4.6 Article

Resilience-based post-earthquake recovery strategies for substation systems

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ELSEVIER
DOI: 10.1016/j.ijdrr.2023.104000

Keywords

Substation system; Functional state model; Seismic resilience framework; Post-earthquake recovery strategy; Optimisation algorithm

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This study proposes a seismic resilience assessment framework based on the functional characteristics of electrical substation systems. It quantifies the functional recovery process and determines efficient post-earthquake recovery strategies using reliability models and seismic simulation. The study also analyzes different repair strategies and their impact on the functional recovery process and seismic resilience level.
Electrical substation systems require significant manpower and material resources for repair after an earthquake; thus, repair efficiency directly affects economic loss. To quantify the functional recovery process of substation systems, this study proposes a seismic resilience assessment frame- work based on the functional characteristics of substation systems. Reliability models of the equipment and systems were constructed to characterise the structural connection features and power transmission paths of substation systems, and the system functional state matrix was ob- tained through a seismic simulation. Moreover, factors influencing functional recovery and repair path control parameters were proposed to determine efficient post -earthquake recovery strate- gies. The Monte Carlo method was used to construct a post -earthquake recovery strategy analysis framework for a substation system. By analysing a typical 220 kV substation using static -based repair strategies, we obtained the functional recovery process and seismic resilience level. Fur- thermore, based on the actual functional requirements, a dynamic recovery strategy analysis method was proposed based on an improved genetic algorithm. Notably, optimal recovery strate- gies for different earthquake intensities and recovery priorities were obtained through iterative reproduction analysis.

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