电力系统自动化2026，Vol.50Issue(2)：60-70,11.DOI:10.7500/AEPS20250410005
极端冰雪天气下计及故障演化的有源配电网故障恢复方法
Fault Restoration Method for Active Distribution Network Considering Fault Evolution Under Extreme Ice and Snow Weather
摘要
Abstract
The mechanism of fault evolution in distribution networks under extreme ice and snow weather is not accurately characterized.Additionally,existing fault restoration methods in distribution network cannot effectively represent the control methods of distributed power sources.This paper proposes a fault restoration method for active distribution networks considering fault evolution under extreme ice and snow weather.Firstly,this paper clarifies the impact of distribution line faults and uncertainty in distribution network power flow under extreme ice and snow weather.The probability of distribution line faults and the probability of system state transitions are quantified.A cascading fault evolution model for distribution network based on probabilistic power flow is constructed.Secondly,based on the region partitioning concept of point-based localization,the hierarchical relationships among master control nodes,subordinate control nodes,and load nodes within islanded regions are comprehensively considered.By integrating the master-slave control logic of islanded operation,a fault restoration model of distribution network is proposed,incorporating the coordination of network reconfiguration and island partition.Finally,the effectiveness of the proposed strategy is verified using the PG&E 69-bus distribution system and a certain 185-bus actual distribution system.关键词
随机潮流/极端冰雪天气/连锁故障/主从控制/故障恢复/配电网重构/孤岛划分/有源配电网Key words
probabilistic power flow/extreme ice and snow weather/cascading fault/master-slave control/fault restoration/distribution network reconfiguration/island partition/active distribution network引用本文复制引用
吉兴全,臧祥宇,张玉敏,叶平峰,杨明,文福拴..极端冰雪天气下计及故障演化的有源配电网故障恢复方法[J].电力系统自动化,2026,50(2):60-70,11.基金项目
国家自然科学基金资助项目(52177095) （52177095）
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.52177095),China Postdoctoral Science Foundation(No.2023M734092),and Shandong Provincial Natural Science Foundation of China(No.ZR2022ME219). （ZR2022ME219）
