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dc.contributor.authorPensado Mariño, Martín 
dc.contributor.authorFebrero Garrido, Lara 
dc.contributor.authorPérez-Iribarren, Estibaliz
dc.contributor.authorEguía Oller, Pablo 
dc.contributor.authorGranada Álvarez, Enrique 
dc.date.accessioned2021-09-17T12:08:47Z
dc.date.available2021-09-17T12:08:47Z
dc.date.issued2021-08-22
dc.identifier.citationEnergies, 14(16): 5188 (2021)spa
dc.identifier.issn19961073
dc.identifier.urihttp://hdl.handle.net/11093/2465
dc.description.abstractAccurate forecasting of a building thermal performance can help to optimize its energy consumption. In addition, obtaining the Heat Loss Coefficient (HLC) allows characterizing the thermal envelope of the building under conditions of use. The aim of this work is to study the thermal inertia of a building developing a new methodology based on Long Short-Term Memory (LSTM) neural networks. This approach was applied to the Rectorate building of the University of Basque Country (UPV/EHU), located in the north of Spain. A comparison of different time-lags selected to catch the thermal inertia has been carried out using the CV(RMSE) and the MBE errors, as advised by ASHRAE. The main contribution of this work lies in the analysis of thermal inertia detection and its influence on the thermal behavior of the building, obtaining a model capable of predicting the thermal demand with an error between 12 and 21%. Moreover, the viability of LSTM neural networks to estimate the HLC of an in-use building with an error below 4% was demonstrated.spa
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades | Ref. RTI2018-096296-B-C21spa
dc.language.isoengspa
dc.publisherEnergiesspa
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.titleEstimation of heat loss coefficient and thermal demands of in-use building by capturing thermal inertia using LSTM neural networksspa
dc.typearticlespa
dc.rights.accessRightsopenAccessspa
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096296-B-C21/ES/INVESTIGACION PARA EL DESARROLLO DE HERRAMIENTAS DE CARACTERIZACION Y PREDICCION DEL RENDIMIENTO ENERGETICO DE EDIFICIOSspa
dc.identifier.doi10.3390/en14165188
dc.identifier.editorhttps://www.mdpi.com/1996-1073/14/16/5188spa
dc.publisher.departamentoEnxeñaría mecánica, máquinas e motores térmicos e fluídosspa
dc.publisher.grupoinvestigacionGTE (Grupo de Tecnoloxía Enerxética)spa
dc.subject.unesco3305.90 Transmisión de Calor en la Edificaciónspa
dc.subject.unesco3305 Tecnología de la Construcciónspa
dc.subject.unesco3328.16 Transferencia de Calorspa
dc.date.updated2021-09-15T12:23:17Z


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    Attribution 4.0 International
    Except where otherwise noted, this item's license is described as Attribution 4.0 International