A Probabilistic Model To Predict Building Occupants’ Diversity Towards Their Interactions With The Building Enveloppe

Abstract

Based on observations conducted in an office building, we apply advanced statistical analysis methods, leading to the formulation of stochastic models for the prediction of buildings occupants’ actions on window openings and shading devices. The statistical analysis method – based on development, the proposed modelling approaches, the robustness of their validation and their scope of application are variable, which advocates for the strengthening of published work into a robust formulation, adaptable to a sufficiently wide range of situations. generalised linear mixed models – enables a correct treatment of the longitudinal nature of the datasets, an accurate estimation of the calibration parameters’ uncertainty and a detailed study of the differences between the occupants surveyed. This analysis results Climate models Radiation models OcOccucuppaannccyymmodoedl el in the formulation of stochastic models for the prediction of occupants’ interactions with the key elements of the building envelope, which include explicit in-built probabilistic terms to account for occupants’ diversity if required. Furthermore, we show that the properties of these probabilistic terms can be used to infer a statistical distribution of the model’s calibration parameters, which comprehensively represent the diversity of observed behaviours between building occupants, and can be applied to simulate their behavioural properties. Electricity demand Water demand Stochastic models for occupants' actions Actions on artificial lighting Actions on electrical & water appliances Heat gains Actions on HVAC systems Actions on blinds Actions on windows Air flows