Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems
Autor(a) principal: | |
---|---|
Data de Publicação: | 2016 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TLA.2016.7785929 http://hdl.handle.net/11449/169299 |
Resumo: | This paper proposes a method based on Artificial Immune Systems for data management solutions provided by a model used to train power grid and find possible solutions to the problem of restoration of electricity distribution systems. The method aims to manage the supply of recurring defects solutions in the power grid through information stored in a database; the network training for non-recurring defects and storage of data in the database; choosing solutions in the database to start the network training process in the search for new solutions. To train the network and find new solutions to the restoration problem, we use a model that has as one solution technique Tabu Search algorithm. To test the efficiency of the proposed method, we present results of tests and discussions carried out in a medium voltage distribution system. |
id |
UNSP_262fc54fc697e3628f6a6d40aeeeb7b3 |
---|---|
oai_identifier_str |
oai:repositorio.unesp.br:11449/169299 |
network_acronym_str |
UNSP |
network_name_str |
Repositório Institucional da UNESP |
repository_id_str |
2946 |
spelling |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systemsartificial immune systemsData managementdistribution systemsrestorationThis paper proposes a method based on Artificial Immune Systems for data management solutions provided by a model used to train power grid and find possible solutions to the problem of restoration of electricity distribution systems. The method aims to manage the supply of recurring defects solutions in the power grid through information stored in a database; the network training for non-recurring defects and storage of data in the database; choosing solutions in the database to start the network training process in the search for new solutions. To train the network and find new solutions to the restoration problem, we use a model that has as one solution technique Tabu Search algorithm. To test the efficiency of the proposed method, we present results of tests and discussions carried out in a medium voltage distribution system.Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP)Universidade Estadual Paulista (Unesp)Cossi, Antonio Marcos [UNESP]Martins Lopes, Mara Lucia [UNESP]2018-12-11T16:45:16Z2018-12-11T16:45:16Z2016-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article4028-4034application/pdfhttp://dx.doi.org/10.1109/TLA.2016.7785929IEEE Latin America Transactions, v. 14, n. 9, p. 4028-4034, 2016.1548-0992http://hdl.handle.net/11449/16929910.1109/TLA.2016.77859292-s2.0-850074159412-s2.0-85007415941.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPporIEEE Latin America Transactions0,253info:eu-repo/semantics/openAccess2023-10-02T06:02:55Zoai:repositorio.unesp.br:11449/169299Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:45:12.070157Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems |
title |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems |
spellingShingle |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems Cossi, Antonio Marcos [UNESP] artificial immune systems Data management distribution systems restoration |
title_short |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems |
title_full |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems |
title_fullStr |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems |
title_full_unstemmed |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems |
title_sort |
Artificial Immune Systems Applied in Data Management Solutions to the Problem of Restoration of Electrical Distribution Systems |
author |
Cossi, Antonio Marcos [UNESP] |
author_facet |
Cossi, Antonio Marcos [UNESP] Martins Lopes, Mara Lucia [UNESP] |
author_role |
author |
author2 |
Martins Lopes, Mara Lucia [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Cossi, Antonio Marcos [UNESP] Martins Lopes, Mara Lucia [UNESP] |
dc.subject.por.fl_str_mv |
artificial immune systems Data management distribution systems restoration |
topic |
artificial immune systems Data management distribution systems restoration |
description |
This paper proposes a method based on Artificial Immune Systems for data management solutions provided by a model used to train power grid and find possible solutions to the problem of restoration of electricity distribution systems. The method aims to manage the supply of recurring defects solutions in the power grid through information stored in a database; the network training for non-recurring defects and storage of data in the database; choosing solutions in the database to start the network training process in the search for new solutions. To train the network and find new solutions to the restoration problem, we use a model that has as one solution technique Tabu Search algorithm. To test the efficiency of the proposed method, we present results of tests and discussions carried out in a medium voltage distribution system. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-09-01 2018-12-11T16:45:16Z 2018-12-11T16:45:16Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/TLA.2016.7785929 IEEE Latin America Transactions, v. 14, n. 9, p. 4028-4034, 2016. 1548-0992 http://hdl.handle.net/11449/169299 10.1109/TLA.2016.7785929 2-s2.0-85007415941 2-s2.0-85007415941.pdf |
url |
http://dx.doi.org/10.1109/TLA.2016.7785929 http://hdl.handle.net/11449/169299 |
identifier_str_mv |
IEEE Latin America Transactions, v. 14, n. 9, p. 4028-4034, 2016. 1548-0992 10.1109/TLA.2016.7785929 2-s2.0-85007415941 2-s2.0-85007415941.pdf |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
IEEE Latin America Transactions 0,253 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
4028-4034 application/pdf |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128271135539200 |