Vis enkel innførsel

dc.contributor.authorSartori, Igor
dc.contributor.authorWalnum, Harald Taxt
dc.contributor.authorSkeie, Kristian
dc.contributor.authorGeorges, Laurent Francis Ghislain
dc.contributor.authorKnudsen, Michael D.
dc.contributor.authorBacher, Peder
dc.contributor.authorCandanedo, José
dc.contributor.authorSigounis, Anna-Maria
dc.contributor.authorPrakash, Anand Krishnan
dc.contributor.authorPritoni, Marco
dc.contributor.authorGranderson, Jessica
dc.contributor.authorYang, Shiyu
dc.contributor.authorWan, Man Pun
dc.date.accessioned2023-05-15T06:40:01Z
dc.date.available2023-05-15T06:40:01Z
dc.date.created2023-04-14T07:39:11Z
dc.date.issued2023
dc.identifier.issn2352-3409
dc.identifier.urihttps://hdl.handle.net/11250/3067870
dc.description.abstractThe data presented here were collected independently for 6 real buildings by researchers of different institutions and gathered in the context of the IEA EBC Annex 81 Data-driven Smart Buildings, as a joint effort to compile a diverse range of datasets suitable for advanced control applications of indoor climate and energy use in buildings. The data were acquired by energy meters, both consumption and PV generation, and sensors of technical installation and indoor climate variables, such as temperature, flow rate, relative humidity, CO2 level, illuminance. Weather variables were either acquired by local sensors or obtained from a close by meteorological station. The data were collected either during normal operation of the building, with observation periods between 2 weeks and 2 months, or during experiments designed to excite the thermal mass of the building, with observation periods of approximately one week. The data have a time resolution varying between 1 min and 15 min; in some case the highest resolution data are also averaged at larger intervals, up to 30 min.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rights
dc.rightsCC BY 4.0
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subjectHeatingen_US
dc.subjectVentilation and air Conditioningen_US
dc.subjectHVACen_US
dc.subjectHigh resolutionen_US
dc.subjectCSV filesen_US
dc.subjectPseudo-Random Binary Sequenceen_US
dc.subjectPRBSen_US
dc.subjectModel identificationModel Predictive Controlen_US
dc.subjectMPCen_US
dc.subjectDeep Reinforcement Learningen_US
dc.subjectDRLen_US
dc.titleSub-hourly measurement datasets from 6 real buildings: Energy use and indoor climateen_US
dc.title.alternativeSub-hourly measurement datasets from 6 real buildings: Energy use and indoor climateen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2023 The authorsen_US
dc.subject.nsiVDP::Teknologi: 500en_US
dc.source.volume48en_US
dc.source.journalData in Briefen_US
dc.identifier.doi10.1016/j.dib.2023.109149
dc.identifier.cristin2140744
dc.source.articlenumber109149en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Med mindre annet er angitt, så er denne innførselen lisensiert som