A two-stage optimal pre-scheduling strategy for power system inertia assessment and replenishment under extreme weather events

Abstract

This paper addresses the challenges posed by reduced power system inertia due to the large-scale renewable energy integration and the threats from frequent extreme weather events. It proposes a strategy to enhance power system resilience by incorporating inertia participation during such events. The strategy derives critical inertia demand formulas based on two key factors under extreme weather, establishing a linearized inertia assessment model. Additionally, considering the vulnerability of power lines to extreme weather events, we propose the Resilience Reserve Factor (RRF). It employs three resilience evaluation indexes to delineate the system's demand for inertia supply, efficiently targeting vulnerable areas for inertia reinforcement, thereby comprehensively enhancing the resilience of the power grid. Lastly, based on the critical inertia demand constraint criterion, we establish a two-stage pre-scheduling strategy incorporating both day-ahead planning and real-time correction while considering assessment accuracy. This approach transforms the inertia assessment problem into a resilience optimization problem, yielding the scheduling status of each generator unit and inertia replenishment results during extreme weather after iteration. The optimized strategy is validated through simulations on the improved IEEE39 buses system. Furthermore, this study employs a frequency response model to investigate the spatial distribution characteristics of inertia. The results indicate that this optimization strategy enables efficient scheduling of resources before and after extreme weather events. In addition to improving the economic performance of the power system, it significantly enhances system resilience by reinforcing both global and localized support during critical disaster resistance phases.