Systemic risk mitigation strategy for power grid cascade failures using constrained spectral clustering

Abstract

Power grids are prone to damage induced by natural or anthropogenic hazard events that might disrupt the functionality of key/multiple grid components concurrently, resulting in a chain of cascade failures spreading throughout the grid. Through integrating grid operation-guided with structure-driven modeling strategies, the current study proposes an approach to manage the risks of such cascade failure (known as systemic-risks) to minimize the possibility of large-scale catastrophic blackouts. The operation-guided modeling strategy is implemented through dispatch and load shedding to rebalance power demand and supply after disruptive events. On the other hand, the grid structure-driven modeling strategy adopted intentional controlled islanding approach through employing a constrained spectral clustering algorithm. Introducing the latter algorithm within the integrated (operation + structure) cascade failure model facilitated identifying the optimal cut-set lines to separate the grid into a group of functioning sub-grids following initial failure and prior to cascade propagation. To demonstrate the utility of the developed systemic risk management strategy, an actual power grid was simulated using a high-fidelity physics-based model under different disruption scenarios to compare the cascade failure size with and without strategy implementation, considering different numbers of sub-grids. The simulations demonstrate that the integrated (dispatch & load shedding-controlled islanding) strategy can effectively boost the overall grid robustness, and subsequently its resilience, and effectively manage catastrophic blackout systemic risks.