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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/270899
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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 Técnicas2025-09-29T10:42:39Zoai: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:34982025-09-29 10:42:39.773CONICET 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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13.070432 |