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dc.contributor.authorBustamante Sánchez, Sergio 
dc.contributor.authorCastro Alonso, Pablo Bernardo 
dc.contributor.authorLaso Pérez, Alberto 
dc.contributor.authorMañana Canteli, Mario 
dc.contributor.authorArroyo Gutiérrez, Alberto 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2017-09-04T14:34:28Z
dc.date.available2017-09-04T14:34:28Z
dc.date.issued2017-08
dc.identifier.issn2071-1050
dc.identifier.otherIPT-2011-1447-920000es_ES
dc.identifier.otherENE-2013-42720-Res_ES
dc.identifier.otherRTC-2015-3795-3es_ES
dc.identifier.urihttp://hdl.handle.net/10902/11719
dc.description.abstractThe European Commission has explained how heating and cooling in buildings and industry account for half of the energy consumption of the EU. Several studies explain how to achieve an energy saving at home, and the use of smart thermostats will help to reduce energy consumption while increasing the efficiency of households. In this article, a comparative evaluation was carried out between four smart thermostats that are now on the market, whose characteristics vary in terms of price, precision of measurements and set temperature, algorithms, etc. A thermal test chamber was designed and constructed from a refrigerator, a thermal blanket, a Raspberry Pi and the necessary electronic components for its control and data collection. From the tests carried out in the thermal chamber, data on the operation of the four thermostats such as the maintenance and the anticipation of the setpoint temperature, were obtained. It was necessary to run the system enough times for each thermostat to memorize the housing characteristics, such as its inertia and its thermal insulation. This would also allow for the generation of a better algorithm to regulate the temperature, which would create a lower oscillation with respect to the setpoint temperature. The learning of the thermostats was not demonstrated and for the anticipation mode it was seen that the thermostats failed to improve or learn in this aspect, as they did not improve the start-up times of the heating system, with the consequent increase in energy consumption.es_ES
dc.description.sponsorshipThis work was supported by the Spanish Government under the R+D initiative INNPACTO with reference IPT-2011-1447-920000, Spanish R+D initiative with reference ENE-2013-42720-R and RETOS RTC-2015-3795-3.es_ES
dc.format.extent18 p.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rightsAtribución 4.0 Internacionales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceSustainability, 2017, 9(8), 1462es_ES
dc.subject.otherSmart thermostates_ES
dc.subject.otherEnergy savinges_ES
dc.subject.otherHome comfortes_ES
dc.titleSmart thermostats: an experimental facility to test their capabilities and savings potentiales_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.3390/su9081462
dc.type.versionpublishedVersiones_ES


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