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计及充换放储一体化电站的主动配电网故障恢复 被引量:19

Fault Recovery of Active Distribution Network Considering Charging-Swapping-Discharging-Storage Integrated Power Station
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摘要 建立了电动汽车区间负荷模型和充换放储一体化电站(简称一体站)区间负荷紧急支撑模型,提出一体站区间负荷紧急支撑策略及其孤岛区间负荷供电范围划分策略。基于区间理论分析,以系统孤岛负荷、开关动作次数和网损分别作为不同层的优化目标,建立主动配电网故障恢复多层优化区间模型。提出混沌模拟退火帝国竞争算法对故障恢复区间模型进行优化,并提出基于仿射数的区间Dist-Flow法用于潮流计算。算例结果表明所提方法快速、有效。 An interval load model of electric vehicles and an emergency support model of interval load for a charging-swappingdischarging-storage integrated power station(CSDSIS)are established.An emergency support strategy of interval load and an island partition strategy for power supply range of interval load for a CSDSIS are proposed.Based on the analysis of interval theory,a multi-layer optimization interval model of fault recovery for active distribution network(ADN)is established by taking the island load of system,times of breaker switching and power loss as the optimization objectives,respectively.Chaotic simulated annealing imperialist competitive algorithm is proposed to optimize the fault recovery interval model,and an interval Dist-Flow method based on affine number is proposed for power flow calculation.Results of the example show that the proposed method is fast and effective.
作者 何晨可 韦钢 袁丁 朱兰 李扬 HE Chenke;WEI Gang;YUAN Ding;ZHU Lan;LI Yang(First Design Research Institute,Shanghai Municipal Engineering Design Institute(Group)Co.,Ltd.,Shanghai 200092,China;College of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China;Cixi Power Supply Company of State Grid Zhejiang Electric Power Co.,Ltd.,Ningbo 315300,China)
出处 《电力系统自动化》 EI CSCD 北大核心 2020年第13期32-38,共7页 Automation of Electric Power Systems
基金 国家自然科学基金青年基金资助项目(51807114) 上海绿色能源并网工程技术研究中心资助项目(13DZ2251900)。
关键词 充换放储一体化电站 区间理论 主动配电网 故障恢复 多层优化 混沌模拟退火帝国竞争算法 Dist-Flow法 charging-swapping-discharging-storage integrated power station(CSDSIS) interval theory active distribution network fault recovery multi-layer optimization chaotic simulated annealing imperialist competitive algorithm Dist-Flow method
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