Understanding Power Grid Network Vulnerability Through the Stochastic Lens of Network Motif Evolution

• Activity Number: 366 - Contributed Poster Presentations: Section on Statistics in Defense and National Security
• Type: Contributed
• Date/Time: Wednesday, August 5, 2020 : 10:00 AM to 2:00 PM
• Sponsor: Section on Statistics in Defense and National Security
• Author(s): Yuzhou Chen* and Hon Keung Tony Ng and Yulia Gel and H. Vincent Poor
• Companies: Southern Methodist Univ, Statistical Science Dept and Southern Methodist University and University of Texas at Dallas and Princeton University
• Keywords: System reliability; Network motifs; Gamma degradation model; Hypothesis testing; Power grid; Robustness

Abstract

Many modern systems and collections of components/devices can be represented as complex networks. These networks such as, for instance, the internet, power grids, and water supply chains, are expected to exhibit high reliability levels since failures of these systems can lead to catastrophic cascading events. As a result, enhancing our understanding of mechanisms behind functionality and reliability of such networks is the key toward ensuring security, sustainability, and resilience of most modern critical infrastructures. Focusing on power grid applications, in this paper we develop a new stochastic model approach based on multiple interdependent topological measures of complex networks. The key engine behind our approach is to evaluate dynamics of multiple network motifs as descriptors of the underlying network topology and its response to adverse events. Under a framework of the gamma degradation family of models, we develop a formal statistical inference for analysis of reliability and robustness levels of a single complex network as well as for assessing differences in reliability properties exhibited by European power grid networks.