首页|Understanding power grid network vulnerability through the stochastic lens of network motif evolution

Understanding power grid network vulnerability through the stochastic lens of network motif evolution

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  • NETL
  • NSTL
  • Oxford Univ Press
Modern cyber-physical systems must exhibit high reliability since their failures can lead to catastrophic cascading events. Enhancing our understanding of the mechanisms behind the functionality of such networks is a key to ensuring the resilience of many critical infrastructures. In this paper, we develop a novel stochastic model, based on topological measures of complex networks, as a framework within which to examine such functionality. The key idea is to evaluate the dynamics of network motifs as descriptors of the underlying network topology and its response to adverse events. Our experiments on multiple power grid networks show that the proposed approach offers a new competitive pathway for resilience quantification of complex systems.

gamma degradation modelhigher-order network substructuresmaximum likelihood estimationnetwork motifspower systemssystem reliability

Yuzhou Chen、Hon Keung Tony Ng、Yulia R. Gel、H. Vincent Poor

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Department of Statistics, University of California, Riverside, CA, USA

Department of Mathematical Sciences, Bentley University, Waltham, MA, USA

Department of Statistics, Virginia Tech, Blacksburg, VA, USA##National Science Foundation, Alexandria, VA, USA

Department of Electrical and Computer Engineering, Princeton University, Princeton, NJ, USA

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2025

10.1093/jrsssc/qlae071

Journal of the royal statistical society, Series C. Applied statistics

Journal of the royal statistical society, Series C. Applied statistics

ISSN：0035-9254
年,卷(期)：2025.74(Pt.3)
  • 59