Two-layer energy management strategy for renewable power-to-gas system-based microgrids

This study proposes a two-layer energy management system for the power-to-gas system-based microgrid. One layer is a supervisory control based on fuzzy logic, which optimally distributes the power among different system components, such as fuel cells and an electrolyzer. The second layer consists of power converters, such as direct current (DC)-DC converters and inverters, which generate power in accordance with the supervisory layer. The main contribution of the present study is to investigate the dynamic performance of the coordinated control between two layers by the proposed control strategy. The proposed controller is validated by hardware-in-theloop experiments. Results show that the proposed controller is effective in stabilizing the DC bus voltage and ensuring power balance in the microgrid by optimally distributing the power among the fuel cells, electrolyzer, and grid. A comparative analysis between the proposed EMS and other benchmark strategies is also performed. The proposed strategy is found to handle power transients for electrolyzer and fuel cell components better than the rule-based strategy. However, the proposed strategy provides similar performance as compared to model predictive control.