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Network reliability analysis based on percolation theory

Author

Listed:
  • Li, Daqing
  • Zhang, Qiong
  • Zio, Enrico
  • Havlin, Shlomo
  • Kang, Rui

Abstract

In this paper, we propose a new way of looking at the reliability of a network using percolation theory. In this new view, a network failure can be regarded as a percolation process and the critical threshold of percolation can be used as network failure criterion linked to the operational settings under control. To demonstrate our approach, we consider both random network models and real networks with different nodes and/or edges lifetime distributions. We study numerically and theoretically the network reliability and find that the network reliability can be solved as a voting system with threshold given by percolation theory. Then we find that the average lifetime of random network increases linearly with the average lifetime of its nodes with uniform life distributions. Furthermore, the average lifetime of the network becomes saturated when system size is increased. Finally, we demonstrate our method on the transmission network system of IEEE 14 bus.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:reensy:v:142:y:2015:i:c:p:556-562
    DOI: 10.1016/j.ress.2015.05.021
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    References listed on IDEAS

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    1. 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.
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    7. 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.
    8. Zio, E. & Ferrario, E., 2013. "A framework for the system-of-systems analysis of the risk for a safety-critical plant exposed to external events," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 114-125.
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