A Two-Stage Optimization Model for Mixed Energy Storage Allocation

This paper presents a two-stage optimization model for the configuration of mixed energy storage systems, integrating energy-type and power-type storage technologies. In the first stage, Empirical Mode Decomposition (EMD) is applied to decompose the power output profile of renewable energy stations into high-frequency and low-frequency components based on a critical frequency. The high-frequency component is allocated to flywheel energy storage for its rapid response capability, while the low-frequency component is managed by battery energy storage due to its high energy density. The EMD results are then used as energy upper-bound constraints in the second stage, which focuses on optimizing the economic configuration of the mixed energy storage system. The second-stage model minimizes the overall system cost while ensuring operational feasibility and reliability. By combining EMD-based energy allocation with an economic optimization framework, this approach provides a systematic and robust methodology for designing cost-effective and technically efficient mixed energy storage systems. Case studies validate the proposed model, demonstrating its effectiveness in achieving both technical and economic objectives. This work contributes to advancing energy storage planning and offers practical insights for deploying hybrid energy storage solutions in modern power systems.