Large-scale dynamic optimization for grade transitions in a low density polyethylene plant

Autores
Cervantes, A.M.; Tonelli, S.; Brandolin, Adriana; Bandoni, Jose Alberto; Biegler, L.
Año de publicación
2002
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. The industrial process under study produces LDPE by high-pressure polymerization of ethylene in a tubular reactor using oxygen and organic peroxides as initiators. The plant produces polyethylene of different grades that require continuous changes from one steady state to another, in order to switch among the different final products. These changes generate disturbances that keep the product out of specifications during the transient states, with a consequent economic loss. The plant model consists of two parts; the first one corresponds to the tubular reactor. Here, the partial differential equations corresponding to the mass and energy dynamic balances are discretized along the distance coordinate by using finite differences. The resulting ordinary differential equations include the energy balance and individual mass balances for oxygen, peroxides, ethylene, butane, free radicals and polymer. Although, methane is also present in the plant, in the reactor model it is considered as a nonreacting impurity along with the other impurities coming from the rest of the process. The second part of the model corresponds to the rest of the plant. Here we considered four components: ethylene, butane, methane and impurities. An interesting aspect of this process is the presence of many time delays that are incorporated in the optimization model. The resulting differential algebraic equation (DAE) plant model includes over five hundred equations. The dynamic optimization problem is solved using a simultaneous nonlinear programming (NLP) approach. 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, which is applied directly to the NLP. In addition, a new mesh refinement strategy is applied to this model to confirm that no further improvement can be found in the optimal control profiles. The paper studies two cases of switching among different polymer grades, determining the optimal profiles of butane fed to the plant, in order to minimize the time to reach the steady state operation corresponding to the desired new product quality. The results are also compared with simpler model where reactor was considered as a black-box with the conversion level taken as constant data for each polymer grade. As a result, the dynamic model we developed and the solution methodology used is a flexible and practical tool to help process engineers for taking decisions during the plant operation.
Fil: Cervantes, A.M.. 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
Optimization
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:11336/101426

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spelling Large-scale dynamic optimization for grade transitions in a low density polyethylene plantCervantes, A.M.Tonelli, S.Brandolin, AdrianaBandoni, Jose AlbertoBiegler, L.OptimizationPolyethylene 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. The industrial process under study produces LDPE by high-pressure polymerization of ethylene in a tubular reactor using oxygen and organic peroxides as initiators. The plant produces polyethylene of different grades that require continuous changes from one steady state to another, in order to switch among the different final products. These changes generate disturbances that keep the product out of specifications during the transient states, with a consequent economic loss. The plant model consists of two parts; the first one corresponds to the tubular reactor. Here, the partial differential equations corresponding to the mass and energy dynamic balances are discretized along the distance coordinate by using finite differences. The resulting ordinary differential equations include the energy balance and individual mass balances for oxygen, peroxides, ethylene, butane, free radicals and polymer. Although, methane is also present in the plant, in the reactor model it is considered as a nonreacting impurity along with the other impurities coming from the rest of the process. The second part of the model corresponds to the rest of the plant. Here we considered four components: ethylene, butane, methane and impurities. An interesting aspect of this process is the presence of many time delays that are incorporated in the optimization model. The resulting differential algebraic equation (DAE) plant model includes over five hundred equations. The dynamic optimization problem is solved using a simultaneous nonlinear programming (NLP) approach. 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, which is applied directly to the NLP. In addition, a new mesh refinement strategy is applied to this model to confirm that no further improvement can be found in the optimal control profiles. The paper studies two cases of switching among different polymer grades, determining the optimal profiles of butane fed to the plant, in order to minimize the time to reach the steady state operation corresponding to the desired new product quality. The results are also compared with simpler model where reactor was considered as a black-box with the conversion level taken as constant data for each polymer grade. As a result, the dynamic model we developed and the solution methodology used is a flexible and practical tool to help process engineers for taking decisions during the plant operation.Fil: Cervantes, A.M.. 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 Ltd2002-02-15info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/101426Cervantes, A.M.; Tonelli, S.; Brandolin, Adriana; Bandoni, Jose Alberto; Biegler, L.; Large-scale dynamic optimization for grade transitions in a low density polyethylene plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 26; 2; 15-2-2002; 227-2370098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0098135401007438info:eu-repo/semantics/altIdentifier/doi/10.1016/S0098-1354(01)00743-8info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:34:53Zoai:ri.conicet.gov.ar:11336/101426instacron: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 09:34:54.139CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Large-scale dynamic optimization for grade transitions in a low density polyethylene plant
title Large-scale dynamic optimization for grade transitions in a low density polyethylene plant
spellingShingle Large-scale dynamic optimization for grade transitions in a low density polyethylene plant
Cervantes, A.M.
