Multi-dimensional Resilience Enhancement Strategy for Distribution Network During Typhoon Based on Improved Normal Constraints Method

被引：0

作者：

Ke, Jun ^{[1
,2
]}

Wang, Xu ^{[1
,2
]}

Wei, Xinchi ^{[3
]}

Jiang, Chuanwen ^{[1
,2
]}

Yang, Hongkun ^{[1
,2
]}

Zhang, Ke ^{[1
,2
]}

机构：

[1] Key Laboratory of Control of Power Transmission and Conversion, Shanghai Jiao Tong University, Shanghai

[2] Shanghai Non-carbon Energy Conversion and Utilization Institute, Shanghai

[3] State Grid Shanghai Electric Power Research Institute, Shanghai

来源：

Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2025年 / 49卷 / 14期

基金：

中国国家自然科学基金;

关键词：

distribution network; multi-objective optimization; normal constraint; power supply capability; power supply reliability; resilience; typhoon; uncertainty;

D O I：

10.7500/AEPS20240717002

中图分类号：

学科分类号：

摘要：

To address the decline in power supply capability of distribution networks during typhoons, it is necessary to fully utilize distributed resources in distribution networks and enhance the resilience of distribution networks during disasters from multiple aspects such as comprehensive power supply reliability, disaster resistance resource utilization rate, and power quality. Based on the typhoon asymmetric wind field disaster model, a dual-layer architecture of distribution networks is proposed based on the improved normal constraint method to support multi-dimensional resilience enhancement strategies collaboratively. First, the typhoon asymmetric wind field is parameterized and modeled in combination with meteorological information, and the uncertainty model of breakage on the affected lines and the safe output model of renewable energy are established. Then, a dual-layer operation architecture of source-grid-load-storage collaborative support for disaster response scheduling in distribution networks is established, and multi-dimensional resilience evaluation indicators considering power supply capability, resource utilization rate, and power quality are proposed. On this basis, the improved normal constraint method is used to quickly solve the boundary time-varying mixed-integer second-order cone programming multi-objective optimization problem, and the decision edge with high information entropy is obtained. Finally, the IEEE 33-bus distribution system is used for case study to examine the application ability of the proposed strategy. © 2025 Automation of Electric Power Systems Press. All rights reserved.

引用

页码：99 / 108

页数：9

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