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Improved predictive control in multi-modular matrix converter for six-phase generation systems

Distributed generation systems are emerging as a good solution as part of the response to the world’s growing energy demand. In this context multi-phase wind generation systems are a feasible option. These systems consist of renewable AC sources which requires efficient and controlled power conversi...

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Zapisane w:
1. autor: Toledo Gallardo, Sergio Ramón (author)
Kolejni autorzy: Maqueda Acuña, Edgar Marcial (author), Rivera, Marco (author), Gregor Recalde, Raúl Igmar (author), Wheeler, Pat (author), Romero, Carlos (author)
Format: article
Język:angielski
Wydane: 2020
Hasła przedmiotowe:
5. Energía
MULTI-PHASE WIND GENERATION SYSTEMS
MODULAR MATRIX CONVERTER
MODEL PREDICTIVE CONTROL
ENERGIA
Dostęp online:http://hdl.handle.net/20.500.14066/3855
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author Toledo Gallardo, Sergio Ramón
author2 Maqueda Acuña, Edgar Marcial
Rivera, Marco
Gregor Recalde, Raúl Igmar
Wheeler, Pat
Romero, Carlos
author2_role author
author
author
author
author
author_browse Gregor Recalde, Raúl Igmar
Maqueda Acuña, Edgar Marcial
Rivera, Marco
Romero, Carlos
Toledo Gallardo, Sergio Ramón
Wheeler, Pat
author_facet Toledo Gallardo, Sergio Ramón
Maqueda Acuña, Edgar Marcial
Rivera, Marco
Gregor Recalde, Raúl Igmar
Wheeler, Pat
Romero, Carlos
author_role author
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bitstream.checksumAlgorithm.fl_str_mv MD5
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bitstream.url.fl_str_mv http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3855/1/PINV15-584art.pdf
http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3855/2/license.txt
http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3855/3/PINV15-584art.pdf.txt
dc.contributor.other.es.fl_str_mv Universidad Nacional de Asunción - Facultad de Ingeniería
dc.creator.none.fl_str_mv Toledo Gallardo, Sergio Ramón
Maqueda Acuña, Edgar Marcial
Rivera, Marco
Gregor Recalde, Raúl Igmar
Wheeler, Pat
Romero, Carlos
dc.date.accessioned.none.fl_str_mv 2022-05-02T18:54:51Z
dc.date.available.none.fl_str_mv 2022-05-02T18:54:51Z
dc.date.issued.none.fl_str_mv 2020
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/20.500.14066/3855
dc.language.iso.es.fl_str_mv eng
dc.relation.projectCONACYT.es.fl_str_mv PINV15-584
dc.rights.accessRights.es.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.classification.es.fl_str_mv 5. Energía
dc.subject.ocde.es.fl_str_mv ENERGIA
dc.subject.other.es.fl_str_mv MULTI-PHASE WIND GENERATION SYSTEMS
MODULAR MATRIX CONVERTER
MODEL PREDICTIVE CONTROL
dc.title.es.fl_str_mv Improved predictive control in multi-modular matrix converter for six-phase generation systems
dc.type.es.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
description Distributed generation systems are emerging as a good solution as part of the response to the world’s growing energy demand. In this context multi-phase wind generation systems are a feasible option. These systems consist of renewable AC sources which requires efficient and controlled power conversion stages. This work proposes a novel predictive current control strategy that takes advantage of a multi-modular matrix converter topology in the power stage of a six-phase generation system. The proposed method uses a coupling signal between the modules to decrease the error and the total harmonic distortion compared to independent control of each module. Experimental results validate the new control strategy showing the improvement regarding the target parameters.
eu_rights_str_mv openAccess
format article
id CONACYT_b2ad782138033dcfd92b6deaaa92388a
language eng
network_acronym_str CONACYT
network_name_str Repositorio Institucional CONACYT
oai_identifier_str oai:repositorio.conacyt.gov.py:20.500.14066/3855
publishDate 2020
publishDateSort 2020
repository.mail.fl_str_mv repositorio.institucional@conacyt.gov.py
repository.name.fl_str_mv Repositorio Institucional CONACYT
repository_id_str
spelling 1116600703600f5a34336-f380-4a8a-9597-f4eaf02dd82f6005696000000-0002-7717-4100ebba12f3-5b62-4aae-a76a-8ea5a420a72660040ab3680-cde4-4877-b202-e21221668dd5600Universidad Nacional de Asunción - Facultad de Ingeniería2022-05-02T18:54:51Z2022-05-02T18:54:51Z2020http://hdl.handle.net/20.500.14066/3855Distributed generation systems are emerging as a good solution as part of the response to the world’s growing energy demand. In this context multi-phase wind generation systems are a feasible option. These systems consist of renewable AC sources which requires efficient and controlled power conversion stages. This work proposes a novel predictive current control strategy that takes advantage of a multi-modular matrix converter topology in the power stage of a six-phase generation system. The proposed method uses a coupling signal between the modules to decrease the error and the total harmonic distortion compared to independent control of each module. Experimental results validate the new control strategy showing the improvement regarding the target parameters.Consejo Nacional de Ciencia y TecnologíaPROCIENCIAeng5. EnergíaMULTI-PHASE WIND GENERATION SYSTEMSMODULAR MATRIX CONVERTERMODEL PREDICTIVE CONTROLENERGIAImproved predictive control in multi-modular matrix converter for six-phase generation systemsinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion10EnergiesPINV15-584info:eu-repo/semantics/openAccess13Toledo Gallardo, Sergio RamónMaqueda Acuña, Edgar MarcialRivera, MarcoGregor Recalde, Raúl IgmarWheeler, PatRomero, CarlosORIGINALPINV15-584art.pdfPINV15-584art.pdfapplication/pdf6653729http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3855/1/PINV15-584art.pdf2eb27ac32ed16ad4d1acab7e0069c6caMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81698http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3855/2/license.txt858b22fda432bd774e469302988c1974MD52TEXTPINV15-584art.pdf.txtPINV15-584art.pdf.txtExtracted texttext/plain37236http://repositorio.conacyt.gov.py/bitstream/20.500.14066/3855/3/PINV15-584art.pdf.txt83422772a771bf3397e28ee7f2c399e0MD5320.500.14066/3855oai:repositorio.conacyt.gov.py:20.500.14066/38552026-02-12 19:30:32.597Repositorio Institucional CONACYTrepositorio.institucional@conacyt.gov.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
spellingShingle Improved predictive control in multi-modular matrix converter for six-phase generation systems
Toledo Gallardo, Sergio Ramón
5. Energía
MULTI-PHASE WIND GENERATION SYSTEMS
MODULAR MATRIX CONVERTER
MODEL PREDICTIVE CONTROL
ENERGIA
status_str publishedVersion
title Improved predictive control in multi-modular matrix converter for six-phase generation systems
title_full Improved predictive control in multi-modular matrix converter for six-phase generation systems
title_fullStr Improved predictive control in multi-modular matrix converter for six-phase generation systems
title_full_unstemmed Improved predictive control in multi-modular matrix converter for six-phase generation systems
title_short Improved predictive control in multi-modular matrix converter for six-phase generation systems
title_sort Improved predictive control in multi-modular matrix converter for six-phase generation systems
topic 5. Energía
MULTI-PHASE WIND GENERATION SYSTEMS
MODULAR MATRIX CONVERTER
MODEL PREDICTIVE CONTROL
ENERGIA
url http://hdl.handle.net/20.500.14066/3855

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