New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration

Detalhes bibliográficos
Autor(a) principal: Lujano Rojas,JM
Data de Publicação: 2016
Outros Autores: Osorio,GJ, João Catalão
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/4856
http://dx.doi.org/10.1016/j.ijepes.2015.11.064
Resumo: In this paper, a methodology to solve Unit Commitment (UC) problem from a probabilistic perspective is developed and illustrated. The method presented is based on solving the Economic Dispatch (ED) problem describing the Probability Distribution Function (PDF) of the output power of thermal generators, energy not supplied, excess of electricity, Generation Cost (GC), and Spinning Reserve (SR). The obtained ED solution is combined with Priority List (PL) method in order to solve UC problem probabilistically, giving especial attention to the probability of providing a determined amount of SR at each time step. Three case studies are analysed; the first case study explains how PDF of SR can be used as a metric to decide the amount of power that should be committed; while in the second and third case studies, two systems of 10-units and 110-units are analysed in order to evaluate the quality of the obtained solution from the proposed approach. Results are thoroughly compared to those offered by a stochastic programming approach based on mixed-integer linear programming formulation, observing a difference on GCs between 1.41% and 1.43% for the 10-units system, and between 3.75% and 4.5% for the 110-units system, depending on the chosen significance level of the probabilistic analysis.
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spelling New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integrationIn this paper, a methodology to solve Unit Commitment (UC) problem from a probabilistic perspective is developed and illustrated. The method presented is based on solving the Economic Dispatch (ED) problem describing the Probability Distribution Function (PDF) of the output power of thermal generators, energy not supplied, excess of electricity, Generation Cost (GC), and Spinning Reserve (SR). The obtained ED solution is combined with Priority List (PL) method in order to solve UC problem probabilistically, giving especial attention to the probability of providing a determined amount of SR at each time step. Three case studies are analysed; the first case study explains how PDF of SR can be used as a metric to decide the amount of power that should be committed; while in the second and third case studies, two systems of 10-units and 110-units are analysed in order to evaluate the quality of the obtained solution from the proposed approach. Results are thoroughly compared to those offered by a stochastic programming approach based on mixed-integer linear programming formulation, observing a difference on GCs between 1.41% and 1.43% for the 10-units system, and between 3.75% and 4.5% for the 110-units system, depending on the chosen significance level of the probabilistic analysis.2017-12-22T18:37:47Z2016-01-01T00:00:00Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/4856http://dx.doi.org/10.1016/j.ijepes.2015.11.064engLujano Rojas,JMOsorio,GJJoão Catalãoinfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:36Zoai:repositorio.inesctec.pt:123456789/4856Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:53:22.843614Repositório 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 New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration
title New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration
spellingShingle New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration
Lujano Rojas,JM
title_short New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration
title_full New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration
title_fullStr New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration
title_full_unstemmed New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration
title_sort New probabilistic method for solving economic dispatch and unit commitment problems incorporating uncertainty due to renewable energy integration
author Lujano Rojas,JM
author_facet Lujano Rojas,JM
Osorio,GJ
João Catalão
author_role author
author2 Osorio,GJ
João Catalão
author2_role author
author
dc.contributor.author.fl_str_mv Lujano Rojas,JM
Osorio,GJ
João Catalão
description In this paper, a methodology to solve Unit Commitment (UC) problem from a probabilistic perspective is developed and illustrated. The method presented is based on solving the Economic Dispatch (ED) problem describing the Probability Distribution Function (PDF) of the output power of thermal generators, energy not supplied, excess of electricity, Generation Cost (GC), and Spinning Reserve (SR). The obtained ED solution is combined with Priority List (PL) method in order to solve UC problem probabilistically, giving especial attention to the probability of providing a determined amount of SR at each time step. Three case studies are analysed; the first case study explains how PDF of SR can be used as a metric to decide the amount of power that should be committed; while in the second and third case studies, two systems of 10-units and 110-units are analysed in order to evaluate the quality of the obtained solution from the proposed approach. Results are thoroughly compared to those offered by a stochastic programming approach based on mixed-integer linear programming formulation, observing a difference on GCs between 1.41% and 1.43% for the 10-units system, and between 3.75% and 4.5% for the 110-units system, depending on the chosen significance level of the probabilistic analysis.
publishDate 2016
dc.date.none.fl_str_mv 2016-01-01T00:00:00Z
2016
2017-12-22T18:37:47Z
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http://dx.doi.org/10.1016/j.ijepes.2015.11.064
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http://dx.doi.org/10.1016/j.ijepes.2015.11.064
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