Optimization
Polyethylene plant
title_short Large-scale dynamic optimization for grade transitions in a low density polyethylene plant
title_full Large-scale dynamic optimization for grade transitions in a low density polyethylene plant
title_fullStr Large-scale dynamic optimization for grade transitions in a low density polyethylene plant
title_full_unstemmed Large-scale dynamic optimization for grade transitions in a low density polyethylene plant
title_sort Large-scale dynamic optimization for grade transitions in a low density polyethylene plant
dc.creator.none.fl_str_mv Cervantes, A.M.
Tonelli, S.
Brandolin, Adriana
Bandoni, Jose Alberto
Biegler, L.
author Cervantes, A.M.
author_facet Cervantes, A.M.
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 Optimization
Polyethylene plant
topic Optimization
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. The industrial process under study produces LDPE by high-pressure polymerization of ethylene in a tubular reactor using oxygen and organic peroxides as initiators. The plant produces polyethylene of different grades that require continuous changes from one steady state to another, in order to switch among the different final products. These changes generate disturbances that keep the product out of specifications during the transient states, with a consequent economic loss. The plant model consists of two parts; the first one corresponds to the tubular reactor. Here, the partial differential equations corresponding to the mass and energy dynamic balances are discretized along the distance coordinate by using finite differences. The resulting ordinary differential equations include the energy balance and individual mass balances for oxygen, peroxides, ethylene, butane, free radicals and polymer. Although, methane is also present in the plant, in the reactor model it is considered as a nonreacting impurity along with the other impurities coming from the rest of the process. The second part of the model corresponds to the rest of the plant. Here we considered four components: ethylene, butane, methane and impurities. An interesting aspect of this process is the presence of many time delays that are incorporated in the optimization model. The resulting differential algebraic equation (DAE) plant model includes over five hundred equations. The dynamic optimization problem is solved using a simultaneous nonlinear programming (NLP) approach. 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, which is applied directly to the NLP. In addition, a new mesh refinement strategy is applied to this model to confirm that no further improvement can be found in the optimal control profiles. The paper studies two cases of switching among different polymer grades, determining the optimal profiles of butane fed to the plant, in order to minimize the time to reach the steady state operation corresponding to the desired new product quality. The results are also compared with simpler model where reactor was considered as a black-box with the conversion level taken as constant data for each polymer grade. As a result, the dynamic model we developed and the solution methodology used is a flexible and practical tool to help process engineers for taking decisions during the plant operation.
Fil: Cervantes, A.M.. 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. The industrial process under study produces LDPE by high-pressure polymerization of ethylene in a tubular reactor using oxygen and organic peroxides as initiators. The plant produces polyethylene of different grades that require continuous changes from one steady state to another, in order to switch among the different final products. These changes generate disturbances that keep the product out of specifications during the transient states, with a consequent economic loss. The plant model consists of two parts; the first one corresponds to the tubular reactor. Here, the partial differential equations corresponding to the mass and energy dynamic balances are discretized along the distance coordinate by using finite differences. The resulting ordinary differential equations include the energy balance and individual mass balances for oxygen, peroxides, ethylene, butane, free radicals and polymer. Although, methane is also present in the plant, in the reactor model it is considered as a nonreacting impurity along with the other impurities coming from the rest of the process. The second part of the model corresponds to the rest of the plant. Here we considered four components: ethylene, butane, methane and impurities. An interesting aspect of this process is the presence of many time delays that are incorporated in the optimization model. The resulting differential algebraic equation (DAE) plant model includes over five hundred equations. The dynamic optimization problem is solved using a simultaneous nonlinear programming (NLP) approach. 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, which is applied directly to the NLP. In addition, a new mesh refinement strategy is applied to this model to confirm that no further improvement can be found in the optimal control profiles. The paper studies two cases of switching among different polymer grades, determining the optimal profiles of butane fed to the plant, in order to minimize the time to reach the steady state operation corresponding to the desired new product quality. The results are also compared with simpler model where reactor was considered as a black-box with the conversion level taken as constant data for each polymer grade. As a result, the dynamic model we developed and the solution methodology used is a flexible and practical tool to help process engineers for taking decisions during the plant operation.
publishDate 2002
dc.date.none.fl_str_mv 2002-02-15
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/11336/101426
Cervantes, A.M.; Tonelli, S.; Brandolin, Adriana; Bandoni, Jose Alberto; Biegler, L.; Large-scale dynamic optimization for grade transitions in a low density polyethylene plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 26; 2; 15-2-2002; 227-237
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/101426
identifier_str_mv Cervantes, A.M.; Tonelli, S.; Brandolin, Adriana; Bandoni, Jose Alberto; Biegler, L.; Large-scale dynamic optimization for grade transitions in a low density polyethylene plant; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 26; 2; 15-2-2002; 227-237
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/S0098135401007438
info:eu-repo/semantics/altIdentifier/doi/10.1016/S0098-1354(01)00743-8
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
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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)
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reponame_str CONICET Digital (CONICET)
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repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
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