A planning model for offshore natural gas transmission

Detalhes bibliográficos
Autor(a) principal: Iamashita,Edson K.
Data de Publicação: 2008
Outros Autores: Galaxe,Frederico, Arica,José
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382008000100002
Resumo: This paper aims at new approach to solve complex integrated offshore gas planning problems, defining the best transmission strategy for a system with a large number of platforms interconnected between them and with delivery points through a complex gas pipeline network (which can be cycled). The problem is formulated as a large quadratic mixed-integer problem, where non-convexity and non-differentiability is found. Because the complexity of the problem, it is proposed a heuristic, in the context of genetic technique, for solving it. Several numerical experiments are presented at the end of this work. The results show that the performance of our approach is very good, being its results very close to exact solutions. The algorithm could be used for sizing and optimization designs of gas pipeline networks, as well as for the gas transmission planning of an existing network, seeking for profit maximization.
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spelling A planning model for offshore natural gas transmissionnatural gastransmission networksgenetic meta-heuristicThis paper aims at new approach to solve complex integrated offshore gas planning problems, defining the best transmission strategy for a system with a large number of platforms interconnected between them and with delivery points through a complex gas pipeline network (which can be cycled). The problem is formulated as a large quadratic mixed-integer problem, where non-convexity and non-differentiability is found. Because the complexity of the problem, it is proposed a heuristic, in the context of genetic technique, for solving it. Several numerical experiments are presented at the end of this work. The results show that the performance of our approach is very good, being its results very close to exact solutions. The algorithm could be used for sizing and optimization designs of gas pipeline networks, as well as for the gas transmission planning of an existing network, seeking for profit maximization.Sociedade Brasileira de Pesquisa Operacional2008-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382008000100002Pesquisa Operacional v.28 n.1 2008reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/S0101-74382008000100002info:eu-repo/semantics/openAccessIamashita,Edson K.Galaxe,FredericoArica,Joséeng2008-06-23T00:00:00Zoai:scielo:S0101-74382008000100002Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2008-06-23T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv A planning model for offshore natural gas transmission
title A planning model for offshore natural gas transmission
spellingShingle A planning model for offshore natural gas transmission
Iamashita,Edson K.
natural gas
transmission networks
genetic meta-heuristic
title_short A planning model for offshore natural gas transmission
title_full A planning model for offshore natural gas transmission
title_fullStr A planning model for offshore natural gas transmission
title_full_unstemmed A planning model for offshore natural gas transmission
title_sort A planning model for offshore natural gas transmission
author Iamashita,Edson K.
author_facet Iamashita,Edson K.
Galaxe,Frederico
Arica,José
author_role author
author2 Galaxe,Frederico
Arica,José
author2_role author
author
dc.contributor.author.fl_str_mv Iamashita,Edson K.
Galaxe,Frederico
Arica,José
dc.subject.por.fl_str_mv natural gas
transmission networks
genetic meta-heuristic
topic natural gas
transmission networks
genetic meta-heuristic
description This paper aims at new approach to solve complex integrated offshore gas planning problems, defining the best transmission strategy for a system with a large number of platforms interconnected between them and with delivery points through a complex gas pipeline network (which can be cycled). The problem is formulated as a large quadratic mixed-integer problem, where non-convexity and non-differentiability is found. Because the complexity of the problem, it is proposed a heuristic, in the context of genetic technique, for solving it. Several numerical experiments are presented at the end of this work. The results show that the performance of our approach is very good, being its results very close to exact solutions. The algorithm could be used for sizing and optimization designs of gas pipeline networks, as well as for the gas transmission planning of an existing network, seeking for profit maximization.
publishDate 2008
dc.date.none.fl_str_mv 2008-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382008000100002
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382008000100002
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0101-74382008000100002
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.28 n.1 2008
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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