Dynamic Resilience Region-Based Proactive Scheduling for Enhancing the Power System Resilience

Abstract

Extreme weather conditions exhibit an unfolding phenomenon in which N-k failures occur sequentially in a power system. Existing proactive scheduling methods primarily employ a rolling approach to address these unfolding events and derive decisions with the objective of optimizing operational costs. However, pursuing the optimal schemes within each present rolling window may lead to substantial load shedding due to unpredictable failure in the subsequent stage. To effectively reduce the load shedding caused by unpredictable failures, the concept of the dynamic resilience region (DRR), which can help identify operation points with maximum security margins when extreme events gradually unfold, is proposed in this paper. First, the DRR is modeled by projecting the intersection of the steady-state security regions of all predictable sequential N-k failures to the schedulable variables. Then, the analytical form of the DRR is theoretically derived. To efficiently acquire the analytical form of the DRR, a solution algorithm based on resilience-cut techniques is proposed, and its convergence is proven. Finally, the DRR-based proactive scheduling method is proposed for handling extreme unfolding events. Within each rolling window, we aim to maximize the security margin rather than minimize the operational costs, thereby significantly reducing the load shedding caused by unpredictable failures in the subsequent stages. Case studies based on IEEE 30-bus and 118-bus systems demonstrate that the proposed method effectively reduces total load shedding throughout extreme events.