Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition

Detalhes bibliográficos
Autor(a) principal: Almeida, José
Data de Publicação: 2022
Outros Autores: Lezama, Fernando, Soares, João, Vale, Zita, Canizes, Bruno
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/22463
Resumo: In this paper, multiple evolutionary algorithms are applied to solve an energy resource management problem in the day-ahead context involving a risk-based analysis corresponding to the proposed 2022 competition on evolutionary computation. We test numerous evolutionary algorithms for a risk-averse day-ahead operation to show preliminary results for the competition. We use evolutionary computation to follow the competition guidelines. Results show that the HyDE algorithm obtains a better solution with lesser costs when compared to the other tested algorithm due to the minimization of worst-scenario impact.
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spelling Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competitionComputing methodologiesSearch methodologiesApplied computingEngineeringIn this paper, multiple evolutionary algorithms are applied to solve an energy resource management problem in the day-ahead context involving a risk-based analysis corresponding to the proposed 2022 competition on evolutionary computation. We test numerous evolutionary algorithms for a risk-averse day-ahead operation to show preliminary results for the competition. We use evolutionary computation to follow the competition guidelines. Results show that the HyDE algorithm obtains a better solution with lesser costs when compared to the other tested algorithm due to the minimization of worst-scenario impact.This research has received funding from FEDER funds through the Operational Programme for Competitiveness and Internationaliza- tion (COMPETE 2020), under Project POCI-01-0145-FEDER-028983; by National Funds through the FCT Portuguese Foundation for Science and Technology, under Projects PTDC/EEI-EEE/28983/2017 (CENERGETIC), CEECIND/02814/2017, UIDB/000760/2020, and UIDP/00760/2020ACMRepositório Científico do Instituto Politécnico do PortoAlmeida, JoséLezama, FernandoSoares, JoãoVale, ZitaCanizes, Bruno2023-03-14T09:28:38Z20222022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/22463eng978-1-4503-9268-610.1145/3520304.3535080info: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:RCAAP2023-03-22T01:46:51Zoai:recipp.ipp.pt:10400.22/22463Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:42:34.091996Repositório 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 Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition
title Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition
spellingShingle Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition
Almeida, José
Computing methodologies
Search methodologies
Applied computing
Engineering
title_short Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition
title_full Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition
title_fullStr Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition
title_full_unstemmed Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition
title_sort Preliminary results of advanced heuristic optimization in the risk-based energy scheduling competition
author Almeida, José
author_facet Almeida, José
Lezama, Fernando
Soares, João
Vale, Zita
Canizes, Bruno
author_role author
author2 Lezama, Fernando
Soares, João
Vale, Zita
Canizes, Bruno
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Almeida, José
Lezama, Fernando
Soares, João
Vale, Zita
Canizes, Bruno
dc.subject.por.fl_str_mv Computing methodologies
Search methodologies
Applied computing
Engineering
topic Computing methodologies
Search methodologies
Applied computing
Engineering
description In this paper, multiple evolutionary algorithms are applied to solve an energy resource management problem in the day-ahead context involving a risk-based analysis corresponding to the proposed 2022 competition on evolutionary computation. We test numerous evolutionary algorithms for a risk-averse day-ahead operation to show preliminary results for the competition. We use evolutionary computation to follow the competition guidelines. Results show that the HyDE algorithm obtains a better solution with lesser costs when compared to the other tested algorithm due to the minimization of worst-scenario impact.
publishDate 2022
dc.date.none.fl_str_mv 2022
2022-01-01T00:00:00Z
2023-03-14T09:28:38Z
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/10400.22/22463
url http://hdl.handle.net/10400.22/22463
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-1-4503-9268-6
10.1145/3520304.3535080
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 ACM
publisher.none.fl_str_mv ACM
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
repository.mail.fl_str_mv
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