Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events

Detalhes bibliográficos
Autor(a) principal: Mota, Bruno
Data de Publicação: 2021
Outros Autores: Gomes, Luis, Faria, Pedro, Ramos, Carlos, Vale, Zita, Correia, Regina
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/16757
Resumo: This article belongs to the Special Issue The Artificial Intelligence Technologies for Electric Power Systems
id RCAP_deeffb2f3db75436c7e801279d0d4a5a
oai_identifier_str oai:recipp.ipp.pt:10400.22/16757
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Production Line Optimization to Minimize Energy Cost and Participate in Demand Response EventsDemand-side managementDemand responseFlexibilityGenetic algorithmProduction lineTasks schedulingThis article belongs to the Special Issue The Artificial Intelligence Technologies for Electric Power SystemsThe scheduling of tasks in a production line is a complex problem that needs to take into account several constraints, such as product deadlines and machine limitations. With innovative focus, the main constraint that will be addressed in this paper, and that usually is not considered, is the energy consumption cost in the production line. For that, an approach based on genetic algorithms is proposed and implemented. The use of local energy generation, especially from renewable sources, and the possibility of having multiple energy providers allow the user to manage its consumption according to energy prices and energy availability. The proposed solution takes into account the energy availability of renewable sources and energy prices to optimize the scheduling of a production line using a genetic algorithm with multiple constraints. The proposed algorithm also enables a production line to participate in demand response events by shifting its production, by using the flexibility of production lines. A case study using real production data that represents a textile industry is presented, where the tasks for six days are scheduled. During the week, a demand response event is launched, and the proposed algorithm shifts the consumption by changing task orders and machine usage.This work has received funding from Portugal 2020 under SPEAR project (NORTE-01-0247-FEDER-040224) and from FEDER Funds through COMPETE program and from National Funds through (FCT) under the project UIDB/00760/2020, and CEECIND/02887/2017.Repositório Científico do Instituto Politécnico do PortoMota, BrunoGomes, LuisFaria, PedroRamos, CarlosVale, ZitaCorreia, Regina2021-01-27T11:52:57Z20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/16757eng1996-107310.3390/en14020462info: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:RCAAP2023-03-13T13:03:55Zoai:recipp.ipp.pt:10400.22/16757Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:36:23.331597Repositório 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 Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events
title Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events
spellingShingle Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events
Mota, Bruno
Demand-side management
Demand response
Flexibility
Genetic algorithm
Production line
Tasks scheduling
title_short Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events
title_full Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events
title_fullStr Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events
title_full_unstemmed Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events
title_sort Production Line Optimization to Minimize Energy Cost and Participate in Demand Response Events
author Mota, Bruno
author_facet Mota, Bruno
Gomes, Luis
Faria, Pedro
Ramos, Carlos
Vale, Zita
Correia, Regina
author_role author
author2 Gomes, Luis
Faria, Pedro
Ramos, Carlos
Vale, Zita
Correia, Regina
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Mota, Bruno
Gomes, Luis
Faria, Pedro
Ramos, Carlos
Vale, Zita
Correia, Regina
dc.subject.por.fl_str_mv Demand-side management
Demand response
Flexibility
Genetic algorithm
Production line
Tasks scheduling
topic Demand-side management
Demand response
Flexibility
Genetic algorithm
Production line
Tasks scheduling
description This article belongs to the Special Issue The Artificial Intelligence Technologies for Electric Power Systems
publishDate 2021
dc.date.none.fl_str_mv 2021-01-27T11:52:57Z
2021
2021-01-01T00:00:00Z
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/10400.22/16757
url http://hdl.handle.net/10400.22/16757
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1996-1073
10.3390/en14020462
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.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
_version_ 1799131454912856064

Registros relacionados