dc.contributor | Escuela Superior y Tecnica de Ingenieros de Minas | es_ES |
dc.contributor.author | Pérez Montalvo, Ernesto | |
dc.contributor.author | Zapata Velásquez, Manuel Eduardo | |
dc.contributor.author | Benítez Vázquez, Laura María | |
dc.contributor.author | Cermeño González, Juan Manuel | |
dc.contributor.author | Alejandro Miranda, Jose | |
dc.contributor.author | Martínez Cabero, Miguel Ángel | |
dc.contributor.author | Puente Gil, Álvaro de la | |
dc.contributor.other | Ingenieria Electrica | es_ES |
dc.date | 2022 | |
dc.date.accessioned | 2024-01-26T10:20:18Z | |
dc.date.available | 2024-01-26T10:20:18Z | |
dc.identifier.citation | Pérez-Montalvo, E., Zapata-Velásquez, M.-E., Benítez-Vázquez, L.-M., Cermeño-González, J.-M., Alejandro-Miranda, J., Martínez-Cabero, M.-Á., & de la Puente-Gil, Á. (2022). Model of monthly electricity consumption of healthcare buildings based on climatological variables using PCA and linear regression. Energy Reports, 8, 250-258. https://doi.org/10.1016/J.EGYR.2022.06.117 | es_ES |
dc.identifier.uri | https://hdl.handle.net/10612/17838 | |
dc.description.abstract | [EN] At this time, due to the global pandemic that has occurred, public administrations want to optimize resources and reduce
greenhouse gases with more interest than before. It is the case of the Energy Regional Entity of the Junta de Castilla y León
(Spain) that pursues the optimization of the energy consumption in particular of healthcare sector buildings. For this purpose,
this work focuses on estimating electricity consumption for each month, for which different scenarios will be generated and the
corresponding model is obtained for each scenario. This model has been developed considering the historical monthly data of
consumption and climatic variables for the last 3 years. Electricity consumption in public sanitary buildings is related to their
climatology, due to the use of air conditioning to adjust the indoor temperature. Subsequently, from the models obtained, the
results will be analyzed. Significant differences have been observed in the estimation of electricity consumption with respect
to the real data provided by the Junta de Castilla y León. The results obtained show how the availability of climatic variables
increases the accuracy of the model obtained by about 30%. | es_ES |
dc.language | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.subject | Ingenierías | es_ES |
dc.subject.other | PCA | es_ES |
dc.subject.other | Data mining | es_ES |
dc.subject.other | Regression models | es_ES |
dc.subject.other | Smart metering | es_ES |
dc.subject.other | Building energy index | es_ES |
dc.title | Model of monthly electricity consumption of healthcare buildings based on climatological variables using PCA and linear regression | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.identifier.doi | https://doi.org/10.1016/j.egyr.2022.06.117 | |
dc.description.peerreviewed | SI | es_ES |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es_ES |
dc.identifier.essn | 2352-4847 | |
dc.journal.title | Energy Reports | es_ES |
dc.volume.number | 8 | es_ES |
dc.issue.number | 9 | es_ES |
dc.page.initial | 250 | es_ES |
dc.page.final | 258 | es_ES |
dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es_ES |
dc.subject.unesco | 3306 Ingeniería y Tecnología Eléctricas | es_ES |