A new MILP based approach for unit commitment in power production planning

Detalhes bibliográficos
Autor(a) principal: Viana, Ana
Data de Publicação: 2013
Outros Autores: Pedroso, J. P.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/3316
Resumo: This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.
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spelling A new MILP based approach for unit commitment in power production planningUnit commitmentCombinatorial optimisationMixed-integer programmingThis paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.ElsevierRepositório Científico do Instituto Politécnico do PortoViana, AnaPedroso, J. P.2014-01-13T15:55:06Z20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/3316eng0142-061510.1016/j.ijepes.2012.08.046info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T12:43:02Zoai:recipp.ipp.pt:10400.22/3316Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:24:15.173473Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A new MILP based approach for unit commitment in power production planning
title A new MILP based approach for unit commitment in power production planning
spellingShingle A new MILP based approach for unit commitment in power production planning
Viana, Ana
Unit commitment
Combinatorial optimisation
Mixed-integer programming
title_short A new MILP based approach for unit commitment in power production planning
title_full A new MILP based approach for unit commitment in power production planning
title_fullStr A new MILP based approach for unit commitment in power production planning
title_full_unstemmed A new MILP based approach for unit commitment in power production planning
title_sort A new MILP based approach for unit commitment in power production planning
author Viana, Ana
author_facet Viana, Ana
Pedroso, J. P.
author_role author
author2 Pedroso, J. P.
author2_role author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Viana, Ana
Pedroso, J. P.
dc.subject.por.fl_str_mv Unit commitment
Combinatorial optimisation
Mixed-integer programming
topic Unit commitment
Combinatorial optimisation
Mixed-integer programming
description This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01T00:00:00Z
2014-01-13T15:55:06Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/3316
url http://hdl.handle.net/10400.22/3316
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0142-0615
10.1016/j.ijepes.2012.08.046
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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