Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil

Detalhes bibliográficos
Autor(a) principal: Celeste,Alcigeimes B.
Data de Publicação: 2009
Outros Autores: Curi,Wilson F., Curi,Rosires C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382009000100011
Resumo: This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly operating rules for a reservoir system located in the semiarid Northeast of Brazil. ISO employs a deterministic optimization model to find optimal reservoir allocations under several possible inflow scenarios and later constructs the rules by analyzing the ensemble of these optimal releases. The operating policies provide the monthly reservoir release conditioned on the storage at the beginning of the month and the inflow predicted for the month. In addition to the classical regression analysis, this study establishes the rules by a two-dimensional interpolation strategy. After the rules are identified, they are applied to operate the system under new inflow realizations and show ability to produce policies similar to those obtained by deterministic optimization taking the same inflows as perfect forecasts.
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spelling Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazilreservoir operationimplicit stochastic optimizationsemiarid regionsThis paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly operating rules for a reservoir system located in the semiarid Northeast of Brazil. ISO employs a deterministic optimization model to find optimal reservoir allocations under several possible inflow scenarios and later constructs the rules by analyzing the ensemble of these optimal releases. The operating policies provide the monthly reservoir release conditioned on the storage at the beginning of the month and the inflow predicted for the month. In addition to the classical regression analysis, this study establishes the rules by a two-dimensional interpolation strategy. After the rules are identified, they are applied to operate the system under new inflow realizations and show ability to produce policies similar to those obtained by deterministic optimization taking the same inflows as perfect forecasts.Sociedade Brasileira de Pesquisa Operacional2009-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382009000100011Pesquisa Operacional v.29 n.1 2009reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/S0101-74382009000100011info:eu-repo/semantics/openAccessCeleste,Alcigeimes B.Curi,Wilson F.Curi,Rosires C.eng2009-05-28T00:00:00Zoai:scielo:S0101-74382009000100011Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2009-05-28T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil
title Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil
spellingShingle Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil
Celeste,Alcigeimes B.
reservoir operation
implicit stochastic optimization
semiarid regions
title_short Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil
title_full Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil
title_fullStr Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil
title_full_unstemmed Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil
title_sort Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil
author Celeste,Alcigeimes B.
author_facet Celeste,Alcigeimes B.
Curi,Wilson F.
Curi,Rosires C.
author_role author
author2 Curi,Wilson F.
Curi,Rosires C.
author2_role author
author
dc.contributor.author.fl_str_mv Celeste,Alcigeimes B.
Curi,Wilson F.
Curi,Rosires C.
dc.subject.por.fl_str_mv reservoir operation
implicit stochastic optimization
semiarid regions
topic reservoir operation
implicit stochastic optimization
semiarid regions
description This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly operating rules for a reservoir system located in the semiarid Northeast of Brazil. ISO employs a deterministic optimization model to find optimal reservoir allocations under several possible inflow scenarios and later constructs the rules by analyzing the ensemble of these optimal releases. The operating policies provide the monthly reservoir release conditioned on the storage at the beginning of the month and the inflow predicted for the month. In addition to the classical regression analysis, this study establishes the rules by a two-dimensional interpolation strategy. After the rules are identified, they are applied to operate the system under new inflow realizations and show ability to produce policies similar to those obtained by deterministic optimization taking the same inflows as perfect forecasts.
publishDate 2009
dc.date.none.fl_str_mv 2009-04-01
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=S0101-74382009000100011
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382009000100011
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0101-74382009000100011
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.29 n.1 2009
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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