Two-Stage Coordinated Optimization Scheduling of Power Systems Considering Conditional Value-at-Risk under Major Weather Events

With the increasing penetration of renewable energy in modern power systems, major weather events can easily trigger significant fluctuations in both renewable energy generation and electricity demand. Traditional dispatching models are inadequate in effectively coordinating flexible resources and managing system risks, posing dual challenges: ensuring both power supply security and facilitating the integration of renewable energy. This study aims to realize coordinated and optimized multi-timescale scheduling of flexible resources to address the challenges posed by complex and dynamic operating environments. To this end, we propose an innovative event-driven, multi-timescale dispatch model for flexible resource coordination and optimization, which enables real-time awareness and rapid response to extreme weather events, thereby enhancing the system's adaptability to sudden disturbances. Furthermore, considering variations in electricity demand and the volatility of renewable energy under different weather conditions, a two-stage (day-ahead and intra-day) scheduling strategy for flexible resources is optimized to ensure efficient and reliable system operation across both routine and major weather events. The effectiveness of the proposed method is validated using real-world data from a provincial-level power grid in China. The results demonstrate that the event-driven dispatch strategy enables dynamic response to major weather events, majorly enhancing system robustness and risk mitigation capabilities.