Real-time implementation of adaptive PV-integrated SAPF to enhance power quality

Abstract

This paper presents the design and implementation of a photovoltaic-integrated shunt active power filter (SAPF) to improve the power quality and to generate clean power. The system uses adaptive neuro-fuzzy inference system (ANFIS)-based maximum power point tracking and control of synchronous reference frame theory–based SAPF. Various control schemes are implemented in MATLAB and then validated in real-time using FPGA-based computation engine of OPAL-RT 4510. Control techniques built around the artificial neural network, fuzzy logic control, and ANFIS are compared for balanced and unbalanced loads on parameters like total losses with/without compensation, voltage drop, power factor, and total harmonic distortion.