Motif-based resiliency assessment for cyber-physical power systems under various hazards

Abstract

Cyber-physical power systems (CPPS) are integral to meeting society's demand for secure, sustainable, affordable and resilient critical networks and services. Given the convergence of decarbonising, heating, cooling, and transportation networks onto cyber-physical power systems (CPPS), this takes on increased significance. This paper introduces an innovative approach to the open challenge of how we evaluate CPPS resilience, presenting the use of network motifs and Monte Carlo simulations. We demonstrate how our methodology enables a comprehensive analysis of CPPS by capturing the interdependence between cyber and physical networks and by accounting for inherent uncertainties in cyber and physical components. Specifically, this method incorporates the dynamic interplay between the physical and cyber networks, presenting a time-dependent motif-based resilience metric. This metric evaluates CPPS performance in maintaining critical loads during and after diverse extreme events in cyber and/or physical layers. The resilience status of the system is determined using the prevalence of 4-node motifs within the system's network, offering valuable redundant paths for critical load supply. The study models a variety of natural events, including earthquakes, windstorms, and tornadoes, along with cyber-attacks while accounting for their inherent uncertainties using Monte Carlo simulation. The proposed approach is demonstrated through two test CPPS, specifically the IEEE 14-bus and IEEE 30-bus test systems, affirming its effectiveness in quantifying CPPS resilience. By comprehensively addressing system dynamics, interdependencies, and uncertainties, the proposed technique advances our understanding of CPPS and supports resilient system design.