CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution

Autores
Mores, Patricia Liliana; Rodríguez, Néstor Hugo; Scenna, Nicolas Jose; Mussati, Sergio Fabian
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The post combustion process based on the CO2 absorption using amine aqueous solution is one of the more attractive options to drastically reduce greenhouse gas emissions from electric power sector. However, the solvent regeneration is highly energy intensive affecting the total operating cost significantly. The CO2 removal target depends on the absorption and desorption processes where the main parameters of both processes are strongly coupled. Consequently, the simultaneous optimization of the whole CO2 capture process is essential to determine the best design and operating conditions in order to minimize the total cost. This paper presents and discusses different cost optimizations including both investments and operating costs. The impact of different CO2 emission reduction targets on the total annual cost, operating conditions and dimensions of process units is investigated in detail. Optimized results are discussed through different case studies.
Fil: Mores, Patricia Liliana. 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: Rodríguez, Néstor Hugo. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina
Fil: Scenna, Nicolas Jose. 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: Mussati, Sergio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina
Materia
CO2 capture cost
Mathematical modeling
Optimization NLP models
Greenhouse gas emissions
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/270899
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solutionMores, Patricia LilianaRodríguez, Néstor HugoScenna, Nicolas JoseMussati, Sergio FabianCO2 capture costMathematical modelingOptimization NLP modelsGreenhouse gas emissionshttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2The post combustion process based on the CO2 absorption using amine aqueous solution is one of the more attractive options to drastically reduce greenhouse gas emissions from electric power sector. However, the solvent regeneration is highly energy intensive affecting the total operating cost significantly. The CO2 removal target depends on the absorption and desorption processes where the main parameters of both processes are strongly coupled. Consequently, the simultaneous optimization of the whole CO2 capture process is essential to determine the best design and operating conditions in order to minimize the total cost. This paper presents and discusses different cost optimizations including both investments and operating costs. The impact of different CO2 emission reduction targets on the total annual cost, operating conditions and dimensions of process units is investigated in detail. Optimized results are discussed through different case studies.Fil: Mores, Patricia Liliana. 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: Rodríguez, Néstor Hugo. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; ArgentinaFil: Scenna, Nicolas Jose. 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: Mussati, Sergio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; ArgentinaElsevier2012-09info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/270899Mores, Patricia Liliana; Rodríguez, Néstor Hugo; Scenna, Nicolas Jose; Mussati, Sergio Fabian; CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution; Elsevier; International Journal of Greenhouse Gas Control; 10; 9-2012; 148-1631750-5836CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ijggc.2012.06.002info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:40:42Zoai:ri.conicet.gov.ar:11336/270899instacron: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:34982025-10-15 15:40:43.212CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution
title CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution
spellingShingle CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution
Mores, Patricia Liliana
CO2 capture cost
Mathematical modeling
Optimization NLP models
Greenhouse gas emissions
title_short CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution
title_full CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution
title_fullStr CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution
title_full_unstemmed CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution
title_sort CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution
dc.creator.none.fl_str_mv Mores, Patricia Liliana
Rodríguez, Néstor Hugo
Scenna, Nicolas Jose
Mussati, Sergio Fabian
author Mores, Patricia Liliana
author_facet Mores, Patricia Liliana
Rodríguez, Néstor Hugo
Scenna, Nicolas Jose
Mussati, Sergio Fabian
author_role author
author2 Rodríguez, Néstor Hugo
Scenna, Nicolas Jose
Mussati, Sergio Fabian
author2_role author
author
author
dc.subject.none.fl_str_mv CO2 capture cost
Mathematical modeling
Optimization NLP models
Greenhouse gas emissions
topic CO2 capture cost
Mathematical modeling
Optimization NLP models
Greenhouse gas emissions
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv The post combustion process based on the CO2 absorption using amine aqueous solution is one of the more attractive options to drastically reduce greenhouse gas emissions from electric power sector. However, the solvent regeneration is highly energy intensive affecting the total operating cost significantly. The CO2 removal target depends on the absorption and desorption processes where the main parameters of both processes are strongly coupled. Consequently, the simultaneous optimization of the whole CO2 capture process is essential to determine the best design and operating conditions in order to minimize the total cost. This paper presents and discusses different cost optimizations including both investments and operating costs. The impact of different CO2 emission reduction targets on the total annual cost, operating conditions and dimensions of process units is investigated in detail. Optimized results are discussed through different case studies.
Fil: Mores, Patricia Liliana. 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: Rodríguez, Néstor Hugo. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina
Fil: Scenna, Nicolas Jose. 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: Mussati, Sergio Fabian. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentina. Universidad Tecnológica Nacional. Regional Rosario. Centro de Aplicaciones Informáticas y Modelado en Ingeniería; Argentina
description The post combustion process based on the CO2 absorption using amine aqueous solution is one of the more attractive options to drastically reduce greenhouse gas emissions from electric power sector. However, the solvent regeneration is highly energy intensive affecting the total operating cost significantly. The CO2 removal target depends on the absorption and desorption processes where the main parameters of both processes are strongly coupled. Consequently, the simultaneous optimization of the whole CO2 capture process is essential to determine the best design and operating conditions in order to minimize the total cost. This paper presents and discusses different cost optimizations including both investments and operating costs. The impact of different CO2 emission reduction targets on the total annual cost, operating conditions and dimensions of process units is investigated in detail. Optimized results are discussed through different case studies.
publishDate 2012
dc.date.none.fl_str_mv 2012-09
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/11336/270899
Mores, Patricia Liliana; Rodríguez, Néstor Hugo; Scenna, Nicolas Jose; Mussati, Sergio Fabian; CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution; Elsevier; International Journal of Greenhouse Gas Control; 10; 9-2012; 148-163
1750-5836
CONICET Digital
CONICET
url http://hdl.handle.net/11336/270899
identifier_str_mv Mores, Patricia Liliana; Rodríguez, Néstor Hugo; Scenna, Nicolas Jose; Mussati, Sergio Fabian; CO2 capture in power plants: Minimization of the investment and operating cost of the post-combustion process using MEA aqueous solution; Elsevier; International Journal of Greenhouse Gas Control; 10; 9-2012; 148-163
1750-5836
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ijggc.2012.06.002
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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
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score 13.22299

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