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Clustering the Occupant Behavior in Residential Buildings: A Method Comparison

: Carbonare, N.; Pflug, T.; Wagner, A.

Volltext (PDF; )

Both, P. von ; International Building Performance Simulation Association -IBPSA-:
BauSIM 2018. 7. Deutsch-österreichische IBPSA Konferenz. Tagungsband : 26.-28. September 2018, Karlsruhe, Germany
Karlsruhe: KIT, 2018
BauSIM Konferenz <7, 2018, Karlsruhe>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer ISE ()
Thermische Systeme und Gebäudetechnik; occupant behavior; Energieeffiziente Gebäude; Gebäudehülle; Wärme- und Kälteversorgung; Betriebsführung und Gesamtenergiekonzepte; Thermische Speicher für Gebäude; Materialien und Komponenten für Wärmetransformation

The aim of this paper is to investigate possible patterns of the occupant behaviour in residential buildings. Measurements were taken in multifamily buildings where several occupantrelated variables were recorded. We chose and compared two different clustering methods: whole time series and features clustering (kmeans algorithm). The mentioned methods were performed selecting two variables (window opening and indoor temperature), and tested with supervised learning methods. Results suggest that features clustering can perform better than whole time series. The representation of the occupant behaviour through features is meant to be applied in future work regarding the optimization of control strategies in ventilation systems.