Active power filter for three-phase four-wire electric systems using neural networks

This paper presents the design of neural networks compared with the conventional technique, a hysteresis controller for active power filter for three-phase four-wire electric system. A particular three-layer neural network structure is studied in some detail. Simulation and experimental results of t...

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Main Authors: Madtharad C., Premrudeepreechacharn S.
Format: Article
Language:English
Published: 2014
Online Access:http://www.scopus.com/inward/record.url?eid=2-s2.0-0037185414&partnerID=40&md5=e52030dc3ef8b10bd4d5fa423b6b250c
http://cmuir.cmu.ac.th/handle/6653943832/1415
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Institution: Chiang Mai University
Language: English
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spelling th-cmuir.6653943832-14152014-08-29T09:29:16Z Active power filter for three-phase four-wire electric systems using neural networks Madtharad C. Premrudeepreechacharn S. This paper presents the design of neural networks compared with the conventional technique, a hysteresis controller for active power filter for three-phase four-wire electric system. A particular three-layer neural network structure is studied in some detail. Simulation and experimental results of the active power filter with both controllers are also presented to verify the feasibility of such controller. The simulation and experimental result show that both controller techniques can reduce harmonics in three-phase four-wire electric systems drawn by nonlinear loads and can reduce neutral current. The advantage of the neural network controller technique over hysteresis controller technique are less voltage ripple of d.c. bus, and less switching loss. Furthermore, the neural networks controller has better fault tolerance than the hysteresis controller. © 2002 Elsevier Science B.V. All rights reserved. 2014-08-29T09:29:16Z 2014-08-29T09:29:16Z 2002 Article 03787796 10.1016/S0378-7796(01)00185-7 EPSRD http://www.scopus.com/inward/record.url?eid=2-s2.0-0037185414&partnerID=40&md5=e52030dc3ef8b10bd4d5fa423b6b250c http://cmuir.cmu.ac.th/handle/6653943832/1415 English
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
language English
description This paper presents the design of neural networks compared with the conventional technique, a hysteresis controller for active power filter for three-phase four-wire electric system. A particular three-layer neural network structure is studied in some detail. Simulation and experimental results of the active power filter with both controllers are also presented to verify the feasibility of such controller. The simulation and experimental result show that both controller techniques can reduce harmonics in three-phase four-wire electric systems drawn by nonlinear loads and can reduce neutral current. The advantage of the neural network controller technique over hysteresis controller technique are less voltage ripple of d.c. bus, and less switching loss. Furthermore, the neural networks controller has better fault tolerance than the hysteresis controller. © 2002 Elsevier Science B.V. All rights reserved.
format Article
author Madtharad C.
Premrudeepreechacharn S.
spellingShingle Madtharad C.
Premrudeepreechacharn S.
Active power filter for three-phase four-wire electric systems using neural networks
author_facet Madtharad C.
Premrudeepreechacharn S.
author_sort Madtharad C.
title Active power filter for three-phase four-wire electric systems using neural networks
title_short Active power filter for three-phase four-wire electric systems using neural networks
title_full Active power filter for three-phase four-wire electric systems using neural networks
title_fullStr Active power filter for three-phase four-wire electric systems using neural networks
title_full_unstemmed Active power filter for three-phase four-wire electric systems using neural networks
title_sort active power filter for three-phase four-wire electric systems using neural networks
publishDate 2014
url http://www.scopus.com/inward/record.url?eid=2-s2.0-0037185414&partnerID=40&md5=e52030dc3ef8b10bd4d5fa423b6b250c
http://cmuir.cmu.ac.th/handle/6653943832/1415
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