dc.creator | Bienvenido Huertas, José David | es |
dc.creator | Rubio Bellido, Carlos | es |
dc.creator | Pérez Ordóñez, Juan Luis | es |
dc.creator | Martínez Abella, Fernando | es |
dc.date.accessioned | 2019-07-04T08:16:37Z | |
dc.date.available | 2019-07-04T08:16:37Z | |
dc.date.issued | 2019-03-27 | |
dc.identifier.citation | Bienvenido-Huertas, D., Rubio Bellido, C., Pérez Ordóñez, J.L. y Martínez Abella, F. (2019). Estimating adaptive setpoint temperatures using weather stations. Energies, 12 (7), 1-47. | |
dc.identifier.issn | 1996-1073 | es |
dc.identifier.uri | https://hdl.handle.net/11441/87832 | |
dc.description.abstract | Reducing both the energy consumption and CO 2 emissions of buildings is nowadays one of the main objectives of society. The use of heating and cooling equipment is among the main causes of energy consumption. Therefore, reducing their consumption guarantees such a goal. In this context, the use of adaptive setpoint temperatures allows such energy consumption to be significantly decreased. However, having reliable data from an external temperature probe is not always possible due to various factors. This research studies the estimation of such temperatures without using external temperature probes. For this purpose, a methodology which consists of collecting data from 10 weather stations of Galicia is carried out, and prediction models (multivariable linear regression (MLR) and multilayer perceptron (MLP)) are applied based on two approaches: (1) using both the setpoint temperature and the mean daily external temperature from the previous day; and (2) using the mean daily external temperature from the previous 7 days. Both prediction models provide adequate performances for approach 1, obtaining accurate results between 1 month (MLR) and 5 months (MLP). However, for approach 2, only the MLP obtained accurate results from the 6th month. This research ensures the continuity of using adaptive setpoint temperatures even in case of possible measurement errors or failures of the external temperature probes. | es |
dc.description.sponsorship | Spanish Ministry of Science, Innovation and Universities 00064742/ITC-20133094 | es |
dc.description.sponsorship | Spanish Ministry of Economy, Industry and Competitiveness BIA 2017-85657-R | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | es |
dc.relation.ispartof | Energies, 12 (7), 1-47. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Adaptive setpoint temperature | es |
dc.subject | Multilayer perceptron | es |
dc.subject | Multivariable linear regression | es |
dc.subject | Weather station | es |
dc.title | Estimating adaptive setpoint temperatures using weather stations | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Construcciones Arquitectónicas II (ETSIE) | es |
dc.relation.projectID | 00064742/ITC-20133094 | es |
dc.relation.projectID | BIA 2017-85657-R | es |
dc.relation.publisherversion | http://doi.org/10.3390/en12071197 | es |
dc.identifier.doi | 10.3390/en12071197 | es |
idus.format.extent | 47 p. | es |
dc.journaltitle | Energies | es |
dc.publication.volumen | 12 | es |
dc.publication.issue | 7 | es |
dc.publication.initialPage | 1 | es |
dc.publication.endPage | 47 | es |