Power management using model predictive control in a hydrogen-based microgrid

Due to the intermittent feature of renewable energies, microgrids usually require additional energy sources to operate when the stored energy or the renewable energy supply is scarce or are not present. Then, hybrid systems obtained by combining several sources and means of storage can be used. In order to draw the best performance of such systems, a proper energy management is essential. A key factor is to try to adapt the energy production to the demand, where Model Predictive Control (MPC) and supervision techniques can play an important role. The problem is more interesting when several possibilities for using the produced energy exist, and it is necessary to select how the energy is distributed among subsystems. Hence different objectives can arise (minimizing the use of conventional energy sources, energy saving, economic and quality aspects...). In this paper a supervisory MPC for optimal power management and control in a hydrogen-based Micro-Grid (MG) is designed. The system operation under appropriate constraints is also taken into account in the problem formulation. Simulations are carried out over experimentally validated models to demonstrate the goodness of the controller.