台风条件下含大规模海上风电的电力系统调度策略：一种两阶段样本鲁棒优化方法

Typhoons, as extreme weather events, pose significant threats to the safe and stable operation of power systems, especially those integrating large offshore wind farms. The impact on power systems during typhoons is often severe and unpredictable. Given the challenges in accessing wind power generation data under typhoon conditions, this paper utilizes the barometric pressure and wind field models of typhoons, integrated with Monte Carlo simulation, to generate real-time wind power data samples. Subsequently, a two-stage Sample Robust Optimization (SRO) model is employed to address the unit commitment (UC) problem in power systems with substantial offshore wind power integration. This model combines the two-stage Sample Average Approximation (SAA) with robust optimization principles, ensuring both asymptotic optimality and strong out-of-sample performance. To manage non-anticipativity in decision-making, an implicit decision rule guides thermal power output, significantly reducing conservatism compared to linear decision rules. Furthermore, practical strategies are implemented to enhance computational efficiency, facilitating application to larger-scale power systems. Simulation results confirm the effectiveness of the proposed model and method.