Strategies to Improve the Resilience of Power Distribution Networks Under the Influence of Combined Extreme Weather
In recent years, the increasing frequency of typhoons and urban flooding incidents has significantly jeopardized the power supply security of distribution networks in coastal metropolitan areas. Given this critical situation, the strategic allocation of pre-disaster preparedness resources and post-disaster recovery resources has become paramount in enhancing the resilience of distribution networks. This study presents a comprehensive methodology for improving distribution network resilience through optimized pre-disaster resource deployment and post-disaster recovery scheduling. The proposed approach focuses on achieving efficient coordination among drainage systems, repair operations, and mobile energy storage system scheduling under complex extreme weather conditions, including typhoons, torrential rainfall, and urban inundation. The research methodology encompasses three main components: first, the development of a distribution network fault model that accounts for the compounded effects of typhoons and urban flooding; second, the formulation of an integrated model for pre-disaster resource deployment and post-disaster recovery operations, considering the distinctive characteristics of various recovery resources; and finally, the validation of the proposed strategy's efficacy through empirical case analysis. The findings demonstrate the effectiveness of this integrated approach in strengthening distribution network resilience against extreme weather events.
Authors
- Yuhan Wu
- Xinyu Li (ORCID: https://orcid.org/0000-0002-7853-6724)
- Chunming Liu (ORCID: https://orcid.org/0000-0002-0564-4476)
- Zhiyuan Ma (ORCID: https://orcid.org/0000-0002-0381-7804)
- Y. H. Wan
Institutions
- North China Electric Power University (CN)
Publication Details
- Published
- 2025-03-21
- DOI
- https://doi.org/10.1109/sgai64825.2025.11009860
- Citations
- 1
- Primary Topic
- Smart Grid and Power Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.73