Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Detalhes bibliográficos
Autor(a) principal: Canizes, Bruno
Data de Publicação: 2013
Outros Autores: Soares, João, Faria, Pedro, Vale, Zita
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/3396
Resumo: Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.
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spelling Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity marketsAncillary servicesArtificial neural networksElectricity marketsLinear programmingMixed integer non-linear programmingPower systemsAncillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.ElsevierRepositório Científico do Instituto Politécnico do PortoCanizes, BrunoSoares, JoãoFaria, PedroVale, Zita2014-01-21T12:39:19Z20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/3396eng0306-261910.1016/j.apenergy.2013.03.031info: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:RCAAP2023-03-13T12:43:12Zoai:recipp.ipp.pt:10400.22/3396Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:24:24.162137Repositório 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 Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
title Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
spellingShingle Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
Canizes, Bruno
Ancillary services
Artificial neural networks
Electricity markets
Linear programming
Mixed integer non-linear programming
Power systems
title_short Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
title_full Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
title_fullStr Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
title_full_unstemmed Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
title_sort Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets
author Canizes, Bruno
author_facet Canizes, Bruno
Soares, João
Faria, Pedro
Vale, Zita
author_role author
author2 Soares, João
Faria, Pedro
Vale, Zita
author2_role author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Canizes, Bruno
Soares, João
Faria, Pedro
Vale, Zita
dc.subject.por.fl_str_mv Ancillary services
Artificial neural networks
Electricity markets
Linear programming
Mixed integer non-linear programming
Power systems
topic Ancillary services
Artificial neural networks
Electricity markets
Linear programming
Mixed integer non-linear programming
Power systems
description Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01T00:00:00Z
2014-01-21T12:39:19Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/3396
url http://hdl.handle.net/10400.22/3396
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0306-2619
10.1016/j.apenergy.2013.03.031
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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