dc.contributor.author | Djerboub, Khaled | |
dc.contributor.author | Allaoui, Tayeb | |
dc.contributor.author | Champenois, Gerard | |
dc.contributor.author | Denai, Mouloud | |
dc.contributor.author | Habib, Chaib | |
dc.date.accessioned | 2020-07-18T00:07:39Z | |
dc.date.available | 2020-07-18T00:07:39Z | |
dc.date.issued | 2020-06-30 | |
dc.identifier.citation | Djerboub , K , Allaoui , T , Champenois , G , Denai , M & Habib , C 2020 , ' Particle Swarm Optimization Trained Artificial Neural Network to Control Shunt Active Power Filter Based on Multilevel Flying Capacitor Inverter ' , European Journal of Electrical Engineering (EJEE) , vol. 22 , no. 3 , pp. 199-207 . https://doi.org/10.18280/ejee.220301 | |
dc.identifier.other | PURE: 22336836 | |
dc.identifier.other | PURE UUID: 6e2243c6-c999-4a83-bbb1-22165ec33c84 | |
dc.identifier.other | Scopus: 85088090960 | |
dc.identifier.uri | http://hdl.handle.net/2299/22968 | |
dc.description | © 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/). | |
dc.description.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. | en |
dc.format.extent | 9 | |
dc.language.iso | eng | |
dc.relation.ispartof | European Journal of Electrical Engineering (EJEE) | |
dc.title | Particle Swarm Optimization Trained Artificial Neural Network to Control Shunt Active Power Filter Based on Multilevel Flying Capacitor Inverter | en |
dc.contributor.institution | Centre for Engineering Research | |
dc.contributor.institution | Communications and Intelligent Systems | |
dc.contributor.institution | School of Physics, Engineering & Computer Science | |
dc.contributor.institution | Department of Engineering and Technology | |
dc.description.status | Peer reviewed | |
rioxxterms.version | VoR | |
rioxxterms.versionofrecord | https://doi.org/10.18280/ejee.220301 | |
rioxxterms.type | Journal Article/Review | |
herts.preservation.rarelyaccessed | true | |