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CU-BEMS, smart building electricity consumption and indoor environmental sensor datasets

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dc.contributor.authorPipattanasomporn, Manisaen
dc.contributor.authorChitalia, Gopalen
dc.contributor.authorSongsiri, Jitkomuten
dc.contributor.authorAswakul, Chaoditen
dc.contributor.authorPora, Wanchalermen
dc.contributor.authorSuwankawin, Surapongen
dc.contributor.authorAudomvongseree, Kulyosen
dc.contributor.authorHoonchareon, Naebboonen
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2020-11-11T14:28:58Zen
dc.date.available2020-11-11T14:28:58Zen
dc.date.issued2020-07-20en
dc.description.abstractThis paper describes the release of the detailed building operation data, including electricity consumption and indoor environmental measurements, of the seven-story 11,700-m(2) office building located in Bangkok, Thailand. The electricity consumption data (kW) are that of individual air conditioning units, lighting, and plug loads in each of the 33 zones of the building. The indoor environmental sensor data comprise temperature (degrees C), relative humidity (%), and ambient light (lux) measurements of the same zones. The entire datasets are available at one-minute intervals for the period of 18 months from July 1, 2018, to December 31, 2019. Such datasets can be used to support a wide range of applications, such as zone-level, floor-level, and building-level load forecasting, indoor thermal model development, validation of building simulation models, development of demand response algorithms by load type, anomaly detection methods, and reinforcement learning algorithms for control of multiple AC units.en
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1038/s41597-020-00582-3en
dc.identifier.eissn2052-4463en
dc.identifier.issue1en
dc.identifier.other241en
dc.identifier.pmid32686680en
dc.identifier.urihttp://hdl.handle.net/10919/100834en
dc.identifier.volume7en
dc.language.isoenen
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.titleCU-BEMS, smart building electricity consumption and indoor environmental sensor datasetsen
dc.title.serialScientific Dataen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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Scholarly Works, Electrical and Computer Engineering
Destination Area: Intelligent Infrastructure for Human-Centered Communities (IIHCC)