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dc.contributor.authorUriarte Pérez de Nanclares, Irati
dc.contributor.authorErcoreca González, Aitor
dc.contributor.authorGiraldo Soto, Catalina ORCID
dc.contributor.authorMartín Escudero, Koldobika ORCID
dc.contributor.authorUriarte-Arrien, Amaia
dc.contributor.authorEguía López, Pablo ORCID
dc.date.accessioned2024-02-08T11:10:11Z
dc.date.available2024-02-08T11:10:11Z
dc.date.issued2019-03-07
dc.identifier.citationEnergy and Buildings 192 : 101-122 (2019)es_ES
dc.identifier.issn0378-7788
dc.identifier.issn1872-6178
dc.identifier.urihttp://hdl.handle.net/10810/65447
dc.description.abstractThe performance gap between the design energy consumption of buildings and their real energy consumption has three main sources: the energy systems’ performance, the users’ behaviour and the buildings’ envelope performance. The latter should be characterized under in-use conditions by estimating their in-use Heat Loss Coefficient (HLC). This work further develops an existing ‘average method’ by fully developing it from the energy conservation principle applied to a generic in-use building. Furthermore, the uncertainty sources are identified and limited through the mathematical development of the method. An innovative solution to the problematic of multizone buildings is also demonstrated, where HLC values should be calculated for different floors and then aggregated to obtain the entire building’s HLC. Furthermore, all these can be done without the need of a detailed model of the building. The improved average method has been applied to an occupied, energetically monitored office building of the University of the Basque Country. The building was energetically rehabilitated during the summer of 2017. Therefore, the proposed method has been applied over the three winters prior to rehabilitation and then, to the winter after the rehabilitation. It has thus been possible to estimate a 28% reduction of the HLC for the post-retrofitted case, as compared to the pre-retrofitted one.es_ES
dc.description.sponsorshipThis work was supported by the Spanish Economy and Competitiveness Ministry and the European Regional Development Fund (grant numbers ENE2015-65999-C2-2-R and ENE2015-65999-C2-1- R) through the IMMOEN project ‘Implementation of automated calibration and multiobjective optimization techniques applied to Building Energy Model simulations by means of monitored buildings’, project reference: ENE2015-65999-C2-2-R and ENE2015- 65999-C2-1-R (MINECO/FEDER); by the European Commission through the A2PBEER project ‘Affordable and Adaptable Public Buildings through Energy Efficient Retrofitting’, Grant agreement no: 609060; by the University of the Basque Country (UPV/EHU) by providing funding and the studied in-use office building. The corresponding author also acknowledges the support provided by the Education Department of the Basque Government (grant number PRE_2017_1_0122) through a scholarship granted to her to complete her PhD degree.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/ENE2015-65999-C2-2-R
dc.relationinfo:eu-repo/grantAgreement/MINECO/ENE2015-65999-C2-1-R
dc.relationinfo:eu-repo/grantAgreement/EC/A2PBEER/609060
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectbuilding envelope energy performancees_ES
dc.subjectHeat Loss Coefficient (HLC)es_ES
dc.subjectenergy monitoringes_ES
dc.subjectaverage methodes_ES
dc.titleMathematical development of an average method for estimating the reduction of the Heat Loss Coefficient of an energetically retrofitted occupied office buildinges_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2019 Elsevier under CC BY-NC-ND license
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0378778818337587
dc.identifier.doi10.1016/j.enbuild.2019.03.006
dc.contributor.funderEuropean Commission
dc.departamentoesMáquinas y motores térmicoses_ES
dc.departamentoeuMakina eta motor termikoakes_ES


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© 2019 Elsevier under CC BY-NC-ND license
Except where otherwise noted, this item's license is described as © 2019 Elsevier under CC BY-NC-ND license