Optimization of Cogeneration Power-Desalination Plants
- Autores
- Pietrasanta, Ariana Milagros; Mussati, Sergio Fabian; Aguirre, Pio Antonio; Morosuk, Tatiana; Mussati, Miguel Ceferino
- Año de publicación
- 2022
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- The design of new dual-purpose thermal desalination plants is a combinatory problem because the optimal process configuration strongly depends on the desired targets of electricity and freshwater. This paper proposes a mathematical model for selecting the optimal structure, the operating conditions, and sizes of all system components of dual-purpose thermal desalination plants. Electricity is supposed to be generated by a combined-cycle heat and power plant (CCHPP) with the following candidate structures: (a) one or two gas turbines; (b) one or two additional burners in the heat recovery steam generator; (c) the presence or missing a medium-pressure steam turbine; (d) steam generation and reheating at low pressure. Freshwater is supposed to be obtained from two candidate thermal processes: and (e) a multi-effect distillation (MED) or a multi-stage flash (MSF) system. The number of effects in MED and stages in MSF are also discrete decisions. Different case studies are presented to show the applicability of the model for same cost data. The proposed model is a powerful tool in optimizing new plants (or plants under modernization) and/or improving existing plants for desired electricity generation and freshwater production. No articles addressing the optimization involving the discrete decisions mentioned above are found in the literature.
Fil: Pietrasanta, Ariana Milagros. 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 - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
Fil: Aguirre, Pio Antonio. 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: Morosuk, Tatiana. Technishe Universitat Berlin; Alemania
Fil: Mussati, Miguel Ceferino. 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
-
COMBINED-CYCLE HEAT AND POWER PLANT
DESALINATION
MINLP
MULTI-EFFECT DISTILLATION
MUTI-STAGE FLASH DESALINATION
OPTIMIZATION - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/217889
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Optimization of Cogeneration Power-Desalination PlantsPietrasanta, Ariana MilagrosMussati, Sergio FabianAguirre, Pio AntonioMorosuk, TatianaMussati, Miguel CeferinoCOMBINED-CYCLE HEAT AND POWER PLANTDESALINATIONMINLPMULTI-EFFECT DISTILLATIONMUTI-STAGE FLASH DESALINATIONOPTIMIZATIONhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2The design of new dual-purpose thermal desalination plants is a combinatory problem because the optimal process configuration strongly depends on the desired targets of electricity and freshwater. This paper proposes a mathematical model for selecting the optimal structure, the operating conditions, and sizes of all system components of dual-purpose thermal desalination plants. Electricity is supposed to be generated by a combined-cycle heat and power plant (CCHPP) with the following candidate structures: (a) one or two gas turbines; (b) one or two additional burners in the heat recovery steam generator; (c) the presence or missing a medium-pressure steam turbine; (d) steam generation and reheating at low pressure. Freshwater is supposed to be obtained from two candidate thermal processes: and (e) a multi-effect distillation (MED) or a multi-stage flash (MSF) system. The number of effects in MED and stages in MSF are also discrete decisions. Different case studies are presented to show the applicability of the model for same cost data. The proposed model is a powerful tool in optimizing new plants (or plants under modernization) and/or improving existing plants for desired electricity generation and freshwater production. No articles addressing the optimization involving the discrete decisions mentioned above are found in the literature.Fil: Pietrasanta, Ariana Milagros. 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 - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Aguirre, Pio Antonio. 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: Morosuk, Tatiana. Technishe Universitat Berlin; AlemaniaFil: Mussati, Miguel Ceferino. 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; ArgentinaMDPI2022-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/217889Pietrasanta, Ariana Milagros; Mussati, Sergio Fabian; Aguirre, Pio Antonio; Morosuk, Tatiana; Mussati, Miguel Ceferino; Optimization of Cogeneration Power-Desalination Plants; MDPI; Energies; 15; 22; 11-2022; 1-221996-1073CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3390/en15228374info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:48:32Zoai:ri.conicet.gov.ar:11336/217889instacron: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 09:48:33.357CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Optimization of Cogeneration Power-Desalination Plants |
title |
Optimization of Cogeneration Power-Desalination Plants |
spellingShingle |
Optimization of Cogeneration Power-Desalination Plants Pietrasanta, Ariana Milagros COMBINED-CYCLE HEAT AND POWER PLANT DESALINATION MINLP MULTI-EFFECT DISTILLATION MUTI-STAGE FLASH DESALINATION OPTIMIZATION |
