Evaluation of neural network based real time maximum power tracking controller for PV system

This paper presents a neural network based maximum power tracking controller for interconnected PV power systems. The neural network is utilized to identify the optimal operating voltage of the PV power system. The controller generates the control signal in real-time, and the control signal is fed back to the voltage control loop of the inverter to shift the terminal voltage of the PV power system to its identified optimum, which yields maximum power generation. The controller is of the PI type. The proportional and the integral gains are set to their optimal values to achieve fast response and also to prevent overshoot and also undershoot. Continuous measurement is required for the open circuit voltage on the monitoring cell, and also for the terminal voltage of the PV power system. Because of the accurate identification of the optimal operating voltage of the PV power system, more than 99% power is drawn from the actual maximum power