Quantifying the value of seismic structural health monitoring for post-earthquake recovery of electric power system in terms of resilience enhancement

IF 11 1区工程技术 Q1 ENGINEERING, INDUSTRIAL

Reliability Engineering & System Safety Pub Date : 2026-09-01 Epub Date: 2026-01-31 DOI:10.1016/j.ress.2026.112292

Huangbin Liang , Beatriz Moya , Francisco Chinesta , Eleni Chatzi

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引用次数: 0

Abstract

Post-earthquake recovery of electric power networks (EPNs) is critical to community resilience. Traditional recovery processes often rely on prolonged and imprecise manual inspections for damage diagnosis, leading to suboptimal repair prioritization and extended service disruptions. Seismic Structural Health Monitoring (SSHM) offers the potential to expedite post-earthquake recovery by enabling more accurate and timely damage assessment. However, the deployment of SSHM comes with a cost and the quantifiable benefit of SSHM in terms of system-level resilience remains underexplored. This study develops an integrated probabilistic simulation framework to quantify the system-level value of SSHM in enhancing EPN resilience. The framework incorporates damage simulations based on EPN configuration, seismic hazard, fragility function, and damage-functionality mapping models, along with recovery simulations considering repair scheduling, resource constraints, transfer and repair durations. System functionality is evaluated via graph-based island detection and optimal power flow analysis under electrical constraints. Resilience is quantified using the Lack of Resilience (LoR) metric derived from the time-evolution functionality restoration curve. The effect of SSHM is incorporated by altering the quality of damage information used to create repair schedules. Specifically, different monitoring scenarios (e.g., no-SSHM baseline, partial SSHM, and full SSHM with various assessing accuracy levels) are modelled using observation matrices that simulate misclassification of component damage states. The results demonstrate that improved damage awareness enabled by SSHM significantly accelerates recovery and reduces LoR by up to 21%. This study provides a quantitative foundation for evaluating the system-level resilience benefits of SSHM and guiding evidence-based sensor investment decisions for critical infrastructures.

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量化地震结构健康监测对电力系统灾后恢复弹性增强的价值

震后电网的恢复对社区的恢复能力至关重要。传统的恢复过程通常依赖于长时间和不精确的人工检查来进行损坏诊断，从而导致次优的修复优先级和延长的服务中断。地震结构健康监测（SSHM）通过实现更准确和及时的损害评估，为加速震后恢复提供了潜力。然而，部署SSHM是有成本的，而SSHM在系统级弹性方面的可量化收益仍未得到充分探索。本研究开发了一个综合概率模拟框架，以量化SSHM在增强EPN弹性方面的系统级价值。该框架结合了基于EPN配置、地震危害、易损性函数和损伤功能映射模型的损伤模拟，以及考虑修复调度、资源约束、转移和修复持续时间的恢复模拟。通过基于图的孤岛检测和在电气约束下的最优潮流分析来评估系统功能。利用从时间演化功能恢复曲线中导出的缺乏弹性（LoR）度量来量化弹性。通过改变用于制定维修计划的损坏信息的质量，将SSHM的影响纳入其中。具体来说，不同的监测场景（例如，无SSHM基线，部分SSHM和具有不同评估精度水平的完全SSHM）使用模拟组件损伤状态错误分类的观察矩阵进行建模。结果表明，SSHM提高了损伤意识，显著加快了恢复速度，并将损失损失降低了21%。该研究为评估SSHM的系统级弹性效益和指导关键基础设施的基于证据的传感器投资决策提供了定量基础。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Reliability Engineering & System Safety 管理科学-工程：工业

CiteScore

15.20

自引率

39.50%

发文量

621

审稿时长

67 days

期刊介绍： Elsevier publishes Reliability Engineering & System Safety in association with the European Safety and Reliability Association and the Safety Engineering and Risk Analysis Division. The international journal is devoted to developing and applying methods to enhance the safety and reliability of complex technological systems, like nuclear power plants, chemical plants, hazardous waste facilities, space systems, offshore and maritime systems, transportation systems, constructed infrastructure, and manufacturing plants. The journal normally publishes only articles that involve the analysis of substantive problems related to the reliability of complex systems or present techniques and/or theoretical results that have a discernable relationship to the solution of such problems. An important aim is to balance academic material and practical applications.