Optimization Method of Energy Storage Power Station Capacity Configuration Based on Electricity Spot Joint Market Revenue

To enhance the investment recovery and operational efficiency of energy storage power station (ESPS), stimulate potential investment interest in energy storage, and facilitate the integration of new energy sources and the development of the electricity spot market, this paper proposes an optimal capacity configuration model for ESPS participating in the operation of the electricity spot joint market as an independent market entity. Initially, considering the investment and maintenance costs of energy storage, along with operational revenues influenced by the variability of new energy sources output, a capacity planning model framework for ESPS is established, optimizing for the minimal annual operational costs within the planning cycle. Subsequently, to maximize the operational revenue of ESPS, a master-slave game method is employed, with the energy storage operator and the power system dispatch center acting as the leader and follower, respectively, to construct a bidding model for ESPS participating in the day-ahead energy and frequency regulation joint market operation. Finally, the Karush-Kuhn-Tucker (KKT) conditions are utilized to transform the master-slave game bidding model into a single-layer model, forming a two-layer planning model for the capacity configuration of ESPS, which is then solved using a particle swarm optimization algorithm nested with CPLEX. Simulation results demonstrate that the proposed method effectively enhances the market competitiveness and economic viability of ESPS.