Model Predictive Control for Storage Optimization in Stand-Alone PV-Fuel Cell DC Microgrid with Li-ion and Lead-Acid Batteries Storage

The present paper deals with the implementation of Model Predictive Control for optimization of energy storage in the case of a stand-alone photovoltaic-fuel cell DC microgrid equipped with Li-ion and lead-acid batteries. This work begins by broadly introducing the general concept of MPC and its relation to microgrid energy management. Detailed explanations have been provided for problem formulation including the mathematical modeling of system dynamics, operational constraints, and optimization objectives. The proposed MPC framework is validated using two scenarios of simulation: one for a sunny day and the other for a cloudy day. The simulation results show the potential of MPC to handle the change in environmental conditions while maintaining operational constraints, efficient energy storage management, and increasing the overall performance of the microgrid. This work shows the potential of MPC for energy optimization and resilience in renewable energy-based microgrids.