Mitigation of Low Voltage Electrical Network Pollution Using a Two-Level PAPF Controlled by the ANN-PQ Algorithm

The study focuses on enhancing the performance of APFs (the two-level parallel active power filter (PAPF)) by investigating the efficiency of the ANN-PQ algorithm in comparison to the conventional PQ algorithm. The proposed ANN-PQ algorithm leverages the capabilities of artificial neural networks to optimize harmonic cancellation and reactive power compensation, thereby improving power quality. Results of simulation are presented to showcase the effectiveness of the two algorithms in mitigating harmonic distortion, reducing Total Harmonic Distortion (THD), and enhancing current waveform quality. Through a comprehensive analysis of key parameters such as THD reduction, power factor improvement, and load current quality, the study provides a detailed evaluation of the effectiveness of the ANN-PQ algorithm compared to the conventional PQ algorithm.