Operation and capacity configuration of hybrid energy storage power plants participating in electricity markets based on stochastic optimization

To enhance the performance and economic benefits of independent energy storage power stations participating in the electricity market, a hybrid energy storage system (HESS) combining lithium batteries (LiB) and flywheel energy storage (FES) is developed, and a stochastic optimization-based method for operation and capacity configuration of HESS is proposed. First, an operation strategy is established for energy storage participation in the electricity spot market, aiming to maximize the daily net revenue of LiB. In the frequency regulation market, a model predictive control (MPC)-based power allocation strategy for the LiB-FES HESS is proposed to improve the performance in responding to automatic generation control signals. Furthermore, considering the uncertainty of frequency regulation bid winning, a stochastic bid-winning model for power stations is established. A day-ahead bidding strategy based on stochastic optimization is developed to balance daily revenue and risks. Finally, with the goal of maximizing the annualized revenue of the HESS over the project planning horizon, an annualized revenue model covering the entire lifecycle is established. Optimization is achieved through joint iterative optimization of capacity configuration and operation strategies. Case study results show that, compared to the commonly used first-order filtering method, the proposed MPC strategy increases the daily frequency regulation performance index Kp by 15.6% and daily net revenue by 15.9% under fixed energy storage capacity. The stochastic capacity optimization bidding strategy increases the average daily net revenue by 6.8% compared to the fixed capacity approach. Overall, the proposed configuration method enhances the annualized net revenue of the power station by 27.9% compared to conventional engineering methods.