Real-time implementation of improved predictive model control for standalone power generation system based PV renewable energy

In this study, improved predictive model control (PMC) strategy with prediction horizon of one sampling time for standalone solar photovoltaic (PV) system is discussed. Two control strategies based on the improved PMC approach are designed and implemented to ensure a fast and accurate stability of the system. Enhanced PMC-based maximum power point tracking is developed and implemented to extract maximum power and achieve high performance from solar PV under the presence of severe conditions by estimating the equivalent system resistance and output PV voltage. Furthermore, to achieve high performance without saturation issue, adaptive proportional-integral controller with anti-windup is employed. In addition, modelling as well as the parameters design method are offered. An efficient dc-dc boost converter is employed. To regulate the output ac voltage and frequency, as well as, supply a clean power to the connected load, improved PMC controller is developed and implemented. To predict the attitude of the output ac voltage at each sampling prediction interval for all possible switching states, the cost function is defined and evaluated as a standard to select the position function of the switches. The performances of the proposed system and their enhanced control strategies are verified using MATLAB/Simulink, and validated in real time using laboratory prototype.