Production scheduling optimization for power-intensive processes with time-sensitive electricity prices

Autores
Basán, Natalia; Méndez, Carlos A.
Año de publicación
2016
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Continuous power-intensive processes in air separation plant can take advantage of optimal production planning to reduce the consumption of electricity. In this work a solution approach is developed based on a discrete-time scheduling formulation that allows modeling and optimizing operating decisions either in a fixed or a rolling horizon scheme. The main goal of this contribution is to find an optimal hourly schedule for next week that minimizes total energy consumption cost while satisfying all operational constraints. The MILP model is tested on real-world electricity price and demand input data. The results show optimal solutions for the proposed methodology with a modest computational effort considering a one-hour time grid and one-week time horizon.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
Scheduling
continuous power-intensive processes
air separation plant
energy consumption cost
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/58392
Acceder
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network_name_str SEDICI (UNLP)
spelling Production scheduling optimization for power-intensive processes with time-sensitive electricity pricesBasán, NataliaMéndez, Carlos A.Ciencias InformáticasSchedulingcontinuous power-intensive processesair separation plantenergy consumption costContinuous power-intensive processes in air separation plant can take advantage of optimal production planning to reduce the consumption of electricity. In this work a solution approach is developed based on a discrete-time scheduling formulation that allows modeling and optimizing operating decisions either in a fixed or a rolling horizon scheme. The main goal of this contribution is to find an optimal hourly schedule for next week that minimizes total energy consumption cost while satisfying all operational constraints. The MILP model is tested on real-world electricity price and demand input data. The results show optimal solutions for the proposed methodology with a modest computational effort considering a one-hour time grid and one-week time horizon.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2016-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf61-70http://sedici.unlp.edu.ar/handle/10915/58392enginfo:eu-repo/semantics/altIdentifier/url/http://45jaiio.sadio.org.ar/sites/default/files/1577-4988-1-DR_0.pdfinfo:eu-repo/semantics/altIdentifier/issn/2451-7542info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-sa/3.0/Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T09:50:06Zoai:sedici.unlp.edu.ar:10915/58392Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 09:50:06.774SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Production scheduling optimization for power-intensive processes with time-sensitive electricity prices
title Production scheduling optimization for power-intensive processes with time-sensitive electricity prices
spellingShingle Production scheduling optimization for power-intensive processes with time-sensitive electricity prices
Basán, Natalia
Ciencias Informáticas
Scheduling
continuous power-intensive processes
air separation plant
energy consumption cost
title_short Production scheduling optimization for power-intensive processes with time-sensitive electricity prices
title_full Production scheduling optimization for power-intensive processes with time-sensitive electricity prices
title_fullStr Production scheduling optimization for power-intensive processes with time-sensitive electricity prices
title_full_unstemmed Production scheduling optimization for power-intensive processes with time-sensitive electricity prices
title_sort Production scheduling optimization for power-intensive processes with time-sensitive electricity prices
dc.creator.none.fl_str_mv Basán, Natalia
Méndez, Carlos A.
author Basán, Natalia
author_facet Basán, Natalia
Méndez, Carlos A.
author_role author
author2 Méndez, Carlos A.
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Scheduling
continuous power-intensive processes
air separation plant
energy consumption cost
topic Ciencias Informáticas
Scheduling
continuous power-intensive processes
air separation plant
energy consumption cost
dc.description.none.fl_txt_mv Continuous power-intensive processes in air separation plant can take advantage of optimal production planning to reduce the consumption of electricity. In this work a solution approach is developed based on a discrete-time scheduling formulation that allows modeling and optimizing operating decisions either in a fixed or a rolling horizon scheme. The main goal of this contribution is to find an optimal hourly schedule for next week that minimizes total energy consumption cost while satisfying all operational constraints. The MILP model is tested on real-world electricity price and demand input data. The results show optimal solutions for the proposed methodology with a modest computational effort considering a one-hour time grid and one-week time horizon.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description Continuous power-intensive processes in air separation plant can take advantage of optimal production planning to reduce the consumption of electricity. In this work a solution approach is developed based on a discrete-time scheduling formulation that allows modeling and optimizing operating decisions either in a fixed or a rolling horizon scheme. The main goal of this contribution is to find an optimal hourly schedule for next week that minimizes total energy consumption cost while satisfying all operational constraints. The MILP model is tested on real-world electricity price and demand input data. The results show optimal solutions for the proposed methodology with a modest computational effort considering a one-hour time grid and one-week time horizon.
publishDate 2016
dc.date.none.fl_str_mv 2016-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/58392
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/2451-7542
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
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Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-sa/3.0/
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dc.format.none.fl_str_mv application/pdf
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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