Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System
Autor(a) principal: | |
---|---|
Data de Publicação: | 2010 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TLA.2010.5453948 http://hdl.handle.net/11449/8935 |
Resumo: | In this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform. |
id |
UNSP_398390fd3642648ca2a82d03cadeeaf6 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/8935 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase SystemHarmonicspower systemartificial neural networksIn this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform.UFABC, Ctr Engn, St Andre, SP, BrazilUSP, Dept Engn Eletr, São Carlos, SP, BrazilUTFPR CP, Dept Electrotecn, Cornelio Procopio, PR, BrazilUNESP FEB, Dept Engn Eletr, Bauru, SP, BrazilUNESP FEB, Dept Engn Eletr, Bauru, SP, BrazilInstitute of Electrical and Electronics Engineers (IEEE)Universidade Federal do ABC (UFABC)Universidade de São Paulo (USP)UTFPR CPUniversidade Estadual Paulista (Unesp)Nascimento, C. F.Oliveira, A. A.Goedtel, A.Silva, I. N.Serni, P. J. A. [UNESP]2014-05-20T13:27:18Z2014-05-20T13:27:18Z2010-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article65-73application/pdfhttp://dx.doi.org/10.1109/TLA.2010.5453948IEEE Latin America Transactions. Piscataway: IEEE-Inst Electrical Electronics Engineers Inc, v. 8, n. 1, p. 65-73, 2010.1548-0992http://hdl.handle.net/11449/893510.1109/TLA.2010.5453948WOS:000277053200010WOS000277053200010.pdf48317899018238490000-0002-9984-9949Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporIEEE Latin America Transactions0.5020,253info:eu-repo/semantics/openAccess2024-06-28T13:34:25Zoai:repositorio.unesp.br:11449/8935Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:48:27.344246Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System |
title |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System |
spellingShingle |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System Nascimento, C. F. Harmonics power system artificial neural networks |
title_short |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System |
title_full |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System |
title_fullStr |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System |
title_full_unstemmed |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System |
title_sort |
Neural Network-Based Approach for Identification of the Harmonic Content of a Nonlinear Load in a Single-Phase System |
author |
Nascimento, C. F. |
author_facet |
Nascimento, C. F. Oliveira, A. A. Goedtel, A. Silva, I. N. Serni, P. J. A. [UNESP] |
author_role |
author |
author2 |
Oliveira, A. A. Goedtel, A. Silva, I. N. Serni, P. J. A. [UNESP] |
author2_role |
author author author author |
dc.contributor.none.fl_str_mv |
Universidade Federal do ABC (UFABC) Universidade de São Paulo (USP) UTFPR CP Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Nascimento, C. F. Oliveira, A. A. Goedtel, A. Silva, I. N. Serni, P. J. A. [UNESP] |
dc.subject.por.fl_str_mv |
Harmonics power system artificial neural networks |
topic |
Harmonics power system artificial neural networks |
description |
In this paper an alternative method based on artificial neural networks is presented to determine harmonic components in the load current of a single-phase electric power system with nonlinear loads, whose parameters can vary so much in reason of the loads characteristic behaviors as because of the human intervention. The first six components in the load current are determined using the information contained in the time-varying waveforms. The effectiveness of this method is verified by using it in a single-phase active power filter with selective compensation of the current drained by an AC controller. The proposed method is compared with the fast Fourier transform. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-03-01 2014-05-20T13:27:18Z 2014-05-20T13:27:18Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/TLA.2010.5453948 IEEE Latin America Transactions. Piscataway: IEEE-Inst Electrical Electronics Engineers Inc, v. 8, n. 1, p. 65-73, 2010. 1548-0992 http://hdl.handle.net/11449/8935 10.1109/TLA.2010.5453948 WOS:000277053200010 WOS000277053200010.pdf 4831789901823849 0000-0002-9984-9949 |
url |
http://dx.doi.org/10.1109/TLA.2010.5453948 http://hdl.handle.net/11449/8935 |
identifier_str_mv |
IEEE Latin America Transactions. Piscataway: IEEE-Inst Electrical Electronics Engineers Inc, v. 8, n. 1, p. 65-73, 2010. 1548-0992 10.1109/TLA.2010.5453948 WOS:000277053200010 WOS000277053200010.pdf 4831789901823849 0000-0002-9984-9949 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
IEEE Latin America Transactions 0.502 0,253 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
65-73 application/pdf |
dc.publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers (IEEE) |
publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers (IEEE) |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129553461149696 |