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Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis

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  • Ouyang, Min
  • Wang, Zhenghua

Abstract

As infrastructure systems are highly interconnected, it is crucial to analyze their resilience with the consideration of their interdependencies. This paper adapts an existing resilience assessment framework for single systems to interdependent systems and mainly focuses on modeling and resilience contribution analysis of multi-systems’ joint restoration processes, which are seldom addressed in the literature. Taking interdependent power and gas systems in Houston, Texas, USA under hurricane hazards as an illustrative exmaple, five types of joint restoration stategies are proposed, including random restoration strategy RS1, independent restoration strategy RS2, power first and gas second restoration strategy RS3, gas aimed restoration strategy RS4, and power and gas compromised restoration strategy RS5. Results show that under limited restoration resources, RS1 produces the least resilience for both systems, RS2 and RS3 both generates the largest power system resilience while RS4 is the best for the gas system; and if quantifying the total resilience as the evenly weighted sum of two systems’ individual resilience, RS5 produces the largest total resilience. The proposed method can help decision makers search optimum joint restoration strategy, which can significantly enhance both systems’ resilience.

Suggested Citation

  • Ouyang, Min & Wang, Zhenghua, 2015. "Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis," Reliability Engineering and System Safety, Elsevier, vol. 141(C), pages 74-82.
    • Handle: RePEc:eee:reensy:v:141:y:2015:i:c:p:74-82
    DOI: 10.1016/j.ress.2015.03.011
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    References listed on IDEAS

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    1. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    2. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
    3. Ouyang, Min & Dueñas-Osorio, Leonardo, 2011. "An approach to design interface topologies across interdependent urban infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1462-1473.
    4. Monforti, F. & Szikszai, A., 2010. "A MonteCarlo approach for assessing the adequacy of the European gas transmission system under supply crisis conditions," Energy Policy, Elsevier, vol. 38(5), pages 2486-2498, May.
    5. Ouyang, Min & Zhao, Lijing & Pan, Zhezhe & Hong, Liu, 2014. "Comparisons of complex network based models and direct current power flow model to analyze power grid vulnerability under intentional attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 45-53.
    6. Ouyang, Min & Zhao, Lijing & Hong, Liu & Pan, Zhezhe, 2014. "Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 38-46.
    7. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
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