Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions

Autores
Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Scenna, Nicolas Jose; Mussati, Sergio Fabian
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steam-reheat combined-cycle power plants (CCPP) is presented. A superstructure-based representation of the process, which embeds a large number of candidate configurations, is first proposed. Then, a generalized disjunctive programming (GDP) mathematical model is derived from it. Series, parallel, and combined series-parallel arrangements of heat exchangers are simultaneously embedded. Extrinsic functions executed outside GAMS from dynamic-link libraries (DLL) are used to estimate the thermodynamic properties of the working fluids. As a main result, improved process configurations with respect to two reported reference cases were found. The total heat transfer areas calculated in this work are by around 15% and 26% lower than those corresponding to the reference cases.This paper contributes to the literature in two ways: (i) with a disjunctive optimization model of natural gas CCPP and the corresponding solution strategy, and (ii) with improved HRSG configurations.
Fil: Manassaldi, Juan Ignacio. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Fil: Mussati, Miguel Ceferino. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Scenna, Nicolas Jose. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Fil: Mussati, Sergio Fabian. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Materia
GENERALIZED DISJUNCTIVE PROGRAMMING
EXTRINSIC FUNCTIONS
THREE-PRESSURE REHEAT COMBINED-CYCLE POWER PLANT
HEAT RECOVERY STEAM GENERATOR HRSG
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/154751
Acceder
id CONICETDig_f6316bf97faf7ec063fc2d6fd4b135da
oai_identifier_str oai:ri.conicet.gov.ar:11336/154751
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic FunctionsManassaldi, Juan IgnacioMussati, Miguel CeferinoScenna, Nicolas JoseMussati, Sergio FabianGENERALIZED DISJUNCTIVE PROGRAMMINGEXTRINSIC FUNCTIONSTHREE-PRESSURE REHEAT COMBINED-CYCLE POWER PLANTHEAT RECOVERY STEAM GENERATOR HRSGhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steam-reheat combined-cycle power plants (CCPP) is presented. A superstructure-based representation of the process, which embeds a large number of candidate configurations, is first proposed. Then, a generalized disjunctive programming (GDP) mathematical model is derived from it. Series, parallel, and combined series-parallel arrangements of heat exchangers are simultaneously embedded. Extrinsic functions executed outside GAMS from dynamic-link libraries (DLL) are used to estimate the thermodynamic properties of the working fluids. As a main result, improved process configurations with respect to two reported reference cases were found. The total heat transfer areas calculated in this work are by around 15% and 26% lower than those corresponding to the reference cases.This paper contributes to the literature in two ways: (i) with a disjunctive optimization model of natural gas CCPP and the corresponding solution strategy, and (ii) with improved HRSG configurations.Fil: Manassaldi, Juan Ignacio. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Mussati, Miguel Ceferino. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Scenna, Nicolas Jose. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Mussati, Sergio Fabian. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaPergamon-Elsevier Science Ltd2020-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/154751Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Scenna, Nicolas Jose; Mussati, Sergio Fabian; Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 146; 12-2020; 1-190098-13541873-4375CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0098135420312333info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2020.107190info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:58:55Zoai:ri.conicet.gov.ar:11336/154751instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:58:55.835CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions
title Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions
spellingShingle Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions
Manassaldi, Juan Ignacio
GENERALIZED DISJUNCTIVE PROGRAMMING
EXTRINSIC FUNCTIONS
THREE-PRESSURE REHEAT COMBINED-CYCLE POWER PLANT
HEAT RECOVERY STEAM GENERATOR HRSG
title_short Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions
title_full Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions
title_fullStr Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions
title_full_unstemmed Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions
title_sort Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions
dc.creator.none.fl_str_mv Manassaldi, Juan Ignacio
Mussati, Miguel Ceferino
Scenna, Nicolas Jose
Mussati, Sergio Fabian
author Manassaldi, Juan Ignacio
author_facet Manassaldi, Juan Ignacio
Mussati, Miguel Ceferino
Scenna, Nicolas Jose
Mussati, Sergio Fabian
author_role author
author2 Mussati, Miguel Ceferino
Scenna, Nicolas Jose
Mussati, Sergio Fabian
author2_role author
author
author
dc.subject.none.fl_str_mv GENERALIZED DISJUNCTIVE PROGRAMMING
EXTRINSIC FUNCTIONS
THREE-PRESSURE REHEAT COMBINED-CYCLE POWER PLANT
HEAT RECOVERY STEAM GENERATOR HRSG
topic GENERALIZED DISJUNCTIVE PROGRAMMING
EXTRINSIC FUNCTIONS
THREE-PRESSURE REHEAT COMBINED-CYCLE POWER PLANT
HEAT RECOVERY STEAM GENERATOR HRSG
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steam-reheat combined-cycle power plants (CCPP) is presented. A superstructure-based representation of the process, which embeds a large number of candidate configurations, is first proposed. Then, a generalized disjunctive programming (GDP) mathematical model is derived from it. Series, parallel, and combined series-parallel arrangements of heat exchangers are simultaneously embedded. Extrinsic functions executed outside GAMS from dynamic-link libraries (DLL) are used to estimate the thermodynamic properties of the working fluids. As a main result, improved process configurations with respect to two reported reference cases were found. The total heat transfer areas calculated in this work are by around 15% and 26% lower than those corresponding to the reference cases.This paper contributes to the literature in two ways: (i) with a disjunctive optimization model of natural gas CCPP and the corresponding solution strategy, and (ii) with improved HRSG configurations.
Fil: Manassaldi, Juan Ignacio. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Fil: Mussati, Miguel Ceferino. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Scenna, Nicolas Jose. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina
Fil: Mussati, Sergio Fabian. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
description A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steam-reheat combined-cycle power plants (CCPP) is presented. A superstructure-based representation of the process, which embeds a large number of candidate configurations, is first proposed. Then, a generalized disjunctive programming (GDP) mathematical model is derived from it. Series, parallel, and combined series-parallel arrangements of heat exchangers are simultaneously embedded. Extrinsic functions executed outside GAMS from dynamic-link libraries (DLL) are used to estimate the thermodynamic properties of the working fluids. As a main result, improved process configurations with respect to two reported reference cases were found. The total heat transfer areas calculated in this work are by around 15% and 26% lower than those corresponding to the reference cases.This paper contributes to the literature in two ways: (i) with a disjunctive optimization model of natural gas CCPP and the corresponding solution strategy, and (ii) with improved HRSG configurations.
publishDate 2020
dc.date.none.fl_str_mv 2020-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/154751
Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Scenna, Nicolas Jose; Mussati, Sergio Fabian; Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 146; 12-2020; 1-19
0098-1354
1873-4375
CONICET Digital
CONICET
url http://hdl.handle.net/11336/154751
identifier_str_mv Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Scenna, Nicolas Jose; Mussati, Sergio Fabian; Optimization of Triple-Pressure Combined-Cycle Power Plants by Generalized Disjunctive Programming and Extrinsic Functions; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 146; 12-2020; 1-19
0098-1354
1873-4375
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0098135420312333
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.compchemeng.2020.107190
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1842269550273363968
score 13.13397

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