Resilience Assessment for Interconnected Power Systems Under Typhoon-Rainstorm Disasters: An AP-ADMM-Based Distributed Approach
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Le résumé fourni par la source
Typhoons, especially those coupled with rainstorm events, pose a significant threat to the safe and stable operation of power systems, bringing a high potential risk of large-scale blackouts and extensive economic loss. In the context of global grid interconnection, inter-system mutual assistance is regarded as a promising way to mitigate the destructive impacts of typhoon-rainstorm disasters. Regrettably, scant attention has been paid to the resilience performance of interconnected power systems (IPS) in existing works. This paper proposes a joint assessment model to quantify the overall resilience of all subsystems within IPS under typhoon-rainstorm disasters, and a distributed optimization approach based on the adaptive penalty alternating direction method of multipliers (AP-ADMM) algorithm is further developed to solve the proposed model with well-preserved individual privacy. The results of numerical experiments on the modified IEEE 30-bus test system suggest that grid interconnection with inter-system mutual assistance is an effective way to mitigate the potential risk of power outages and economic loss caused by typhoon-rainstorm disasters, where all subsystems benefit from the cooperation with resilience enhancement. In addition, the developed adaptive penalty principle demonstrates superior convergence performance, accelerating the iteration process under the premise of ensuring accuracy.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Resilience Assessment for Interconnected Power Systems Under Typhoon-Rainstorm Disasters: An AP-ADMM-Based Distributed Approach
- Date Crossref
- 29/09/2025
- Éditeur
- IEEE
- Type
- proceedings-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
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