Neural-network-based approach applied to harmonic component estimation in microgrids

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Federal de São Carlos (UFSCar)-
Autor(es): dc.contributorDept. of Electrical Engineering-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorFederal University of S ao Carlos-
Autor(es): dc.creatorReis Bernardino, Luiz Gustavo-
Autor(es): dc.creatorDo Nascimento, Claudionor Francisco-
Autor(es): dc.creatorTavares Neto, Roberto Fernandes-
Autor(es): dc.creatorDe Souza, Wesley Angelino-
Autor(es): dc.creatorMarafao, Fernando Pinhabel-
Data de aceite: dc.date.accessioned2025-08-21T22:21:37Z-
Data de disponibilização: dc.date.available2025-08-21T22:21:37Z-
Data de envio: dc.date.issued2022-05-01-
Data de envio: dc.date.issued2022-05-01-
Data de envio: dc.date.issued2020-12-31-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1109/COBEP53665.2021.9684083-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/234231-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/234231-
Descrição: dc.descriptionPower quality in smart microgrids must be carefully analyzed, whereas adverse consequences may harm the electrical systems without power management and appropriate measures. The main goal of this paper is to develop a 5th, 7th, 11th, and 13th voltage harmonic components identification method based on artificial neural network (ANN). This tool could provide information to the smart microgrid management and control system or be an alternative solution to the harmonic identification process of a harmonic compensator embededs into power converters. The trained algorithm can identify harmonic components amplitude and phase angle in the interfacing point between microgrid and power converters. it was possible to generate a voltage waveform with a maximum difference of 0.04 p.u. between the expected waveform and the one built with the parameters identified by ANN. The ANN method validation was performed through computer simulations.-
Descrição: dc.descriptionFederal University of São Carlos Dept. of Electrical Engineering-
Descrição: dc.descriptionFederal University of Technology - Paraná Dept. of Electrical Engineering-
Descrição: dc.descriptionSão Paulo State University Dept. of Control and Automation Engineering-
Descrição: dc.descriptionDept. of Production Engineering Federal University of S ao Carlos-
Descrição: dc.descriptionSão Paulo State University Dept. of Control and Automation Engineering-
Idioma: dc.languageen-
Relação: dc.relation2021 Brazilian Power Electronics Conference, COBEP 2021-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectArtificial neural networks-
Palavras-chave: dc.subjectharmonic component identification-
Palavras-chave: dc.subjectmicrogrids-
Palavras-chave: dc.subjectpower quality-
Título: dc.titleNeural-network-based approach applied to harmonic component estimation in microgrids-
Tipo de arquivo: dc.typeaula digital-
Aparece nas coleções:Repositório Institucional - Unesp

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