Rolling Optimization Model for Coordinating with Multi-Type Reserve Resources in Power Systems Considering Multiple Uncertainties

With the increasing integration of renewable energy sources such as wind power, power systems are facing multiple uncertainties, posing challenges to the secure and reliable operation of the power systems. Therefore, it is essential to set reserve capacity to address these uncertainties. This paper proposes a rolling optimization model for coordinating with multitype reserve resources in power systems considering multiple uncertainties. By leveraging the progressive enhancement in prediction accuracy for wind power and load from day-ahead to intra-day and then to real-time, the proposed model enables reserve resources across multi-time scales to participate in multilevel reserve optimization. The model categorizes generation-side reserve resources according to different time scales to minimize the total cost of the power system, while incorporating reserve capacity constraints and reserve invoking constraints as the constraints. Finally, a case study based on a certain power system is conducted which enables more rational dispatching of generation-side reserve resources. The results demonstrate that the proposed model more effectively characterizes the impact of multiple uncertainties and multi-time scales on the reserve capacity invocation of the power system compared to traditional method.