Disturbance Rejection Based Model Predictive Control for DC-DC Converters in Photovoltaic and Battery Energy Systems of DC-Microgrid

This paper presents a disturbance rejection based model predictive control to regulate the currents of photovoltaic and battery energy systems in a DC-microgrid. The model predictive control is carried out through optimization of a cost function defined on a future horizon. Disturbance rejection is achieved using disturbance estimation to eliminate unknown uncertainties. The proposed disturbance rejection based model predictive control structure is experimentally evaluated using a laboratory setup for DC-microgrid. It is found that the proposed structure enhances the tracking performance compared to the conventional model predictive control.