Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets

Autores
Alemany, Juan Manuel; Kasprzyk, Leszek; Magnago, Fernando
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Mixed integer linear programming is one of the main approaches used to solve unit commitment problems. Due to the computational complexity of unit commitment problems, several researches remark the benefits of using less binary variables or relaxing them for the branch-and-cut algorithm. However, integrality constraints relaxation seems to be case dependent because there are many instances where applying it may not improve the computational burden. In addition, there is a lack of extensive numerical experiments evaluating the effects of the relaxation of binary variables in mixed integer linear programming based unit commitment. Therefore, the primary purpose of this work is to analyze the effects of binary variables and compare different relaxations, supported by extensive computational experiments. To accomplish this objective, two power systems are used for the numerical tests: the IEEE118 test system and a very large scale real system. The results suggest that a direct link between the relaxation of binary variables and computational burden cannot be easily assured in the general case. Therefore, relaxing binary variables should not be used as a general rule-of-practice to improve computational burden, at least, until each particular model is tested under different load scenarios and formulations to quantify the final effects of binary variables on the specific UC implementation. The secondary aim of this work is to give some preliminary insight into the reasons that could be supporting the binary relaxation in some UC instances.
Fil: Alemany, Juan Manuel. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Kasprzyk, Leszek. Poznan University of Technology. Institute of Electrical and Electronics Industry; Polonia
Fil: Magnago, Fernando. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Nexant Inc; Estados Unidos
Materia
BINARY VARIABLES RELAXATION
BRANCH AND CUT ALGORITHM
DAY-AHEAD ELECTRICITY MARKET CLEARING
MIXED INTEGER LINEAR PROGRAMMING
UNIT COMMITMENT
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:11336/138907
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity marketsAlemany, Juan ManuelKasprzyk, LeszekMagnago, FernandoBINARY VARIABLES RELAXATIONBRANCH AND CUT ALGORITHMDAY-AHEAD ELECTRICITY MARKET CLEARINGMIXED INTEGER LINEAR PROGRAMMINGUNIT COMMITMENThttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Mixed integer linear programming is one of the main approaches used to solve unit commitment problems. Due to the computational complexity of unit commitment problems, several researches remark the benefits of using less binary variables or relaxing them for the branch-and-cut algorithm. However, integrality constraints relaxation seems to be case dependent because there are many instances where applying it may not improve the computational burden. In addition, there is a lack of extensive numerical experiments evaluating the effects of the relaxation of binary variables in mixed integer linear programming based unit commitment. Therefore, the primary purpose of this work is to analyze the effects of binary variables and compare different relaxations, supported by extensive computational experiments. To accomplish this objective, two power systems are used for the numerical tests: the IEEE118 test system and a very large scale real system. The results suggest that a direct link between the relaxation of binary variables and computational burden cannot be easily assured in the general case. Therefore, relaxing binary variables should not be used as a general rule-of-practice to improve computational burden, at least, until each particular model is tested under different load scenarios and formulations to quantify the final effects of binary variables on the specific UC implementation. The secondary aim of this work is to give some preliminary insight into the reasons that could be supporting the binary relaxation in some UC instances.Fil: Alemany, Juan Manuel. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Kasprzyk, Leszek. Poznan University of Technology. Institute of Electrical and Electronics Industry; PoloniaFil: Magnago, Fernando. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Nexant Inc; Estados UnidosElsevier Science SA2018-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/138907Alemany, Juan Manuel; Kasprzyk, Leszek; Magnago, Fernando; Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets; Elsevier Science SA; Electric Power Systems Research; 160; 7-2018; 429-4380378-7796CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.epsr.2018.03.019info:eu-repo/semantics/altIdentifier/url/http://linkinghub.elsevier.com/retrieve/pii/S0378779618300919info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:38:59Zoai:ri.conicet.gov.ar:11336/138907instacron: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 09:38:59.765CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets
title Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets
spellingShingle Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets
Alemany, Juan Manuel
BINARY VARIABLES RELAXATION
BRANCH AND CUT ALGORITHM
DAY-AHEAD ELECTRICITY MARKET CLEARING
MIXED INTEGER LINEAR PROGRAMMING
UNIT COMMITMENT
title_short Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets
