A Fast Predictive Reference Current Generation Algorithm for Shunt APF in DER Integrated Network

Abstract

In order to improve the compensating capabilities of shunt active power filters (APF) coupled with renewable energy integrated microgrid network, this research offers a Recursive Least Square Bacterial Foraging Optimization (RLSBFO) based estimation approach for the reference current generation. The suggested approach can improve the compensation of current harmonics in a selective/collective (global) manner. Furthermore, the RLS-BFO-based reference generation approach eliminates the necessity for a PLL based synchronization circuit, which helps to reduce computation latency. The instantaneous active and reactive power theory (PQ theory) and the Kalman filter-based estimation approach are also implemented and compared to assess the suggested controller's effectiveness. The MATLAB based simulation results, followed by the quantitative analysis demonstrate the efficacy of the estimation algorithm.