Distributed Optimal Scheduling of Multi-Microgrid System with Hydrogen Based on Model Predictive Control

The integration of multi-microgrid systems (MMGSs) holds promise for enhancing system reliability and optimizing the utilization of renewable energy resources. Additionally, hydrogen energy storage (HES) offers a viable means of mitigating the inherent fluctuations in renewable energy sources. In order to better realize the energy scheduling across microgrids and cope with renewable energy fluctuations, this study introduces a distributed optimal scheduling for multi-microgrid systems with hydrogen based on model predictive control (MPC). Structured as a two-layer optimization framework, the proposed approach entails an upper layer employing distributed rolling optimization modeling to govern inter-microgrid power transmission and coordination. Concurrently, the lower layer implements a feedback correction model at a shorter time scale, enabling each microgrid to autonomously devise equipment output schemes, thereby facilitating microgrid regulation and leveraging hydrogen energy storage to address renewable energy uncertainty. Finally, empirical validation of the proposed scheme, along with the efficacy of hydrogen energy storage, is demonstrated through a project-based evaluation.