Dynamic Network Flow Model for Power Grid Systemic Risk Assessment and Resilience Enhancement

Abstract

Power infrastructure networks are susceptible to performance disruptions induced by natural or anthropogenic hazard events. For example, extreme weather events or cyberattacks can disrupt the functionality of multiple network components concurrently or sequentially, resulting in a chain of cascading failures throughout the network. Mitigating the impacts of such system-level cascading failures (systemic risks) requires analyzing the entire network considering the physics of its dynamic power flow. This study focuses on the draw-down phase of power infrastructure network resilience—assessing the power grid vulnerability and robustness, through simulating cascading failure propagations using a dynamic cascading failure physics-based model. The study develops and demonstrates the utility of a link vulnerability index to construct power transmission line vulnerability maps, as well as a node importance index for power (sub)station ranking according to the resulting cascading failure size. Overall, understanding the criticality of different network components provides stakeholders with the insights essential for building resilience and subsequently managing it within the context of power grids and supports policymakers and regulators in making informed decisions pertaining to the tolerable degree of systemic risk constrained by available resources.