Risk Assessment and Restoration Prioritization of Urban Distribution Networks Considering Rainstorm-Induced Disaster
Yiliang Chen1, Qianhu Wei1, Kui Xu1, Zhichang Liu1, Zewei Lin1, Zhaohui Xu1, Xi Zheng1, Jun Jia2,*, Ke He2, Weidong Zhong2
1 Shenzhen Power Supply Bureau Co., Ltd., Shenzhen, China
2 Sichuan Energy Internet Research Institute, Tsinghua University, Chengdu, China
* Corresponding Author: Jun Jia. Email:
Energy Engineering https://doi.org/10.32604/ee.2026.080074
Received 02 February 2026; Accepted 15 April 2026; Published online 05 May 2026
Abstract
The secure operation of distribution networks is essential for modern urban systems. However, during extreme rainfall events, multiple hazards, including waterlogging, flooding, seawater backflow, and geological instability, may occur simultaneously. The strong coupling among these factors can generate cascading disaster chains that significantly threaten distribution network reliability. To address this challenge, this study develops a practical framework for risk assessment and dispatch support that explicitly accounts for disaster-chain impacts on distribution networks. Multiple environmental and infrastructure-related indicators are incorporated to characterize regional risk conditions. Entropy-based weighting is employed to ensure that each indicator accurately reflects its relative contribution to the overall network risk, while fuzzy membership evaluation integrates multiple factors, disaster-chain effects into a unified regional risk index. Furthermore, by considering node interactions within the distribution network and the prevailing fault conditions across different regions, a restoration priority index is established to guide repair sequencing. Case studies under extreme rainfall scenarios demonstrate that the proposed method achieves higher fault detection rates and improved spatial coverage compared with the conventional weighted-sum approaches.
Keywords
Distribution networks; multi-hazard risk assessment; emergency dispatch; extreme rainfall; fuzzy synthetic evaluation; restoration priority