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dc.contributor.authorCárdenas Araújo, Juan José
dc.contributor.authorGarcía Espinosa, Antonio
dc.contributor.authorRomeral Martínez, José Luis
dc.contributor.authorUrresty Betancourt, Julio César
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Elèctrica
dc.date.accessioned2012-02-17T15:21:59Z
dc.date.available2012-02-17T15:21:59Z
dc.date.created2009
dc.date.issued2009
dc.identifier.citationCardenas, J. [et al.]. A multi-objective GA to demand-side management in an automated warehouse. A: IEEE International Conference on Emerging Technologies and Factory Automation. "Emerging Technologies & Factory Automation, 2009. ETFA 2009. IEEE Conference on". Mallorca: 2009, p. 1-7.
dc.identifier.isbn1946-0759
dc.identifier.urihttp://hdl.handle.net/2117/15222
dc.description.abstractThe simultaneous operation of the automated storage and retrieval machines (ASRs) in an automated warehouse can increase the likelihood that high power demand peaks turn unstable the electric system. Furthermore, high power peaks mean the need for more electrical power contracted, which in turns leads to more fixed operation cost and inefficient use of the electrical installations. In this context, we present a multi-objective genetic algorithm approach (MOGA) to implement demand-side management (DSM) in an automated warehouse. It works minimizing the total energy demand, but without increasing substantially the time for the operation. Simulations show the performances of the new approach.
dc.format.extent7 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Energies::Energia elèctrica::Automatització i control de l'energia elèctrica
dc.subject.lcshMOGA
dc.subject.lcshGenetic algorithms
dc.subject.lcshDemand-side management (Electric utilities)
dc.subject.lcshWarehouses -- Management -- Automatic control
dc.titleA multi-objective GA to demand-side management in an automated warehouse
dc.typeConference report
dc.subject.lemacAlgorismes genètics
dc.subject.lemacEnergia elèctrica -- Demanda
dc.subject.lemacMagatzems -- Control automàtic
dc.contributor.groupUniversitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://cataleg.upc.edu/record=b1315235~S1*cat
dc.rights.accessOpen Access
drac.iddocument5846483
dc.description.versionPostprint (published version)
upcommons.citation.authorCardenas, J.; Garcia, A.; Romeral, L.; Urresty, J.
upcommons.citation.contributorIEEE International Conference on Emerging Technologies and Factory Automation
upcommons.citation.pubplaceMallorca
upcommons.citation.publishedtrue
upcommons.citation.publicationNameEmerging Technologies & Factory Automation, 2009. ETFA 2009. IEEE Conference on
upcommons.citation.startingPage1
upcommons.citation.endingPage7


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