Blanco Bohorquez, Luis Armando und Aditya, Megha und Schiricke, Björn und Hoffschmidt, Bernhard (2023) Classification of Building Properties from the German Census Data for Energy Analysis Purposes. In: 18th IBPSA Conference on Building Simulation, BS 2023. Building Simulation 2023, 2023-09-04 - 2023-09-06, Shanghai, China. doi: 10.26868/25222708.2023.1266. ISSN 2522-2708.
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Kurzfassung
The building sector is an important target for reducing urban energy consumption. Detailed data on the building stock is needed for modelling urban building energy demands but its availability is often insufficient. In Germany, the largest available public database about the building stock is the census national database, containing critical attributes for building characterization on a national scale, such as building age, construction type, and number of residents. However, the detailed information about the individual buildings is restricted by national data privacy laws and the information is found in an aggregated format. This study shows statistical and machine learning approaches to take the census data and disaggregate its information to each individual building in order to use that information for urban building energy modelling. This study presents a classification model for the following parameters of the 2011 census: building age, building form and heating type, and Number of residents. A study case was conducted in Oldenburg, Germany.
elib-URL des Eintrags: | https://elib.dlr.de/199041/ | ||||||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Vortrag) | ||||||||||||||||||||
Titel: | Classification of Building Properties from the German Census Data for Energy Analysis Purposes | ||||||||||||||||||||
Autoren: |
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Datum: | Juni 2023 | ||||||||||||||||||||
Erschienen in: | 18th IBPSA Conference on Building Simulation, BS 2023 | ||||||||||||||||||||
Referierte Publikation: | Nein | ||||||||||||||||||||
Open Access: | Ja | ||||||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||||||
In SCOPUS: | Ja | ||||||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||||||
DOI: | 10.26868/25222708.2023.1266 | ||||||||||||||||||||
ISSN: | 2522-2708 | ||||||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||||||
Stichwörter: | Building, Energy, Census, ML | ||||||||||||||||||||
Veranstaltungstitel: | Building Simulation 2023 | ||||||||||||||||||||
Veranstaltungsort: | Shanghai, China | ||||||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||||||
Veranstaltungsbeginn: | 4 September 2023 | ||||||||||||||||||||
Veranstaltungsende: | 6 September 2023 | ||||||||||||||||||||
HGF - Forschungsbereich: | Energie | ||||||||||||||||||||
HGF - Programm: | Materialien und Technologien für die Energiewende | ||||||||||||||||||||
HGF - Programmthema: | Thermische Hochtemperaturtechnologien | ||||||||||||||||||||
DLR - Schwerpunkt: | Energie | ||||||||||||||||||||
DLR - Forschungsgebiet: | E SW - Solar- und Windenergie | ||||||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | E - Condition Monitoring | ||||||||||||||||||||
Standort: | Jülich | ||||||||||||||||||||
Institute & Einrichtungen: | Institut für Vernetzte Energiesysteme Institut für Solarforschung > Qualifizierung | ||||||||||||||||||||
Hinterlegt von: | Blanco Bohorquez, Luis Armando | ||||||||||||||||||||
Hinterlegt am: | 10 Nov 2023 11:17 | ||||||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:59 |
Verfügbare Versionen dieses Eintrags
- Classification of Building Properties from the German Census Data for Energy Analysis Purposes. (deposited 10 Nov 2023 11:17) [Gegenwärtig angezeigt]
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