A Hierarchical Resilience Enhancement Framework for Interdependent Critical Infrastructures

Xing Liu, Yi-Ping Fang and Enrico Zio

Reliability Engineering and System Safety, 2021, vol. 215, issue C

Abstract: Resilience is becoming a key concept for risk assessment and safety management of interdependent critical infrastructures (ICIs). This work proposes a resilience enhancement framework for ICIs. With reference to the accidental event, ex-ante and ex-post solutions for enhancing system resilience are analysed and included into a hierarchical model of resilience enhancement strategies (RES). To provide specific resilience enhancement solutions for ICIs, we integrate the hierarchical model with a model predictive control-based dynamic model of ICI system operation. The relationships between the solutions implemented and their impacts on the system parameters are discussed. A multi-objective optimization (MOO) problem is defined, with the objectives of simultaneously minimizing RES cost and maximizing ICIs resilience. The fast non-dominated sorting genetic algorithm NSGA-II is used to solve the MOO problem. For exemplification, a case study is considered, involving interdependent natural gas network and electric power grid. The results show that the resilience enhancement framework is effective in finding optimal RESs for given ICIs.

Keywords: Critical infrastructure; Resilience; Control-based dynamic model; Multi-objective optimization (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (28)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021003872

DOI: 10.1016/j.ress.2021.107868

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