Resilience Analysis of Power System for Seismic Disaster Mitigation

Natural disasters may severely impact critical infrastructure and lifelines and even cause the shutdown of essential facilities. This research proposes a novel assessment framework for earthquake risk and resilience of the power system. It aims to find the most feasible disaster prevention and emergency strategies to improve community resilience by comprehensively considering the 4R (Robustness, Rapidity, Redundancy, Resourcefulness) indicators. In this study, the power system in Taipei City was adopted as the case study. Graph Analysis was first conducted to analyze the centrality of each station and the influence after its breakdown for determining the critical nodes. Then, Monte Carlo simulations were carried out to simulate the damage and recovery of the power system under the considered earthquake scenario. Also, the quantitative measurements for Robustness, Rapidity, Redundancy, and Resourcefulness of the power system have been well-defined individually. The high-risk and vulnerable areas in the case study are recognized. Afterward, based on the results of multi-objective optimization, the optimal disaster prevention and emergency strategies from 4R perspectives can be investigated. The result indicates that the critical power plants and substations can be served as the priority protection targets. However, with limited resources, there is a trade-off between 4R, such as enhancing resisting capacity in advance, providing alternatives during a disaster, or accelerating the restoration of the power system in the aftermath of earthquakes. By comparing the obtained optimal resilience strategies with the government's current policies, the feasibility of the strategies can be discussed. The goal of the research is to enhance the resilience performance of cities when facing disasters. The assessment framework can be applied to other lifeline systems, and the interdependencies between different critical infrastructures should be taken into account in future studies.