Multi-Time Scale Integration of Robust Optimization with MPC for Islanded Hydrogen-Based Microgrid

Multiple uncertainties bring great challenges to optimal dispatch of islanded hydrogen-based microgrid. In this paper, a multi-time scale optimal scheduling strategy integrated with robust optimization and model predictive control (MPC) is proposed. The optimal scheduling strategy is divided into two layers, daily optimization layer and intraday management layer. Based on the uncertainty of PV and load, a two-stage robust optimization model with a time scale of 15 minutes is established in the daily optimization layer. The MPC is adopted to optimize and allocate output/input power among battery, fuel cell and electrolyzer coordinately. Thus, the large consumption of renewable energy resources (RESs) can be realized. The time scale of intraday management layer is defined as 5 minutes. The minimum operating cost and robust operating plan of studied system under the worst scenario are obtained through the robust optimization in daily optimization layer, and the tracking control of system device level is realized through MPC in intraday management layer. Finally, a typical summer simulation test of islanded hydrogenbased microgrid is used to verify the effectiveness and rationality of proposed optimal scheduling method. Results show that the proposed method give a dispatch scheduling, which can guarantee the normal operation of system in all possible scenarios and minimize the operation cost. Meanwhile, it can deal with the fluctuation of uncertain variables in a short time scale, and ensure the safe and stable operation in actual operation.