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A. Mahdavi, M. Del Bolgia, F. Tahmasebi, M. Schuss:
"Prediction of user-driven window operation in buildings";
Talk: Indoor Air 2016 - The 14TH International Conference of Indoor Air Quality and Climate, Ghent, Belgium; 2016-07-03 - 2016-07-08; in: "Proceedings of the 14TH International Conference of Indoor Air Quality and Climate, Ghent, Belgium", J. Laverge, T. Salthammer, M. Stranger (ed.); ISAIQ - International Society of Indoor Air Quality and Climate, (2016).

Inhabitants' presence and control actions in buildings can influence buildings' indoor environmental and energy performance. Thus, multiple past and ongoing research efforts have been and are being undertaken to develop dependable representations of inhabitants' operation of buildings´ environmental systems such as windows, luminaires, and shading devices. However, most existing behavioural models are predominantly derived based on rather limited sets of observational data. In the present contribution we take advantage of long-term observation of indoor and outdoor conditions together with high-resolution data on the frequency of window operation actions in an office space. This dataset provides the basis to test conjectures regarding parameters contributing to inhabitants' control action probability levels. The contribution thus entails an attempt to offer a white-box modelling approach to window operation prediction.

(no german version available) Inhabitants' presence and control actions in buildings can influence buildings' indoor environmental and energy performance. Thus, multiple past and ongoing research efforts have been and are being undertaken to develop dependable representations of inhabitants' operation of buildings´ environmental systems such as windows, luminaires, and shading devices. However, most existing behavioural models are predominantly derived based on rather limited sets of observational data. In the present contribution we take advantage of long-term observation of indoor and outdoor conditions together with high-resolution data on the frequency of window operation actions in an office space. This dataset provides the basis to test conjectures regarding parameters contributing to inhabitants' control action probability levels. The contribution thus entails an attempt to offer a white-box modelling approach to window operation prediction.

Buildings, Inhabitants, behaviour, windows, ventilation