Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional Manancial UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/21793 |
Resumo: | This work proposes a methodology for detecting voltage imbalance using the OpenDSS software and its COM interface. The proposal is to detect voltage imbalance using the communication between OpenDSS and MATLAB through a Perceptron Multilayer Artificial Neural Network. For that, tests were carried out in a distribution network with distributed generators and energy stores. The studies were conducted on an IEEE 13 bus test system. https://doi.org/10.53316/sepoc2021.041 |
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2021-08-08T23:39:03Z2021-08-08T23:39:03Z2021-05-18http://repositorio.ufsm.br/handle/1/21793engSEPOC 20213004000000076000be92198-160f-4d1b-8791-72cac0f1c8d7e64e6e26-2503-4a1c-80fb-1f85d96f440cAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessvoltage unbalanceartificial neural networksOpenDSSCNPQ::ENGENHARIAS::ENGENHARIA ELETRICADetection of Voltage Unbalance in Microgrids using Artificial Neural Networksinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectThis work proposes a methodology for detecting voltage imbalance using the OpenDSS software and its COM interface. The proposal is to detect voltage imbalance using the communication between OpenDSS and MATLAB through a Perceptron Multilayer Artificial Neural Network. For that, tests were carried out in a distribution network with distributed generators and energy stores. The studies were conducted on an IEEE 13 bus test system. https://doi.org/10.53316/sepoc2021.041Marques, Roberta CarvalhoPaschoareli Junior, DionizioBrasilreponame:Repositório Institucional Manancial UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMORIGINAL041 - Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks.pdf041 - Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks.pdfArtigo de Eventoapplication/pdf9626319http://repositorio.ufsm.br/bitstream/1/21793/1/041%20-%20Detection%20of%20Voltage%20Unbalance%20in%20Microgrids%20using%20Artificial%20Neural%20Networks.pdff79c0289fc9f5bfd9dff9d8de36afb28MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8805http://repositorio.ufsm.br/bitstream/1/21793/2/license_rdf4460e5956bc1d1639be9ae6146a50347MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-816http://repositorio.ufsm.br/bitstream/1/21793/3/license.txtf8fcb28efb1c8cf0dc096bec902bf4c4MD53TEXT041 - Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks.pdf.txt041 - Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks.pdf.txtExtracted texttext/plain62http://repositorio.ufsm.br/bitstream/1/21793/4/041%20-%20Detection%20of%20Voltage%20Unbalance%20in%20Microgrids%20using%20Artificial%20Neural%20Networks.pdf.txt5d5b274866efa978cddf483d3e738430MD54THUMBNAIL041 - Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks.pdf.jpg041 - Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks.pdf.jpgIM Thumbnailimage/jpeg9466http://repositorio.ufsm.br/bitstream/1/21793/5/041%20-%20Detection%20of%20Voltage%20Unbalance%20in%20Microgrids%20using%20Artificial%20Neural%20Networks.pdf.jpg1e56fcc657ebf5b468914f54a210a485MD551/217932021-08-09 03:07:48.654oai:repositorio.ufsm.br:1/21793Q3JlYXRpdmUgQ29tbW9ucw==Repositório Institucionalhttp://repositorio.ufsm.br/PUBhttp://repositorio.ufsm.br/oai/requestouvidoria@ufsm.bropendoar:39132021-08-09T06:07:48Repositório Institucional Manancial UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.por.fl_str_mv |
Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks |
title |
Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks |
spellingShingle |
Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks Marques, Roberta Carvalho voltage unbalance artificial neural networks OpenDSS CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
title_short |
Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks |
title_full |
Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks |
title_fullStr |
Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks |
title_full_unstemmed |
Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks |
title_sort |
Detection of Voltage Unbalance in Microgrids using Artificial Neural Networks |
author |
Marques, Roberta Carvalho |
author_facet |
Marques, Roberta Carvalho Paschoareli Junior, Dionizio |
author_role |
author |
author2 |
Paschoareli Junior, Dionizio |
author2_role |
author |
dc.contributor.author.fl_str_mv |
Marques, Roberta Carvalho Paschoareli Junior, Dionizio |
dc.subject.eng.fl_str_mv |
voltage unbalance artificial neural networks OpenDSS |
topic |
voltage unbalance artificial neural networks OpenDSS CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
dc.subject.cnpq.fl_str_mv |
CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA |
description |
This work proposes a methodology for detecting voltage imbalance using the OpenDSS software and its COM interface. The proposal is to detect voltage imbalance using the communication between OpenDSS and MATLAB through a Perceptron Multilayer Artificial Neural Network. For that, tests were carried out in a distribution network with distributed generators and energy stores. The studies were conducted on an IEEE 13 bus test system. https://doi.org/10.53316/sepoc2021.041 |
publishDate |
2021 |
dc.date.submitted.none.fl_str_mv |
2021-05-18 |
dc.date.accessioned.fl_str_mv |
2021-08-08T23:39:03Z |
dc.date.available.fl_str_mv |
2021-08-08T23:39:03Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/21793 |
url |
http://repositorio.ufsm.br/handle/1/21793 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.cnpq.fl_str_mv |
300400000007 |
dc.relation.confidence.fl_str_mv |
600 |
dc.relation.authority.fl_str_mv |
0be92198-160f-4d1b-8791-72cac0f1c8d7 e64e6e26-2503-4a1c-80fb-1f85d96f440c |
dc.relation.ispartof.por.fl_str_mv |
SEPOC 2021 |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.publisher.country.fl_str_mv |
Brasil |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional Manancial UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Repositório Institucional Manancial UFSM |
collection |
Repositório Institucional Manancial UFSM |
bitstream.url.fl_str_mv |
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