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Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios

This paper presents the enhancements performed on the adaptive linear neuron (ADALINE) technique so that it can be applied for active power filtering purposes in a three-phase four-wire system. In the context of active power filtering, the ADALINE technique which was initially developed for a single...

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主要な著者: Hoon, Yap, Mohd Radzi, Mohd Amran, Al-Ogaili, Ali Saadon
フォーマット: 論文
言語:English
出版事項: MDPI 2019
オンライン･アクセス:http://psasir.upm.edu.my/id/eprint/38205/1/38205.pdf
http://psasir.upm.edu.my/id/eprint/38205/
https://www.mdpi.com/2076-3417/9/24/5304
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record_format eprints
spelling my.upm.eprints.382052020-05-04T16:24:00Z http://psasir.upm.edu.my/id/eprint/38205/ Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios Hoon, Yap Mohd Radzi, Mohd Amran Al-Ogaili, Ali Saadon This paper presents the enhancements performed on the adaptive linear neuron (ADALINE) technique so that it can be applied for active power filtering purposes in a three-phase four-wire system. In the context of active power filtering, the ADALINE technique which was initially developed for a single-phase two-wire system has been further expanded to suit three-phase three-wire system. For both systems, ADALINE techniques have been reported to be effective even when the grid voltage is distorted and/or unbalanced. However, further works that study the possibility to apply ADALINE technique in a three-phase four-wire system which invariably carries unbalanced loads, are rather limited. Hence, in this work, a control algorithm (named as enhanced-ADALINE) which combines the strength of highly selective filter (HSF), ADALINE concept and averaging function is proposed, to manage harmonics mitigation by shunt active power filter (SAPF) under non-ideal grid and unbalanced load scenarios. MATLAB-Simulink software is utilized to conduct an exhaustive simulation study which includes circuit connection of SAPF in a three-phase four-wire system, design of control algorithms, and performance assessments. Benchmarking with the existing algorithm is performed to examine the benefits of using the proposed algorithm. From the analysis, simulation findings are presented and thoroughly discussed to verify design concept, capability, and relevance of the proposed algorithm. MDPI 2019 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/38205/1/38205.pdf Hoon, Yap and Mohd Radzi, Mohd Amran and Al-Ogaili, Ali Saadon (2019) Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios. Applied Sciences, 9 (24). art. no. 5304. pp. 1-25. ISSN 2076-3417 https://www.mdpi.com/2076-3417/9/24/5304 10.3390/app9245304
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description This paper presents the enhancements performed on the adaptive linear neuron (ADALINE) technique so that it can be applied for active power filtering purposes in a three-phase four-wire system. In the context of active power filtering, the ADALINE technique which was initially developed for a single-phase two-wire system has been further expanded to suit three-phase three-wire system. For both systems, ADALINE techniques have been reported to be effective even when the grid voltage is distorted and/or unbalanced. However, further works that study the possibility to apply ADALINE technique in a three-phase four-wire system which invariably carries unbalanced loads, are rather limited. Hence, in this work, a control algorithm (named as enhanced-ADALINE) which combines the strength of highly selective filter (HSF), ADALINE concept and averaging function is proposed, to manage harmonics mitigation by shunt active power filter (SAPF) under non-ideal grid and unbalanced load scenarios. MATLAB-Simulink software is utilized to conduct an exhaustive simulation study which includes circuit connection of SAPF in a three-phase four-wire system, design of control algorithms, and performance assessments. Benchmarking with the existing algorithm is performed to examine the benefits of using the proposed algorithm. From the analysis, simulation findings are presented and thoroughly discussed to verify design concept, capability, and relevance of the proposed algorithm.
format Article
author Hoon, Yap
Mohd Radzi, Mohd Amran
Al-Ogaili, Ali Saadon
spellingShingle Hoon, Yap
Mohd Radzi, Mohd Amran
Al-Ogaili, Ali Saadon
Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
author_facet Hoon, Yap
Mohd Radzi, Mohd Amran
Al-Ogaili, Ali Saadon
author_sort Hoon, Yap
title Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
title_short Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
title_full Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
title_fullStr Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
title_full_unstemmed Adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
title_sort adaptive linear neural network approach for three-phase four-wire active power filtering under non-ideal grid and unbalanced load scenarios
publisher MDPI
publishDate 2019
url http://psasir.upm.edu.my/id/eprint/38205/1/38205.pdf
http://psasir.upm.edu.my/id/eprint/38205/
https://www.mdpi.com/2076-3417/9/24/5304
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score 13.251813

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