TY - JOUR
T1 - Particle Swarm Optimization Trained Artificial Neural Network to Control Shunt Active Power Filter Based on Multilevel Flying Capacitor Inverter
AU - Djerboub, Khaled
AU - Allaoui, Tayeb
AU - Champenois, Gerard
AU - Denai, Mouloud
AU - Habib, Chaib
N1 - © 2020 by the authors; licensee IIETA, Edmonton, Canada. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/).
PY - 2020/6/30
Y1 - 2020/6/30
N2 - 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.
AB - 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.
U2 - 10.18280/ejee.220301
DO - 10.18280/ejee.220301
M3 - Article
VL - 22
SP - 199
EP - 207
JO - European Journal of Electrical Engineering
JF - European Journal of Electrical Engineering
IS - 3
ER -