A Multifunctional PV-Based Shunt Active Power Filter Using Neural Network Controller

This paper presents a multifunctional photovoltaic array-based shunt active power filter (PV-SAPF) using a diphase currents neural control strategy. The model aims to supply power to the nonlinear load 24 hours a day either from PV, Grid or combining the both sources according to the solar irradiance. Along with a PV active power injection, the model consists of using PV-SAPF for ancillary services as harmonic currents damping, dc link voltage control and reactive power compensation. In order to achieve a fast, accurate and online extraction of the fundamental component of harmonic currents rejected by nonlinear and online-varying load, a diphase currents neural control method is applied. So that to confirm the efficiency of this latest, the obtained results are compared with those of the classic method using synchronous d-q reference frame strategy. The simulation results depict the performance of the used method adapted to PV-SAPF system with aforementioned functionalities. Furthermore, the total harmonic distortion (THD) is obtained within the limits prescribed by IEEE-519 standard under a widely varying load.