Optimal Capacity of Wind Thermal Pumped-Storage Baling Transmission System

Wind and thermal power baling transmission is an important way for the consumption of renewable energy, and determining their capacity ratio has become a challenging problem. Pumped storage provides flexible regulation, which can mitigate the impact of uncertainty in renewable energy output. This paper first establishes a pumped storage power station model and proposes a two-layer capacity optimization model for the baling transmission system of wind, thermal, and storage. The upper layer aims to minimize the total system cost, while the lower layer targets the minimum cost of typical daily dispatch. The impact of uncertainty in renewable energy output on the system's reserve capacity is addressed using opportunity constraints. By employing sequence operations, the probabilistic opportunity constraints are converted into deterministic constraints, transforming the problem into a mixed-integer linear programming problem that is easier to solve. The case study results indicate that configuring energy storage can effectively reduce system costs. Simultaneously optimizing the capacity of wind, thermal, and storage power sources can reduce daily operating costs, thereby lowering total costs, validating the effectiveness of the model.