Developing a window behaviour model incorporating A/C operation states

Abstract

There have been much research focus on modelling various types of occupant thermal adaptive behaviour with an aim to improve the reliability of building energy performance simulation (BEPS) tools. However, most existing studies exploring occupant interaction with residential building systems limit their scope to a single, isolated behaviour (e.g. window opening only), which fails to consider that occupant reactions are determined by the interconnected effects of series of adaptive actions. This study aimed to develop a stochastic window operation model to address the interdependency between occupant's window and A/C operation. Longitudinal field observations were conducted in a sample of 41 Brisbane region households over a one-year period. The sample households' occupancy status, indoor environmental conditions, use of windows and air-conditioning (A/C) were continuously recorded. The cut-off temperature beyond which the probability of windows being open begins to decrease with an increase of the outdoor temperature, was found to be approx. 27 °C in both living and sleeping areas within the monitored households. This paper proposes a window operation model that captures diverse window opening patterns observed amongst the sample households, with a particular focus on the effect of A/C operation state on window opening and closing actions. The proposed model was tested by running 1000 simulations on a validation dataset. A good agreement observed between 1000 simulations and actual window use patterns indicates that the model can be applied to dynamic building energy performance and indoor environment simulations.