Particle Swarm Optimization Trained Artificial Neural Network to Control Shunt Active Power Filter Based on Multilevel Flying Capacitor Inverter

Khaled Djerboub, Tayeb Allaoui, Gerard Champenois, Mouloud Denai, Chaib Habib

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
33 Downloads (Pure)

Abstract

Shunt Active Power Filters (SAPF) are an emerging power electronics-based technology to mitigate harmonic and improve power quality in distribution grids. The SAPF proposed in this paper is based on three-phase Flying Capacitor Inverter (FCI) with a three-cell per phase topology, which has the advantage to provide voltage stress distribution on the switches. However, controlling the voltage of floating capacitors is a challenging problem for this type of topology. In this paper, a controller based artificial neural networks optimized with particle swarm optimization (ANN-PSO) is proposed to regulate the filter currents to follow the references extracted by the method of synchronous reference frame (SRF). The simulation results showed an enhancement of the power quality with a significant reduction in the THD levels of the current source under various loading conditions, which confirms the effectiveness, and robustness of the proposed control scheme and SAPF topology.
Original languageEnglish
Pages (from-to)199-207
Number of pages9
JournalEuropean Journal of Electrical Engineering (EJEE)
Volume22
Issue number3
DOIs
Publication statusPublished - 30 Jun 2020

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