电力系统自动化2025，Vol.49Issue(21)：53-63,11.DOI:10.7500/AEPS20240302003
极端冰雪天气下计及孤岛划分与融合的配电网故障恢复
Service Restoration of Distribution Network Under Extreme Weather of Ice and Snow Considering Islanding Partition and Combination
摘要
Abstract
In order to achieve the problem of service restoration after large-scale power outage in distribution networks under extreme weather of ice and snow,and solve the problem that the existing islanding partition methods have not effectively considered the combination between neighboring islands,this paper proposes a service restoration method for distribution networks under extreme weather of ice and snow considering the islanding partition and combination.First,the factor of conductor current-carrying temperature change is considered in the conductor ice-cover growth rate model for distribution network.The component failure rate model considering the current thermal effect is proposed.Secondly,on the basis of the traditional virtual current model based on the idea of single-commodity flow,the quantitative relationship between the virtual power and the bus state variables and branch state variables among the islanded areas is comprehensively considered,and the constraint relationship between the virtual power flow and the node state variables and branch state variables is determined by combining with the actual operation status of the distribution network.The service restoration model of distribution network considering islanding partition and combination is constructed.Finally,the effectiveness of the proposed method is verified on PG&E69 test system and an actual 185-bus distribution system.关键词
配电网/极端天气/热效应/孤岛划分/故障恢复/单商品流Key words
distribution network/extreme weather/thermal effect/islanding partition/service restoration/single-commodity flow引用本文复制引用
吉兴全,臧祥宇,张玉敏,文福拴,杨明,王成福..极端冰雪天气下计及孤岛划分与融合的配电网故障恢复[J].电力系统自动化,2025,49(21):53-63,11.基金项目
国家自然科学基金资助项目(52107111) （52107111）
中国博士后科学基金面上资助项目(2023M734092) （2023M734092）
山东省自然科学基金资助项目(ZR2022ME219). This work is supported by National Natural Science Foundation of China(No.52107111),Chinese Postdoctoral Science Foundation(No.2023M734092),and Shandong Provincial Natural Science Foundation of China(No.ZR2022ME219). （ZR2022ME219）
