Shunt active power filter: Current status of control techniques and its integration to renewable energy sources

Abstract

The renewable energy sources (RESs) are a viable alternative to fulfill the ever-rising energy demand. The present power distribution system contains nonlinear loads that bring up power quality issues like harmonics in source current, voltage sag and swell etc. This paper provides exhaustive review of control techniques of shunt active power filter (SAPF), maximum power point tracking (MPPT) and RES integrated with SAPF. Artificial neural network (ANN) based control system is designed to improve SAPF performance in terms of total harmonic distortion. The training data generated from conventional PI and perturb & observe (P&O) technique is used to train ANN based controller for SAPF and MPPT respectively. The photovoltaic (PV) integrated SAPF is simulated in MATLAB and then validated in real-time with microsecond time step on field-programmable gate array (FPGA) based computational engine of OPAL-RT 4510.