A Risk Assessment Framework for Large-Scale Synthetic Power Distribution Networks Considering Historical Hurricane Disasters

Theincreasing frequency and severity of hurricane-induced disasters on power distribution networks highlight the growing importance of conducting thorough risk assessments. This paper introduces a hurricane risk assessment framework tailored for large-scale synthetic power distribution systems, aiming to enhance the practicality and accuracy of assessment significantly. The framework provides a refined method for synthesizing power distribution networks by assigning specific building types and importance levels to individual load points. This refinement enables the accurate modeling of the topological structure and physical characteristics of power distribution systems within specific geographic areas. By utilizing real historical hurricane data, the study simulates hurricane scenarios and outages closely resembling actual events, offering a more realistic portrayal of hurricane risks. Incorporating a novel risk indicator for quantitative assessment, each hurricane scenario in the assessment model undergoes evaluation through calculating weighted load reduction. Synthetic distribution networks are established for Emporia and Portsmouth to validate the approach, followed by risk assessment based on historical hurricane occurrences between 1940 and 2024 in both regions. The results underscore the importance of considering city-scale power distribution networks in hurricane risk assessment, as emphasized by the proposed method. Furthermore, the method's ability to accurately capture the impact of spatial heterogeneity of hurricane effects on risk assessment accuracy is demonstrated through comparisons of different hurricane trajectories.

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Publication Details

Journal
IEEE Transactions on Power Systems
Published
2025-01-16
DOI
https://doi.org/10.1109/tpwrs.2025.3530401
Citations
6
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
Field-Weighted Citation Impact
5.72
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article

A Risk Assessment Framework for Large-Scale Synthetic Power Distribution Networks Considering Historical Hurricane Disasters

Chi K. Tse, Shouxiang Wang, Dong Liu, Qianyu Zhao et al.
6 citations
IEEE Transactions on Power Systems
Infrastructure Resilience and Vulnerability Analysis
5.72
article

A Risk Assessment Framework for Large-Scale Synthetic Power Distribution Networks Considering Historical Hurricane Disasters

Chi K. Tse, Shouxiang Wang, Dong Liu, Qianyu Zhao, Shuo Li
article en
6 citations

Abstract

Theincreasing frequency and severity of hurricane-induced disasters on power distribution networks highlight the growing importance of conducting thorough risk assessments. This paper introduces a hurricane risk assessment framework tailored for large-scale synthetic power distribution systems, aiming to enhance the practicality and accuracy of assessment significantly. The framework provides a refined method for synthesizing power distribution networks by assigning specific building types and importance levels to individual load points. This refinement enables the accurate modeling of the topological structure and physical characteristics of power distribution systems within specific geographic areas. By utilizing real historical hurricane data, the study simulates hurricane scenarios and outages closely resembling actual events, offering a more realistic portrayal of hurricane risks. Incorporating a novel risk indicator for quantitative assessment, each hurricane scenario in the assessment model undergoes evaluation through calculating weighted load reduction. Synthetic distribution networks are established for Emporia and Portsmouth to validate the approach, followed by risk assessment based on historical hurricane occurrences between 1940 and 2024 in both regions. The results underscore the importance of considering city-scale power distribution networks in hurricane risk assessment, as emphasized by the proposed method. Furthermore, the method's ability to accurately capture the impact of spatial heterogeneity of hurricane effects on risk assessment accuracy is demonstrated through comparisons of different hurricane trajectories.

IEEE Transactions on Power SystemsVol. 40(5)
Tianjin University (CN), City University of Hong Kong (HK)
Climate action
Openalex Percentile: Top 5%
Infrastructure Resilience and Vulnerability Analysis
5.72
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