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dc.contributor.authorLumbreras, Mikel
dc.contributor.authorGaray, Roberto
dc.contributor.authorMarijuan, Antonio Garrido
dc.date.accessioned2020-12-17T18:35:36Z
dc.date.available2020-12-17T18:35:36Z
dc.date.issued2020
dc.identifier.citationMikel Lumbreras et al 2020 IOP Conf. Ser.: Earth Environ. Sci. 588 032007en
dc.identifier.issn1755-1307en
dc.identifier.urihttp://hdl.handle.net/11556/1037
dc.description.abstractThe use of smart energy meters enables the monitoring of large quantity of data related to heat consumption patterns in buildings connected to DH networks. This information can be used to understand the interaction between building and the final users´ without accurate information about building characteristics and occupational rates. In this paper an intuitive and clarifier data-driven model is presented, which couples heat demand and weather variables. This model enables the disaggregation of Space-Heating & Domestic Hot water demand, characterization of the total heat demand and the forecasting for the next hours. Simulations for 53 building have been carried out, with satisfactory results for most of them, reaching R2 values above 0.9 in some of them.en
dc.description.sponsorshipThis project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 768567.en
dc.language.isoengen
dc.publisherIOP Scienceen
dc.titleEnergy meters in District-Heating Substations for Heat Consumption Characterization and Prediction Using Machine-Learning Techniquesen
dc.typeconferenceObjecten
dc.identifier.doi10.1088/1755-1315/588/3/032007en
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/768567/EU/REnewable Low TEmperature District/RELaTEDen
dc.rights.accessRightsopenAccessen
dc.subject.keywordsSmart energy metersen
dc.subject.keywordsEnergyen
dc.subject.keywordsBuildingen
dc.identifier.essn1755-1315en
dc.journal.titleIOP Conference Series: Earth and Environmental Scienceen
dc.page.final1.10en
dc.page.initial1.06en
dc.volume.number588en
dc.conference.titleIOP Conference Series: Earth and Environmental Scienceen


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