Maximum Power Point Tracking Based Model Predictive Control and Extended Kalman Filter Using Single Voltage Sensor for PV Systems

The variability of photovoltaic (PV) energy because of atmospheric conditions dependency necessitates employing a maximum power point tracking (MPPT) technique in the installed PV systems. So in this paper, finite control set model predictive control (FCS-MPC) is used to extract the maximum power from the PV source using a boost converter as interfacing circuit. The proposed technique combines FCS-MPC with an extended Kalman filter (EKF) to reduce the number of required sensors. The EKF is used to estimate both of the PV current and the capacitor voltage. This eliminates two sensors circuits from the PV system, which decreases the system cost. The proposed technique is validated by simulation results under different operating conditions.     «

The variability of photovoltaic (PV) energy because of atmospheric conditions dependency necessitates employing a maximum power point tracking (MPPT) technique in the installed PV systems. So in this paper, finite control set model predictive control (FCS-MPC) is used to extract the maximum power from the PV source using a boost converter as interfacing circuit. The proposed technique combines FCS-MPC with an extended Kalman filter (EKF) to reduce the number of required sensors. The EKF is used...     »