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dc.contributor.authorEguía, Pablo
dc.contributor.authorAlonso Rodríguez, Jose María
dc.contributor.authorSaavedra, Ángeles
dc.contributor.authorArce Fariña, Elena
dc.contributor.authorGranada, Enrique
dc.date.accessioned2024-01-19T18:22:40Z
dc.date.available2024-01-19T18:22:40Z
dc.date.issued2018-02-06
dc.identifier.citationEguía Oller, P., Alonso Rodríguez, J. M., Saavedra González, Á., Arce Fariña, E., & Granada Álvarez, E. (2018). Improving the calibration of building simulation with interpolated weather datasets. Renewable Energy, 122, 608-618. https://doi.org/10.1016/j.renene.2018.01.100es_ES
dc.identifier.issn1879-0682
dc.identifier.urihttp://hdl.handle.net/2183/35021
dc.descriptionManuscrito aceptadoes_ES
dc.description.abstract[Abstract]: The building sector offers huge potential for energy savings, which helps to achieve environmental objectives and social benefits. A good approach to determine both the energy consumption of new buildings and the energetic refurbishment of existing buildings is through thermal simulation. This paper studies how building energy simulation calibration can be improved using interpolated weather data to determine on-site meteorological parameters at the building location. The lack of precise meteorological data in the exact location of buildings means that data from nearby stations is generally used, not knowing how far the error spreads in the results of heating demands and loads. The novelty of this paper lies in the analysis of error propagation to the results of demands and loads of thermal simulation, as well as in the method used to reduce these errors by TPS interpolation. As an interesting conclusion, the average (CV(RMSE)) obtained in the simulation of the studied building, placed successively in each one of the 70 meteorological station locations, decreases from 74% when using the nearest neighborhood to each site to 26% using the TPS interpolation technique. The error in the building simulations is almost three times lower using the studied method.es_ES
dc.description.sponsorshipWe would like to thank for the meteorological database to Spanish State Meteorological Agency (AEMET). This investigation article was partially supported by the Spanish Government (Project: ENE2015-65999-C2-1-R). This investigation article was partially supported by the Spanish Government (Economy and Competitiveness Spanish Ministry), through the CDTI center (Industrial Technology Development Centre), and European FEDER 2007 - 2013 Technological Fund (European Regional Development Fund) (Project: IDI-20150503).es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ENE2015-65999-C2-1-R/ES/INVESTIGACION Y DESARROLLO DE TECNICAS DE CALIBRACION Y OPTIMIZACION MULTIOBJETIVO AUTOMATIZADOS APLICADO A SIMULACION DE MODELOS ENERGETICOS EN EDIFICACIONes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ IDI-20150503/ES/HERRAMIENTA DE CONTROL METEOROLÓGICO PARA LA SIMULACIÓN TÉRMICA PARA LA CONSTRUCCIÓN Y EL CONTROL AMBIENTALes_ES
dc.relation.urihttps://doi.org/10.1016/j.renene.2018.01.100es_ES
dc.rights© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/es_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectBuilding simulationes_ES
dc.subjectWeather dataes_ES
dc.subjectInterpolationes_ES
dc.subjectThin plate splinees_ES
dc.titleImproving the calibration of building simulation with interpolated weather datasetses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleRenewable Energyes_ES
UDC.volume122es_ES
UDC.startPage608es_ES
UDC.endPage618es_ES
dc.identifier.doihttps://doi.org/10.1016/j.renene.2018.01.100


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