Dynamic constrained coalition formation among electric vehicles
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/194459 |
Resumo: | Background: The use of electric vehicles (EVs) and vehicle-to-grid (V2G) technologies have been advocated as an efficient way to reduce the intermittency of renewable energy sources in smart grids. However, operating on V2G sessions in a cost-effective way is not a trivial task for EVs. The formation of coalitions among EVs has been proposed to tackle this problem. Methods: In this paper we introduce Dynamic Constrained Coalition Formation (DCCF), which is a distributed heuristic-based method for constrained coalition structure generation (CSG) in dynamic environments. In our approach, coalitions are formed observing constraints imposed by the grid. To this end, EV agents negotiate the formation of feasible coalitions among themselves. Results: Based on experiments, we show that DCCF is efficient to provide good solutions in a fast way. DCCF provides solutions whose quality approaches 98% of the optimum. In dynamically changing scenarios, DCCF also shows good results, keeping the agents payoff stable along time. Conclusions: Essentially, DCCF’s main advantage over traditional CSG algorithms is that its computational effort is very lower. On the other hand, unlike traditional algorithms, DCCF is suitable only for constraint-based problems. |
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Ramos, Gabriel de OliveiraBurguillo, Juan C.Bazzan, Ana Lucia Cetertich2019-05-21T02:37:47Z20140104-6500http://hdl.handle.net/10183/194459000985278Background: The use of electric vehicles (EVs) and vehicle-to-grid (V2G) technologies have been advocated as an efficient way to reduce the intermittency of renewable energy sources in smart grids. However, operating on V2G sessions in a cost-effective way is not a trivial task for EVs. The formation of coalitions among EVs has been proposed to tackle this problem. Methods: In this paper we introduce Dynamic Constrained Coalition Formation (DCCF), which is a distributed heuristic-based method for constrained coalition structure generation (CSG) in dynamic environments. In our approach, coalitions are formed observing constraints imposed by the grid. To this end, EV agents negotiate the formation of feasible coalitions among themselves. Results: Based on experiments, we show that DCCF is efficient to provide good solutions in a fast way. DCCF provides solutions whose quality approaches 98% of the optimum. In dynamically changing scenarios, DCCF also shows good results, keeping the agents payoff stable along time. Conclusions: Essentially, DCCF’s main advantage over traditional CSG algorithms is that its computational effort is very lower. On the other hand, unlike traditional algorithms, DCCF is suitable only for constraint-based problems.application/pdfengJournal of the brazilian computer society. Rio de Janeiro, RJ. Vol. 20, no. 1, art. 8 (Dec. 2014), [15] f.Inteligência artificialInformatica : TransportesArtificial intelligenceSmart gridsMultiagent systemsGame theoryDynamic constrained coalition formation among electric vehiclesinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/otherinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT000985278.pdf.txt000985278.pdf.txtExtracted Texttext/plain60917http://www.lume.ufrgs.br/bitstream/10183/194459/2/000985278.pdf.txte9eb4cadc0e8e4a1e36e8b6c29449e36MD52ORIGINAL000985278.pdfTexto completo (inglês)application/pdf1278014http://www.lume.ufrgs.br/bitstream/10183/194459/1/000985278.pdfd508b58a1ce3258aebad8b970930076aMD5110183/1944592019-05-22 02:38:41.175408oai:www.lume.ufrgs.br:10183/194459Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2019-05-22T05:38:41Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Dynamic constrained coalition formation among electric vehicles |
title |
Dynamic constrained coalition formation among electric vehicles |
spellingShingle |
Dynamic constrained coalition formation among electric vehicles Ramos, Gabriel de Oliveira Inteligência artificial Informatica : Transportes Artificial intelligence Smart grids Multiagent systems Game theory |
title_short |
Dynamic constrained coalition formation among electric vehicles |
title_full |
Dynamic constrained coalition formation among electric vehicles |
title_fullStr |
Dynamic constrained coalition formation among electric vehicles |
title_full_unstemmed |
Dynamic constrained coalition formation among electric vehicles |
title_sort |
Dynamic constrained coalition formation among electric vehicles |
author |
Ramos, Gabriel de Oliveira |
author_facet |
Ramos, Gabriel de Oliveira Burguillo, Juan C. Bazzan, Ana Lucia Cetertich |
author_role |
author |
author2 |
Burguillo, Juan C. Bazzan, Ana Lucia Cetertich |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Ramos, Gabriel de Oliveira Burguillo, Juan C. Bazzan, Ana Lucia Cetertich |
dc.subject.por.fl_str_mv |
Inteligência artificial Informatica : Transportes |
topic |
Inteligência artificial Informatica : Transportes Artificial intelligence Smart grids Multiagent systems Game theory |
dc.subject.eng.fl_str_mv |
Artificial intelligence Smart grids Multiagent systems Game theory |
description |
Background: The use of electric vehicles (EVs) and vehicle-to-grid (V2G) technologies have been advocated as an efficient way to reduce the intermittency of renewable energy sources in smart grids. However, operating on V2G sessions in a cost-effective way is not a trivial task for EVs. The formation of coalitions among EVs has been proposed to tackle this problem. Methods: In this paper we introduce Dynamic Constrained Coalition Formation (DCCF), which is a distributed heuristic-based method for constrained coalition structure generation (CSG) in dynamic environments. In our approach, coalitions are formed observing constraints imposed by the grid. To this end, EV agents negotiate the formation of feasible coalitions among themselves. Results: Based on experiments, we show that DCCF is efficient to provide good solutions in a fast way. DCCF provides solutions whose quality approaches 98% of the optimum. In dynamically changing scenarios, DCCF also shows good results, keeping the agents payoff stable along time. Conclusions: Essentially, DCCF’s main advantage over traditional CSG algorithms is that its computational effort is very lower. On the other hand, unlike traditional algorithms, DCCF is suitable only for constraint-based problems. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014 |
dc.date.accessioned.fl_str_mv |
2019-05-21T02:37:47Z |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/other |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
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publishedVersion |
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http://hdl.handle.net/10183/194459 |
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0104-6500 |
dc.identifier.nrb.pt_BR.fl_str_mv |
000985278 |
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http://hdl.handle.net/10183/194459 |
dc.language.iso.fl_str_mv |
eng |
language |
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dc.relation.ispartof.pt_BR.fl_str_mv |
Journal of the brazilian computer society. Rio de Janeiro, RJ. Vol. 20, no. 1, art. 8 (Dec. 2014), [15] f. |
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info:eu-repo/semantics/openAccess |
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