的负荷分布曲线呈现“三峰状”,分别在6:00、16:00、23:00达到充电高峰。此外,调度优化后的负荷方差仅为329 kW^(2),用户净花费仅为1.43万元。说明研究所构建的负荷预测模型能够有效预测不同用途电动汽车的充放电负荷需求,有利于集群的充放电调度优化,为配电网的优化控制提供了有效的技术指导。In order to optimize the control of regional distribution networks under the large-scale integration of electric vehicles,a charging load prediction model for electric vehicles was studied and constructed.At the same time,a charging and discharging optimization scheduling model was proposed,which was solved using a combination of improved sparrow search algorithm and northern eagle algorithm.The results show that the charging load of private cars is concentrated between 18:00 and 22:00,with a “unimodal” curve.At 20:00,the slow charging load reaches its peak.At the same time,the load distribution curve of taxis shows a “three peak” pattern,reaching the peak charging hours at 6:00,16:00,and 23:00 respectively.In addition,the load variance after scheduling optimization is only 329 kW~2,and the net user cost is only 14300 yuan.The load forecasting model constructed by the research institute can effectively predict the charging and discharging load demands of electric vehicles for different purposes,which is beneficial for optimizing the charging and discharging scheduling of clusters and providing effective technical guidance for the optimization control of distribution networks.
关 键 词:电动汽车 充放电 配电网 负荷预测 NGO SSA
分 类 号:TM73[电气工程—电力系统及自动化]
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