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Genetic algorithm methodology applied to intelligent house control

dc.contributor.authorFernandes, Filipe
dc.contributor.authorSousa, Tiago
dc.contributor.authorSilva, Marco
dc.contributor.authorMorais, H.
dc.contributor.authorVale, Zita
dc.contributor.authorFaria, Pedro
dc.date.accessioned2013-04-19T10:25:22Z
dc.date.available2013-04-19T10:25:22Z
dc.date.issued2011
dc.date.updated2013-04-12T15:57:37Z
dc.description.abstractIn recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.por
dc.identifierDOI 10.1109/CIASG.2011.5953341
dc.identifier.isbn978-1-4244-9893-2
dc.identifier.urihttp://hdl.handle.net/10400.22/1419
dc.language.isoengpor
dc.publisherIEEEpor
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5953341por
dc.subjectArtificial intelligencepor
dc.subjectGenetic algorithmpor
dc.subjectMixed- integer non-linear programmingpor
dc.subjectSCADApor
dc.subjectSmart gridpor
dc.titleGenetic algorithm methodology applied to intelligent house controlpor
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceParis, French Guiana, 2011por
oaire.citation.titleIn Smart Grid - Part Of 17273 - 2011 Ssci, IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG)por
person.familyNameFernandes
person.familyNameVale
person.familyNameFaria
person.givenNameFilipe
person.givenNameZita
person.givenNamePedro
person.identifier632184
person.identifier.ciencia-id721B-B0EB-7141
person.identifier.ciencia-idB212-2309-F9C3
person.identifier.orcid0000-0002-4642-6950
person.identifier.orcid0000-0002-4560-9544
person.identifier.orcid0000-0002-5982-8342
person.identifier.ridA-5824-2012
person.identifier.scopus-author-id7004115775
rcaap.rightsclosedAccesspor
rcaap.typeconferenceObjectpor
relation.isAuthorOfPublication3a332ccf-4cef-4f64-8afa-cce8373191b2
relation.isAuthorOfPublicationff1df02d-0c0f-4db1-bf7d-78863a99420b
relation.isAuthorOfPublication35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6
relation.isAuthorOfPublication.latestForDiscovery35e6a4ab-f644-4bc5-b6fc-9fd89c23d6c6

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