title_short |
Optimization of Cogeneration Power-Desalination Plants |
title_full |
Optimization of Cogeneration Power-Desalination Plants |
title_fullStr |
Optimization of Cogeneration Power-Desalination Plants |
title_full_unstemmed |
Optimization of Cogeneration Power-Desalination Plants |
title_sort |
Optimization of Cogeneration Power-Desalination Plants |
dc.creator.none.fl_str_mv |
Pietrasanta, Ariana Milagros Mussati, Sergio Fabian Aguirre, Pio Antonio Morosuk, Tatiana Mussati, Miguel Ceferino |
author |
Pietrasanta, Ariana Milagros |
author_facet |
Pietrasanta, Ariana Milagros Mussati, Sergio Fabian Aguirre, Pio Antonio Morosuk, Tatiana Mussati, Miguel Ceferino |
author_role |
author |
author2 |
Mussati, Sergio Fabian Aguirre, Pio Antonio Morosuk, Tatiana Mussati, Miguel Ceferino |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
COMBINED-CYCLE HEAT AND POWER PLANT DESALINATION MINLP MULTI-EFFECT DISTILLATION MUTI-STAGE FLASH DESALINATION OPTIMIZATION |
topic |
COMBINED-CYCLE HEAT AND POWER PLANT DESALINATION MINLP MULTI-EFFECT DISTILLATION MUTI-STAGE FLASH DESALINATION OPTIMIZATION |
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 design of new dual-purpose thermal desalination plants is a combinatory problem because the optimal process configuration strongly depends on the desired targets of electricity and freshwater. This paper proposes a mathematical model for selecting the optimal structure, the operating conditions, and sizes of all system components of dual-purpose thermal desalination plants. Electricity is supposed to be generated by a combined-cycle heat and power plant (CCHPP) with the following candidate structures: (a) one or two gas turbines; (b) one or two additional burners in the heat recovery steam generator; (c) the presence or missing a medium-pressure steam turbine; (d) steam generation and reheating at low pressure. Freshwater is supposed to be obtained from two candidate thermal processes: and (e) a multi-effect distillation (MED) or a multi-stage flash (MSF) system. The number of effects in MED and stages in MSF are also discrete decisions. Different case studies are presented to show the applicability of the model for same cost data. The proposed model is a powerful tool in optimizing new plants (or plants under modernization) and/or improving existing plants for desired electricity generation and freshwater production. No articles addressing the optimization involving the discrete decisions mentioned above are found in the literature. Fil: Pietrasanta, Ariana Milagros. 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 - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina Fil: Aguirre, Pio Antonio. 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: Morosuk, Tatiana. Technishe Universitat Berlin; Alemania Fil: Mussati, Miguel Ceferino. 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 |
The design of new dual-purpose thermal desalination plants is a combinatory problem because the optimal process configuration strongly depends on the desired targets of electricity and freshwater. This paper proposes a mathematical model for selecting the optimal structure, the operating conditions, and sizes of all system components of dual-purpose thermal desalination plants. Electricity is supposed to be generated by a combined-cycle heat and power plant (CCHPP) with the following candidate structures: (a) one or two gas turbines; (b) one or two additional burners in the heat recovery steam generator; (c) the presence or missing a medium-pressure steam turbine; (d) steam generation and reheating at low pressure. Freshwater is supposed to be obtained from two candidate thermal processes: and (e) a multi-effect distillation (MED) or a multi-stage flash (MSF) system. The number of effects in MED and stages in MSF are also discrete decisions. Different case studies are presented to show the applicability of the model for same cost data. The proposed model is a powerful tool in optimizing new plants (or plants under modernization) and/or improving existing plants for desired electricity generation and freshwater production. No articles addressing the optimization involving the discrete decisions mentioned above are found in the literature. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-11 |
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/11336/217889 Pietrasanta, Ariana Milagros; Mussati, Sergio Fabian; Aguirre, Pio Antonio; Morosuk, Tatiana; Mussati, Miguel Ceferino; Optimization of Cogeneration Power-Desalination Plants; MDPI; Energies; 15; 22; 11-2022; 1-22 1996-1073 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/217889 |
identifier_str_mv |
Pietrasanta, Ariana Milagros; Mussati, Sergio Fabian; Aguirre, Pio Antonio; Morosuk, Tatiana; Mussati, Miguel Ceferino; Optimization of Cogeneration Power-Desalination Plants; MDPI; Energies; 15; 22; 11-2022; 1-22 1996-1073 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.3390/en15228374 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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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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13.13397 |