An Adaptive Signal Processing Framework for PV Power Maximization

Detalhes bibliográficos
Autor(a) principal: Vidal,AA
Data de Publicação: 2015
Outros Autores: Vítor Grade Tavares, Principe,JC
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/6463
http://dx.doi.org/10.1007/s00034-015-9972-0
Resumo: This paper discusses the possibility of using adaptive signal processing techniques for maximum power point tracking controllers, in order to extract peak power from individual photovoltaic modules. A new technique grounded on unsupervised Hebbian learning theory (maximum eigenvector of the output power) is presented, which works on-online and is capable of operating without a desired response. Important modifications were made to the generic Hebbian adaptation to accommodate the intrinsic feedback loop between the controller and the plant. Analytic derivation of the new update rule is presented, as well as stability analysis by means of Lyapunov theory. Simulation results showing its effectiveness are presented, as well as experimental results.
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spelling An Adaptive Signal Processing Framework for PV Power MaximizationThis paper discusses the possibility of using adaptive signal processing techniques for maximum power point tracking controllers, in order to extract peak power from individual photovoltaic modules. A new technique grounded on unsupervised Hebbian learning theory (maximum eigenvector of the output power) is presented, which works on-online and is capable of operating without a desired response. Important modifications were made to the generic Hebbian adaptation to accommodate the intrinsic feedback loop between the controller and the plant. Analytic derivation of the new update rule is presented, as well as stability analysis by means of Lyapunov theory. Simulation results showing its effectiveness are presented, as well as experimental results.2018-01-16T16:37:11Z2015-01-01T00:00:00Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/6463http://dx.doi.org/10.1007/s00034-015-9972-0engVidal,AAVítor Grade TavaresPrincipe,JCinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:23Zoai:repositorio.inesctec.pt:123456789/6463Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:02.525640Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv An Adaptive Signal Processing Framework for PV Power Maximization
title An Adaptive Signal Processing Framework for PV Power Maximization
spellingShingle An Adaptive Signal Processing Framework for PV Power Maximization
Vidal,AA
title_short An Adaptive Signal Processing Framework for PV Power Maximization
title_full An Adaptive Signal Processing Framework for PV Power Maximization
title_fullStr An Adaptive Signal Processing Framework for PV Power Maximization
title_full_unstemmed An Adaptive Signal Processing Framework for PV Power Maximization
title_sort An Adaptive Signal Processing Framework for PV Power Maximization
author Vidal,AA
author_facet Vidal,AA
Vítor Grade Tavares
Principe,JC
author_role author
author2 Vítor Grade Tavares
Principe,JC
author2_role author
author
dc.contributor.author.fl_str_mv Vidal,AA
Vítor Grade Tavares
Principe,JC
description This paper discusses the possibility of using adaptive signal processing techniques for maximum power point tracking controllers, in order to extract peak power from individual photovoltaic modules. A new technique grounded on unsupervised Hebbian learning theory (maximum eigenvector of the output power) is presented, which works on-online and is capable of operating without a desired response. Important modifications were made to the generic Hebbian adaptation to accommodate the intrinsic feedback loop between the controller and the plant. Analytic derivation of the new update rule is presented, as well as stability analysis by means of Lyapunov theory. Simulation results showing its effectiveness are presented, as well as experimental results.
publishDate 2015
dc.date.none.fl_str_mv 2015-01-01T00:00:00Z
2015
2018-01-16T16:37:11Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://repositorio.inesctec.pt/handle/123456789/6463
http://dx.doi.org/10.1007/s00034-015-9972-0
url http://repositorio.inesctec.pt/handle/123456789/6463
http://dx.doi.org/10.1007/s00034-015-9972-0
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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