Large-scale dynamic optimization of a low density polyethylene plant

Autores
Cervantes, A.; Tonelli, S.; Brandolin, Adriana; Bandoni, Jose Alberto; Biegler, L.
Año de publicación
2000
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper presents the optimal control policy of an industrial low-density polyethylene (LDPE) plant. Based on a dynamic model of the whole plant, optimal feed profiles are determined to minimize the transient states generated during the switching between different steady states. This industrial process produces LDPE by high-pressure polymerization of ethylene in a tubular reactor. The plant produces different final products. The model consists of two parts, the first one corresponds to the reactor and the second to the rest of the plant. The process has many time delays that are also incorporated into the optimization model. The resulting differential algebraic equation (DAE) plant model includes over 500 equations. The continuous state and control variables are discretized by applying orthogonal collocation on finite elements. The resulting NLP is solved with a reduced space interior point algorithm. The paper studies two cases of switching among different polymer grades determining the optimal butane flow rates, in order to minimize the time to reach the steady state operation corresponding to the desired new product quality.
Fil: Cervantes, A.. Carnegie Mellon University; Estados Unidos
Fil: Tonelli, S.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Biegler, L.. Carnegie Mellon University; Estados Unidos
Materia
Optimisation
Polyethylene plant
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:11336/101421
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Large-scale dynamic optimization of a low density polyethylene plantCervantes, A.Tonelli, S.Brandolin, AdrianaBandoni, Jose AlbertoBiegler, L.OptimisationPolyethylene planthttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This paper presents the optimal control policy of an industrial low-density polyethylene (LDPE) plant. Based on a dynamic model of the whole plant, optimal feed profiles are determined to minimize the transient states generated during the switching between different steady states. This industrial process produces LDPE by high-pressure polymerization of ethylene in a tubular reactor. The plant produces different final products. The model consists of two parts, the first one corresponds to the reactor and the second to the rest of the plant. The process has many time delays that are also incorporated into the optimization model. The resulting differential algebraic equation (DAE) plant model includes over 500 equations. The continuous state and control variables are discretized by applying orthogonal collocation on finite elements. The resulting NLP is solved with a reduced space interior point algorithm. The paper studies two cases of switching among different polymer grades determining the optimal butane flow rates, in order to minimize the time to reach the steady state operation corresponding to the desired new product quality.Fil: Cervantes, A.. Carnegie Mellon University; Estados UnidosFil: Tonelli, S.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Biegler, L.. Carnegie Mellon University; Estados UnidosPergamon-Elsevier Science Ltd2000-07-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/101421Cervantes, A.; Tonelli, S.; Brandolin, Adriana; Bandoni, Jose Alberto; Biegler, L.; Large-scale dynamic optimization of a low density polyethylene plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 24; 2-7; 15-7-2000; 983-9890098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0098135400004166info:eu-repo/semantics/altIdentifier/doi/10.1016/S0098-1354(00)00416-6info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:08:23Zoai:ri.conicet.gov.ar:11336/101421instacron: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:34982025-09-10 13:08:23.865CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Large-scale dynamic optimization of a low density polyethylene plant
title Large-scale dynamic optimization of a low density polyethylene plant
spellingShingle Large-scale dynamic optimization of a low density polyethylene plant
Cervantes, A.
Optimisation
Polyethylene plant
title_short Large-scale dynamic optimization of a low density polyethylene plant
title_full Large-scale dynamic optimization of a low density polyethylene plant
title_fullStr Large-scale dynamic optimization of a low density polyethylene plant
title_full_unstemmed Large-scale dynamic optimization of a low density polyethylene plant
title_sort Large-scale dynamic optimization of a low density polyethylene plant
dc.creator.none.fl_str_mv Cervantes, A.
Tonelli, S.
Brandolin, Adriana
Bandoni, Jose Alberto
Biegler, L.
author Cervantes, A.
author_facet Cervantes, A.
Tonelli, S.
Brandolin, Adriana
Bandoni, Jose Alberto
Biegler, L.
author_role author
author2 Tonelli, S.
Brandolin, Adriana
Bandoni, Jose Alberto
Biegler, L.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Optimisation
Polyethylene plant
topic Optimisation
Polyethylene plant
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This paper presents the optimal control policy of an industrial low-density polyethylene (LDPE) plant. Based on a dynamic model of the whole plant, optimal feed profiles are determined to minimize the transient states generated during the switching between different steady states. This industrial process produces LDPE by high-pressure polymerization of ethylene in a tubular reactor. The plant produces different final products. The model consists of two parts, the first one corresponds to the reactor and the second to the rest of the plant. The process has many time delays that are also incorporated into the optimization model. The resulting differential algebraic equation (DAE) plant model includes over 500 equations. The continuous state and control variables are discretized by applying orthogonal collocation on finite elements. The resulting NLP is solved with a reduced space interior point algorithm. The paper studies two cases of switching among different polymer grades determining the optimal butane flow rates, in order to minimize the time to reach the steady state operation corresponding to the desired new product quality.
Fil: Cervantes, A.. Carnegie Mellon University; Estados Unidos
Fil: Tonelli, S.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Brandolin, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Bandoni, Jose Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentina
Fil: Biegler, L.. Carnegie Mellon University; Estados Unidos
description This paper presents the optimal control policy of an industrial low-density polyethylene (LDPE) plant. Based on a dynamic model of the whole plant, optimal feed profiles are determined to minimize the transient states generated during the switching between different steady states. This industrial process produces LDPE by high-pressure polymerization of ethylene in a tubular reactor. The plant produces different final products. The model consists of two parts, the first one corresponds to the reactor and the second to the rest of the plant. The process has many time delays that are also incorporated into the optimization model. The resulting differential algebraic equation (DAE) plant model includes over 500 equations. The continuous state and control variables are discretized by applying orthogonal collocation on finite elements. The resulting NLP is solved with a reduced space interior point algorithm. The paper studies two cases of switching among different polymer grades determining the optimal butane flow rates, in order to minimize the time to reach the steady state operation corresponding to the desired new product quality.
publishDate 2000
dc.date.none.fl_str_mv 2000-07-15
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/11336/101421
Cervantes, A.; Tonelli, S.; Brandolin, Adriana; Bandoni, Jose Alberto; Biegler, L.; Large-scale dynamic optimization of a low density polyethylene plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 24; 2-7; 15-7-2000; 983-989
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/101421
identifier_str_mv Cervantes, A.; Tonelli, S.; Brandolin, Adriana; Bandoni, Jose Alberto; Biegler, L.; Large-scale dynamic optimization of a low density polyethylene plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 24; 2-7; 15-7-2000; 983-989
0098-1354
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/abs/pii/S0098135400004166
info:eu-repo/semantics/altIdentifier/doi/10.1016/S0098-1354(00)00416-6
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
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
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score 12.993085

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