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dc.contributor.advisorOliveira Fuster, Gabriel
dc.contributor.authorJiménez Mares, Jamer
dc.date.accessioned2021-06-22T21:56:05Z
dc.date.available2021-06-22T21:56:05Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/10584/9652
dc.description.abstractThe power consumption in buildings represents a 30-40% of the final energy usage, hence it is necessary to minimize the power consumption by optimizing the operation of several loads without impacting in the customer’s comfort. According to the above in this work an intelligent approach framing in a management model is presented for the power consumption management of devices taking into account some variables as indoor temperature, outdoor temperature, illuminance and presence. Furthermore, in this research the integration of several Demand Side Management (DSM) criteria with one criterion based on neural networks and other inspired on differential tariff is carried out through dynamic and intelligent selections according to variables performance and customer´s preferences, e.g. priority list of criteria, operation based on comfort or consumption, in addition to other preferences as temperature. Likewise, a previous diagnosis analysis through energy audit is carried out to evaluate devices performance and customer habits. Experimental testing to the proposed approach has been performed in an environment object of study with the consumption data base and its performance tested in simulations runs. The testing results show that energy savings can be achieved through of recommendations provided by energy audit and proposed states by dynamic manager.
dc.formatapplication/pdfes_ES
dc.language.isoenges_ES
dc.publisherUniversidad del Nortees_ES
dc.titleManagement model for energy efficiency - Intelligent System moduleen_US
dc.typeTrabajo de grado - Maestríaes_ES
dc.publisher.programMaestría en Ingeniería Electrónicaes_ES
dc.publisher.departmentDepartamento de eléctrica y electrónicaes_ES
dc.description.degreelevelMaestríaes_ES
dc.publisher.placeBarranquilla, Colombiaes_ES
dc.rights.creativecommonshttps://creativecommons.org/licenses/by/4.0/es_ES
dc.type.coarhttp://purl.org/coar/resource_type/c_bdcces_ES
dc.type.driverinfo:eu-repo/semantics/masterThesises_ES
dc.type.contentTextes_ES
dc.type.versioninfo:eu-repo/semantics/updatedVersiones_ES
oaire.versionhttp://purl.org/coar/version/c_ab4af688f83e57aaes_ES
dc.description.degreenameMagister en Ingeniería Electrónicaes_ES
oaire.accessrightshttp://purl.org/coar/access_right/c_abf2es_ES
dcterms.audience.educationalcontextInvestigadoreses_ES
dcterms.audience.educationalcontextEstudianteses_ES
dcterms.audience.educationalcontextMaestroses_ES
dc.subject.lembInteligencia computacional
dc.subject.lembElectrónica -- Mediciones
dc.subject.lembEdificios -- Abastecimiento de energía
dcterms.audience.professionaldevelopmentMaestríaes_ES
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses_ES


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