Power Quality Enhancement of Grid-Connected Solar Photovoltaic System using ANN based Filter

Abstract

Grid-connected photovoltaic (PV) systems are increasingly attracting the attention of industry and academia as a means of providing an alternative to conventional fossil-fuel generation and pollution-free power. This project aims to improve the power quality level of a grid-tied PV distribution system using shunt active power filter (APF) along with adaptive current control technique. In this work Artificial Neural Network controller used to destroy the voltage and current harmonics in a grid-tied PV system. A reference current generation strategy is implemented to mitigate the current harmonics by extracting the fundamental constituents (FCs) from the nonlinear load currents. MCCF is employed to separate the FC from the distorted grid voltages and eliminates the voltage harmonics during extremely polluted grid voltage condition. The comparative analysis is analyzed to check the effectiveness of the proposed hybrid control scheme with existing and adaptive control techniques in respect of power quality, better dc offset rejection, better FC and frequency extraction, and grid synchronization.