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Randomized flow model and centrality measure for electrical power transmission network analysis

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  • Zio, Enrico
  • Piccinelli, Roberta

Abstract

Commonly used centrality measures identify the most important elements in networks of components, based on the assumption that flow occurs in the network only along the shortest paths. This is not so in real networks, where different operational rules drive the flow. For this reason, a different model of flow in a network is considered here: rather than along shortest paths only, it is assumed that contributions come essentially from all paths between nodes, as simulated by random walks. Centrality measures can then be coherently defined. An example of application to an electrical power transmission system is presented.

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  • Zio, Enrico & Piccinelli, Roberta, 2010. "Randomized flow model and centrality measure for electrical power transmission network analysis," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 379-385.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:4:p:379-385
    DOI: 10.1016/j.ress.2009.11.008
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    References listed on IDEAS

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    1. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer;The Psychometric Society, vol. 31(4), pages 581-603, December.
    2. E. Zio, 2007. "From complexity science to reliability efficiency: a new way of looking at complex network systems and critical infrastructures," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 3(3/4), pages 488-508.
    3. Eusgeld, Irene & Kröger, Wolfgang & Sansavini, Giovanni & Schläpfer, Markus & Zio, Enrico, 2009. "The role of network theory and object-oriented modeling within a framework for the vulnerability analysis of critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 94(5), pages 954-963.
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    Cited by:

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    11. Azzolin, Alberto & Dueñas-Osorio, Leonardo & Cadini, Francesco & Zio, Enrico, 2018. "Electrical and topological drivers of the cascading failure dynamics in power transmission networks," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 196-206.
    12. Psaltoglou, Artemis & Calle, Eusebi, 2018. "Enhanced connectivity index – A new measure for identifying critical points in urban public transportation networks," International Journal of Critical Infrastructure Protection, Elsevier, vol. 21(C), pages 22-32.
    13. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2011. "Maximal network reliability for a stochastic power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1332-1339.
    14. Cadini, Francesco & Agliardi, Gian Luca & Zio, Enrico, 2017. "A modeling and simulation framework for the reliability/availability assessment of a power transmission grid subject to cascading failures under extreme weather conditions," Applied Energy, Elsevier, vol. 185(P1), pages 267-279.
    15. Zio, Enrico & Piccinelli, Roberta & Delfanti, Maurizio & Olivieri, Valeria & Pozzi, Mauro, 2012. "Application of the load flow and random flow models for the analysis of power transmission networks," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 102-109.
    16. Xiang, Shihu & Yang, Jun, 2018. "Performance reliability evaluation for mobile ad hoc networks," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 32-39.
    17. Li, Daqing & Zhang, Qiong & Zio, Enrico & Havlin, Shlomo & Kang, Rui, 2015. "Network reliability analysis based on percolation theory," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 556-562.
    18. Wang, Shuliang & Lv, Wenzhuo & Zhang, Jianhua & Luan, Shengyang & Chen, Chen & Gu, Xifeng, 2021. "Method of power network critical nodes identification and robustness enhancement based on a cooperative framework," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    19. Chopade, Pravin & Bikdash, Marwan, 2016. "New centrality measures for assessing smart grid vulnerabilities and predicting brownouts and blackouts," International Journal of Critical Infrastructure Protection, Elsevier, vol. 12(C), pages 29-45.

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