EVALUATION OF NEURAL-NETWORK-BASED REAL-TIME MAXIMUM POWER TRACKING CONTROLLER FOR PV SYSTEM

This paper presents a neural network based maximum power tracking cont roller for interconnected PV systems to commercial power sources. The neural network is utilized to identify the optimal operating voltage o f the PV system. The controller generates the control signal in real t ime, and the control signal is fed back to the voltage control loop of the inverter to shift the terminal voltage of the PV system to the id entified optimal one, which yields the maximum power generation. The c ontroller is a PI type one. The proportional and the integral gains ar e see to their optimal values to achieve the fast response and also to prevent the overshoot and also the undershoot. The continuous measure ment is required for the open circuit voltage on the monitoring cell, and also for the terminal voltage of the PV system. Because of the acc urate identification of the optimal operating voltage of the PV system , more than 99% power is drawn from the actual maximum power.