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Analysis and NN-based control of doubly fed induction generator in wind power generation

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Resumo:With the increasing size of wind power generation it is required to perform power system stability analysis that uses dynamic wind generator models. In this paper are presented all the wind power system components, including the turbine, the generator, the power electronic converter and controllers. The aim is to study the Doubly Fed Induction Generator (DFIG) operation and its connection to the power system, either during normal operation or during transient grid fault events. Two different control system design technologies are present, the first is performed by standard PI controllers and the second is based on artificial neural networks
Autores principais:Soares, Orlando
Outros Autores:Gonçalves, Henrique; Martins, António A.; Carvalho, Adriano
Assunto:Wind power generation, Simulation Control Neural networks Doubly fed induction generator
Ano:2009
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
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author Soares, Orlando
author2 Gonçalves, Henrique
Martins, António A.
Carvalho, Adriano
author2_role author
author
author
author_facet Soares, Orlando
Gonçalves, Henrique
Martins, António A.
Carvalho, Adriano
author_role author
contributor_name_str_mv Biblioteca Digital do IPB
country_str PT
creators_json_txt [{\"Person.name\":\"Soares, Orlando\",\"Person.identifier.orcid\":\"0000-0002-7731-5102\"},{\"Person.name\":\"Gonçalves, Henrique\"},{\"Person.name\":\"Martins, António A.\"},{\"Person.name\":\"Carvalho, Adriano\"}]
datacite.contributors.contributor.contributorName.fl_str_mv Biblioteca Digital do IPB
datacite.creators.creator.creatorName.fl_str_mv Soares, Orlando
Gonçalves, Henrique
Martins, António A.
Carvalho, Adriano
datacite.date.Accepted.fl_str_mv 2009-01-01T00:00:00Z
datacite.date.available.fl_str_mv 2012-09-10T12:28:53Z
datacite.date.embargoed.fl_str_mv 2012-09-10T12:28:53Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Wind power generation,
Simulation
Control
Neural networks
Doubly fed induction generator
datacite.titles.title.fl_str_mv Analysis and NN-based control of doubly fed induction generator in wind power generation
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.creator.none.fl_str_mv Soares, Orlando
Gonçalves, Henrique
Martins, António A.
Carvalho, Adriano
dc.date.Accepted.fl_str_mv 2009-01-01T00:00:00Z
dc.date.available.fl_str_mv 2012-09-10T12:28:53Z
dc.date.embargoed.fl_str_mv 2012-09-10T12:28:53Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv http://hdl.handle.net/10198/7488
dc.language.none.fl_str_mv eng
dc.publisher.none.fl_str_mv Renewable Energy & Power Quality Journal
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Wind power generation,
Simulation
Control
Neural networks
Doubly fed induction generator
dc.title.fl_str_mv Analysis and NN-based control of doubly fed induction generator in wind power generation
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
description With the increasing size of wind power generation it is required to perform power system stability analysis that uses dynamic wind generator models. In this paper are presented all the wind power system components, including the turbine, the generator, the power electronic converter and controllers. The aim is to study the Doubly Fed Induction Generator (DFIG) operation and its connection to the power system, either during normal operation or during transient grid fault events. Two different control system design technologies are present, the first is performed by standard PI controllers and the second is based on artificial neural networks
dirty 0
eu_rights_str_mv openAccess
format article
fulltext.url.fl_str_mv https://bibliotecadigital.ipb.pt/bitstreams/9085bfed-0412-4112-8b2a-26ac037f4e38/download
id ipb_dd4fe89b0fa8d28496e4b0f5a570798e
identifier.url.fl_str_mv http://hdl.handle.net/10198/7488
instacron_str ipb
institution Instituto Politécnico de Bragança
instname_str Instituto Politécnico de Bragança
language eng
network_acronym_str ipb
network_name_str Biblioteca Digital do IPB
oai_identifier_str oai:bibliotecadigital.ipb.pt:10198/7488
organization_str_mv urn:organizationAcronym:ipb
person_str_mv Soares, Orlando
Soares, Orlando
https://www.ciencia-id.pt/6B1D-E906-C118
6B1D-E906-C118
http://orcid.org/0000-0002-7731-5102
0000-0002-7731-5102
Gonçalves, Henrique
Martins, António A.
Carvalho, Adriano
publishDate 2009
publisher.none.fl_str_mv Renewable Energy & Power Quality Journal
reponame_str Biblioteca Digital do IPB
repository_id_str urn:repositoryAcronym:ipb
service_str_mv urn:repositoryAcronym:ipb
spelling engRenewable Energy & Power Quality JournalporWith the increasing size of wind power generation it is required to perform power system stability analysis that uses dynamic wind generator models. In this paper are presented all the wind power system components, including the turbine, the generator, the power electronic converter and controllers. The aim is to study the Doubly Fed Induction Generator (DFIG) operation and its connection to the power system, either during normal operation or during transient grid fault events. Two different control system design technologies are present, the first is performed by standard PI controllers and the second is based on artificial neural networksapplication/pdfporAnalysis and NN-based control of doubly fed induction generator in wind power generationPersonalSoares, OrlandoDSpacehttp://dspace.org/items/615c6198-e821-41f9-86d2-a96fd64888faDSpacehttp://dspace.org/items/615c6198-e821-41f9-86d2-a96fd64888faSoaresOrlandoCiência IDhttps://www.ciencia-id.pt6B1D-E906-C118ORCIDhttp://orcid.org0000-0002-7731-5102Researcher IDhttps://www.researcherid.comO-4067-2015Scopus Author IDhttps://www.scopus.com56370132600Gonçalves, HenriqueMartins, António A.Carvalho, AdrianoHostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptISSNIsPartOf2172-038X2012-09-10T12:28:53Z20092009-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/7488http://purl.org/coar/access_right/c_abf2open accessWind power generation,SimulationControlNeural networksDoubly fed induction generator807170 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/9085bfed-0412-4112-8b2a-26ac037f4e38/download7Valencia, Spain
spellingShingle Analysis and NN-based control of doubly fed induction generator in wind power generation
Soares, Orlando
Wind power generation,
Simulation
Control
Neural networks
Doubly fed induction generator
status SINGLETON
subject.fl_str_mv Wind power generation,
Simulation
Control
Neural networks
Doubly fed induction generator
title Analysis and NN-based control of doubly fed induction generator in wind power generation
title_full Analysis and NN-based control of doubly fed induction generator in wind power generation
title_fullStr Analysis and NN-based control of doubly fed induction generator in wind power generation
title_full_unstemmed Analysis and NN-based control of doubly fed induction generator in wind power generation
title_short Analysis and NN-based control of doubly fed induction generator in wind power generation
title_sort Analysis and NN-based control of doubly fed induction generator in wind power generation
topic Wind power generation,
Simulation
Control
Neural networks
Doubly fed induction generator
topic_facet Wind power generation,
Simulation
Control
Neural networks
Doubly fed induction generator
url http://hdl.handle.net/10198/7488
visible 1