Active and reactive power neurocontroller for grid-connected photovoltaic generation system

Abstract

Many researchers have contributed to the development of a firm foundation for analysis and design of control applications in grid-connected renewable energy sources. This paper presents an intelligent control algorithm fond on artificial neural networks for active and reactive power controller in grid-connected photovoltaic generation system. The system is devices into two parts in which each part contains an inverter with control algorithm. A DC/DC converter in output voltage established by control magnitude besides maximum power point tracker algorithm always finds optimal power of the PV array in use. A DC/AC hysteresis inverter designed can synchronize a sinusoidal current output with the grid voltage and accurate an independent active and reactive power control. Simulation results confirm the validation of the purpose. Neurocontroller based active and reactive power presents an efficiency control that guarantees good response to the steps changing in active and reactive power with an acceptable current/voltage synchronism. In this paper the power circuit and the control system of the presented grid-connected photovoltaic generation system is simulated and tested by MatLab/Simulink.