Stochastic behavioural models of occupants' main bedroom window operation for UK residential buildings

This paper presents the development of stochastic models of occupants' main bedroom window operation based on measurements collected in ten UK dwellings over a period of a year. The study uses multivariate logistic regression to understand the probability of opening and closing windows based on indoor and outdoor environment factors (physical environmental drivers) and according to the time of the day and season (contextual drivers). To the authors' knowledge, these are the first models of window opening and closing behaviour developed for UK residential buildings. The work reported in this paper suggests that occupants' main bedroom window operation is influenced by a range of physical environmental (i.e. indoor and outdoor air temperature and relative humidity, wind speed, solar radiation and rainfall) and contextual variables (i.e. time of day and season). In addition, the effects of the physical environmental variables were observed to vary in relation to the contextual factors. The models provided in this work can be used to calculate the probability that the main bedroom window will be opened or closed in the next 10 min. These models could be used in building performance simulation applications to improve the inputs for occupants' window opening and closing behaviour and thus the predictions of energy use and indoor environmental conditions of residential buildings. •Stochastic models of occupants' main bedroom window operation were developed.•Measurements were collected in ten UK dwellings over a full annual period.•Multivariate logistic regression was used as the modelling method.•Physical environmental and contextual drivers of window operation were studied.•The models can be implemented in building performance simulation applications.