Two-Layer Model Predictive Control of Energy Management Strategy for Hybrid Energy Storage Systems

Power fluctuations and scheduling uncertainties caused by large-scale renewable energy grid integration have made the existing homogeneous energy storage solutions struggle in some cases to balance economic efficiency with dynamic response speed. To address the above challenge, this paper proposes a hybrid energy storage system integrating superconducting magnetic energy storage and hydrogen electric storage, and a corresponding dual-layer model predictive control energy management framework is therefore designed. This framework lies on its cross-timescale hierarchical coordination mechanism. Analytic validation in a typical high-fluctuation renewable microgrid scenario demonstrates that compared to conventional single-layer control strategies, the proposed management system reduced total operating costs by 55.5%, extended system stabilization time by 64.2%, decreased hydrogen storage system mode switching frequency by 59.9%, and simultaneously lowered computational burden by over 97%. This effectively enhanced power supply reliability and extended equipment service life. This innovative framework provides a practical solution for coordinated energy storage control in microgrids having a high ratio of renewable penetration.