Optimization of Bidirectional Energy Flow Control in a Microgrid based on a Finite Control Set Pedictive Control Model

Abstract

Electrical power storage systems are critical components for ensuring the stability and efficiency of microgrids, especially in renewable energy integration scenarios. This study proposes a significant advance in the control of bidirectional energy flows by introducing a finite control set predictive model (FCS-MPC) for the management of battery charging and discharging in a microgrid fed by a photovoltaic source. Photovoltaic production is optimized using an MPPT algorithm based on the Incremental Conductance Method (INC), guaranteeing maximum extraction of available power. Unlike conventional PI controllers, the proposed FCS-MPC offers faster dynamic response, greater accuracy and improved stability, while maintaining a continuous, reliable supply for a 1 kW DC system. Simulations carried out in Matlab/Simulink not only confirm the FCS-MPC’s superior performance, but also demonstrate its ability to reduce oscillations and improve overall system efficiency. These results position the FCS-MPC as a promising solution for advanced microgrid control, paving the way for practical applications in complex energy environments.