Resilience Assessment of Power Distribution System Against Rainstorm-Induced Urban Waterlogging

Frequent rainstorm-induced urban waterlogging poses a severe threat to power distribution systems, resulting in widespread and prolonged outages. Reasonable resilience assessment is an essential prerequisite for disaster prevention and mitigation planning. This paper proposes a pluvial flood resilience assessment framework for distribution systems based on disaster scenario simulation. In the framework, the time evolution of the rainstorm and surface runoff process is simulated, and the pluvial flooding impact is assessed. A distribution system response model based on the time-space network with arrival time function (TSN-ATF) is developed to simulate the power restoration process in conditions of urban road inundation. The parameterized IEEE storm resilience metric is subsequently utilized to quantify the distribution system resilience. Case studies are performed on the modified 33-node test system and a real-world distribution system in central China. Numerical results reveal that flooding duration and site accessibility are critical factors that impede post-rainstorm emergency repair efforts and considerably affect system resilience.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Industry Applications
Published
2025-03-26
DOI
https://doi.org/10.1109/tia.2025.3554467
Citations
5
Primary Topic
Islanding Detection in Power Systems
Type
article
Field-Weighted Citation Impact
3.65
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Resilience Assessment of Power Distribution System Against Rainstorm-Induced Urban Waterlogging

Fengjun Li, Zhaohong Bie, Siyuan Sun, Gengfeng Li et al.
5 citations
IEEE Transactions on Industry Applications
Islanding Detection in Power Systems
3.65
article

Resilience Assessment of Power Distribution System Against Rainstorm-Induced Urban Waterlogging

Fengjun Li, Zhaohong Bie, Siyuan Sun, Gengfeng Li, Jin Liu, Zhao Yang Dong, Mingming Xu, Ming Chen
article en
5 citations

Abstract

Frequent rainstorm-induced urban waterlogging poses a severe threat to power distribution systems, resulting in widespread and prolonged outages. Reasonable resilience assessment is an essential prerequisite for disaster prevention and mitigation planning. This paper proposes a pluvial flood resilience assessment framework for distribution systems based on disaster scenario simulation. In the framework, the time evolution of the rainstorm and surface runoff process is simulated, and the pluvial flooding impact is assessed. A distribution system response model based on the time-space network with arrival time function (TSN-ATF) is developed to simulate the power restoration process in conditions of urban road inundation. The parameterized IEEE storm resilience metric is subsequently utilized to quantify the distribution system resilience. Case studies are performed on the modified 33-node test system and a real-world distribution system in central China. Numerical results reveal that flooding duration and site accessibility are critical factors that impede post-rainstorm emergency repair efforts and considerably affect system resilience.

IEEE Transactions on Industry ApplicationsVol. 61(5)
City University of Hong Kong (HK), Xi'an Jiaotong University (CN)
Climate action
Openalex Percentile: Top 7%
Islanding Detection in Power Systems
3.65
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Resilience Assessment of Power Distribution System Against Rainstorm-Induced Urban Waterlogging — Fengjun Li, Zhaohong Bie, et al. · IEEE Transactions on Industry Applications (2025) | TGRS Research Map | TGRS