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Evaluation of the robustness of critical infrastructures by Hierarchical Graph representation, clustering and Monte Carlo simulation

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  • Ferrario, E.
  • Pedroni, N.
  • Zio, E.

Abstract

In this paper, we present a methodological work that adopts a system-of-systems (SoS) viewpoint for the evaluation of the robustness of interdependent critical infrastructures (CIs). We propose a Hierarchical Graph representation, where the product flow is dispatched to the demand nodes in consideration of different priorities. We use a multi-state model to describe different degrees of degradation of the individual components, where the transitions between the different states of degradation occur stochastically. The quantitative evaluation of the CIs robustness is performed by Monte Carlo simulation. The methodological approach proposed is illustrated by way of two case studies: the first one concerns small-sized gas and electricity networks and a supervisory control and data acquisition (SCADA) system; the second one considers a moderately large power distribution network, adapted from the IEEE 123 node test feeders. The large size of the second case study requires hierarchical clustering for performing the robustness analysis.

Suggested Citation

  • Ferrario, E. & Pedroni, N. & Zio, E., 2016. "Evaluation of the robustness of critical infrastructures by Hierarchical Graph representation, clustering and Monte Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 155(C), pages 78-96.
  • Handle: RePEc:eee:reensy:v:155:y:2016:i:c:p:78-96
    DOI: 10.1016/j.ress.2016.06.007
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    Citations

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    Cited by:

    1. Abedi, Amin & Gaudard, Ludovic & Romerio, Franco, 2019. "Review of major approaches to analyze vulnerability in power system," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 153-172.
    2. Wu, Shengnan & Zhang, Laibin & Barros, Anne & Zheng, Wenpei & Liu, Yiliu, 2018. "Performance analysis for subsea blind shear ram preventers subject to testing strategies," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 281-298.
    3. Su, Huai & Zhang, Jinjun & Zio, Enrico & Yang, Nan & Li, Xueyi & Zhang, Zongjie, 2018. "An integrated systemic method for supply reliability assessment of natural gas pipeline networks," Applied Energy, Elsevier, vol. 209(C), pages 489-501.
    4. Chiou, Suh-Wen, 2018. "A traffic-responsive signal control to enhance road network resilience with hazmat transportation in multiple periods," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 105-118.
    5. Rocchetta, Roberto, 2022. "Enhancing the resilience of critical infrastructures: Statistical analysis of power grid spectral clustering and post-contingency vulnerability metrics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    6. Galbusera, Luca & Trucco, Paolo & Giannopoulos, Georgios, 2020. "Modeling interdependencies in multi-sectoral critical infrastructure systems: Evolving the DMCI approach," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    7. Su, Huai & Zio, Enrico & Zhang, Jinjun & Li, Xueyi, 2018. "A systematic framework of vulnerability analysis of a natural gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 79-91.
    8. Lee, Joohyun & Kwak, Jaewook & Lee, Hyang-Won & Shroff, Ness B., 2018. "Finding minimum node separators: A Markov chain Monte Carlo method," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 225-235.
    9. Munikoti, Sai & Lai, Kexing & Natarajan, Balasubramaniam, 2021. "Robustness assessment of Hetero-functional graph theory based model of interdependent urban utility networks," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    10. Abedi, Amin & Romerio, Franco, 2020. "Multi-period vulnerability analysis of power grids under multiple outages: An AC-based bilevel optimization approach," International Journal of Critical Infrastructure Protection, Elsevier, vol. 30(C).
    11. Thomas J. Wilbanks & Rae Zimmerman & Susan Julius & Paul Kirshen & Joel B. Smith & Richard Moss & William Solecki & Matthias Ruth & Stephen Conrad & Steven J. Fernandez & Michael S. Matthews & Michael, 2020. "Toward indicators of the performance of US infrastructures under climate change risks," Climatic Change, Springer, vol. 163(4), pages 1795-1813, December.

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