Optimization of triple-pressure combined-cycle power plants by generalized disjunctive programming and extrinsic functions.

Autores
Manassaldi, Juan Ignacio; Mussati, Miguel Ceferino; Scenna, Nicolás José; Mussati, Sergio Fabián
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steamreheat 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.
Universidad Tecnológica Nacional (UTN) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
Fil: Manassaldi, Juan Ignacio. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.
Fil: Manassaldi, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.
Fil: Scenna, Nicolás José. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.
Fil: Scenna, Nicolás José. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.
Fil: Mussati, Sergio Fabián. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.
Fil: Mussati, Sergio Fabián. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Desarrollo y Diseño (INGAR) ; Argentina.
Peer Reviewed
Materia
GAMS
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
2024-03-25T21:45:50Z
Repositorio
Repositorio Institucional Abierto (UTN)
Institución
Universidad Tecnológica Nacional
OAI Identificador
oai:ria.utn.edu.ar:20.500.12272/10067
Acceder
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network_acronym_str RIAUTN
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network_name_str Repositorio Institucional Abierto (UTN)
spelling Optimization of triple-pressure combined-cycle power plants by generalized disjunctive programming and extrinsic functions.Manassaldi, Juan IgnacioMussati, Miguel CeferinoScenna, Nicolás JoséMussati, Sergio FabiánGAMSGeneralized disjunctive programmingExtrinsic functionsThree-pressure reheat combined-cycle power plantHeat recovery steam generator HRSGA new mathematical framework for optimal synthesis, design, and operation of triple-pressure steamreheat 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.Universidad Tecnológica Nacional (UTN) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)Fil: Manassaldi, Juan Ignacio. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.Fil: Manassaldi, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.Fil: Scenna, Nicolás José. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.Fil: Scenna, Nicolás José. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.Fil: Mussati, Sergio Fabián. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.Fil: Mussati, Sergio Fabián. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Desarrollo y Diseño (INGAR) ; Argentina.Peer Reviewed2024-03-25T21:45:50Z2024-03-25T21:45:50Z2021-02-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articulopdfapplication/pdfComputers & Chemical Engineering, 146, 107190.0098-1354http://hdl.handle.net/20.500.12272/10067https://doi.org/10.1016/j.compchemeng.2020.107190enginfo:eu-repo/semantics/openAccess2024-03-25T21:45:50Zhttp://creativecommons.org/licenses/by-nc-nd/4.0/Attribution-NonCommercial-NoDerivatives 4.0 InternacionalAcceso abierto, con fines de estudio e investigación. Siempre con la mención de los autores.reponame:Repositorio Institucional Abierto (UTN)instname:Universidad Tecnológica Nacional2026-09-24T12:46:43Zoai:ria.utn.edu.ar:20.500.12272/10067instacron:UTNInstitucionalhttp://ria.utn.edu.ar/Universidad públicaNo correspondehttp://ria.utn.edu.ar/oaigestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:a2026-09-24 12:46:44.82Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacionalfalse
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
GAMS
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, Nicolás José
Mussati, Sergio Fabián
author Manassaldi, Juan Ignacio
author_facet Manassaldi, Juan Ignacio
Mussati, Miguel Ceferino
Scenna, Nicolás José
Mussati, Sergio Fabián
author_role author
author2 Mussati, Miguel Ceferino
Scenna, Nicolás José
Mussati, Sergio Fabián
author2_role author
author
author
dc.subject.none.fl_str_mv GAMS
Generalized disjunctive programming
Extrinsic functions
Three-pressure reheat combined-cycle power plant
Heat recovery steam generator HRSG
topic GAMS
Generalized disjunctive programming
Extrinsic functions
Three-pressure reheat combined-cycle power plant
Heat recovery steam generator HRSG
dc.description.none.fl_txt_mv A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steamreheat 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.
Universidad Tecnológica Nacional (UTN) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)
Fil: Manassaldi, Juan Ignacio. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.
Fil: Manassaldi, Juan Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.
Fil: Scenna, Nicolás José. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.
Fil: Scenna, Nicolás José. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) ; Argentina.
Fil: Mussati, Sergio Fabián. Universidad Tecnológica Nacional (UTN). Facultad Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería (CAIMI) ; Argentina.
Fil: Mussati, Sergio Fabián. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). Instituto de Desarrollo y Diseño (INGAR) ; Argentina.
Peer Reviewed
description A new mathematical framework for optimal synthesis, design, and operation of triple-pressure steamreheat 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 2021
dc.date.none.fl_str_mv 2021-02-01
2024-03-25T21:45:50Z
2024-03-25T21:45:50Z
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 Computers & Chemical Engineering, 146, 107190.
0098-1354
http://hdl.handle.net/20.500.12272/10067
https://doi.org/10.1016/j.compchemeng.2020.107190
identifier_str_mv Computers & Chemical Engineering, 146, 107190.
0098-1354
url http://hdl.handle.net/20.500.12272/10067
https://doi.org/10.1016/j.compchemeng.2020.107190
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
2024-03-25T21:45:50Z
http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Acceso abierto, con fines de estudio e investigación. Siempre con la mención de los autores.
eu_rights_str_mv openAccess
rights_invalid_str_mv 2024-03-25T21:45:50Z
http://creativecommons.org/licenses/by-nc-nd/4.0/
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Acceso abierto, con fines de estudio e investigación. Siempre con la mención de los autores.
dc.format.none.fl_str_mv pdf
application/pdf
dc.source.none.fl_str_mv reponame:Repositorio Institucional Abierto (UTN)
instname:Universidad Tecnológica Nacional
reponame_str Repositorio Institucional Abierto (UTN)
collection Repositorio Institucional Abierto (UTN)
instname_str Universidad Tecnológica Nacional
repository.name.fl_str_mv Repositorio Institucional Abierto (UTN) - Universidad Tecnológica Nacional
repository.mail.fl_str_mv gestionria@rec.utn.edu.ar; fsuarez@rec.utn.edu.ar
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score 13.265058

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