title_full Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets
title_fullStr Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets
title_full_unstemmed Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets
title_sort Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets
dc.creator.none.fl_str_mv Alemany, Juan Manuel
Kasprzyk, Leszek
Magnago, Fernando
author Alemany, Juan Manuel
author_facet Alemany, Juan Manuel
Kasprzyk, Leszek
Magnago, Fernando
author_role author
author2 Kasprzyk, Leszek
Magnago, Fernando
author2_role author
author
dc.subject.none.fl_str_mv BINARY VARIABLES RELAXATION
BRANCH AND CUT ALGORITHM
DAY-AHEAD ELECTRICITY MARKET CLEARING
MIXED INTEGER LINEAR PROGRAMMING
UNIT COMMITMENT
topic BINARY VARIABLES RELAXATION
BRANCH AND CUT ALGORITHM
DAY-AHEAD ELECTRICITY MARKET CLEARING
MIXED INTEGER LINEAR PROGRAMMING
UNIT COMMITMENT
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Mixed integer linear programming is one of the main approaches used to solve unit commitment problems. Due to the computational complexity of unit commitment problems, several researches remark the benefits of using less binary variables or relaxing them for the branch-and-cut algorithm. However, integrality constraints relaxation seems to be case dependent because there are many instances where applying it may not improve the computational burden. In addition, there is a lack of extensive numerical experiments evaluating the effects of the relaxation of binary variables in mixed integer linear programming based unit commitment. Therefore, the primary purpose of this work is to analyze the effects of binary variables and compare different relaxations, supported by extensive computational experiments. To accomplish this objective, two power systems are used for the numerical tests: the IEEE118 test system and a very large scale real system. The results suggest that a direct link between the relaxation of binary variables and computational burden cannot be easily assured in the general case. Therefore, relaxing binary variables should not be used as a general rule-of-practice to improve computational burden, at least, until each particular model is tested under different load scenarios and formulations to quantify the final effects of binary variables on the specific UC implementation. The secondary aim of this work is to give some preliminary insight into the reasons that could be supporting the binary relaxation in some UC instances.
Fil: Alemany, Juan Manuel. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Kasprzyk, Leszek. Poznan University of Technology. Institute of Electrical and Electronics Industry; Polonia
Fil: Magnago, Fernando. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Departamento de Electricidad y Electrónica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina. Nexant Inc; Estados Unidos
description Mixed integer linear programming is one of the main approaches used to solve unit commitment problems. Due to the computational complexity of unit commitment problems, several researches remark the benefits of using less binary variables or relaxing them for the branch-and-cut algorithm. However, integrality constraints relaxation seems to be case dependent because there are many instances where applying it may not improve the computational burden. In addition, there is a lack of extensive numerical experiments evaluating the effects of the relaxation of binary variables in mixed integer linear programming based unit commitment. Therefore, the primary purpose of this work is to analyze the effects of binary variables and compare different relaxations, supported by extensive computational experiments. To accomplish this objective, two power systems are used for the numerical tests: the IEEE118 test system and a very large scale real system. The results suggest that a direct link between the relaxation of binary variables and computational burden cannot be easily assured in the general case. Therefore, relaxing binary variables should not be used as a general rule-of-practice to improve computational burden, at least, until each particular model is tested under different load scenarios and formulations to quantify the final effects of binary variables on the specific UC implementation. The secondary aim of this work is to give some preliminary insight into the reasons that could be supporting the binary relaxation in some UC instances.
publishDate 2018
dc.date.none.fl_str_mv 2018-07
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/11336/138907
Alemany, Juan Manuel; Kasprzyk, Leszek; Magnago, Fernando; Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets; Elsevier Science SA; Electric Power Systems Research; 160; 7-2018; 429-438
0378-7796
CONICET Digital
CONICET
url http://hdl.handle.net/11336/138907
identifier_str_mv Alemany, Juan Manuel; Kasprzyk, Leszek; Magnago, Fernando; Effects of binary variables in mixed integer linear programming based unit commitment in large-scale electricity markets; Elsevier Science SA; Electric Power Systems Research; 160; 7-2018; 429-438
0378-7796
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.epsr.2018.03.019
info:eu-repo/semantics/altIdentifier/url/http://linkinghub.elsevier.com/retrieve/pii/S0378779618300919
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 Elsevier Science SA
publisher.none.fl_str_mv Elsevier Science SA
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 13.070432

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