Understanding building and urban environment interactions: An integrated framework for building occupancy modelling

Abstract

Improving building energy efficiency requires accurate modelling and a comprehensive understanding of how occupants use building space. This thesis focuses on modelling building occupancy to enhance the predictive accuracy of occupancy patterns and gain a better understanding of the causal reasons for occupancy behaviour. A conceptual framework is proposed to relax the restriction of isolated building analysis, which accounts for interactions between buildings, its occupants, and other urban systems, such as the effects of transport incidents on occupancy and circulation in buildings. This thesis also presents a counterpart mapping of the framework that elaborates the links between modelling of transport and building systems. To operationalise the proposed framework, a novel modelling approach which has not been used in the current context, called the hazard-based model, is applied to model occupancy from a single building up to a district area. The proposed framework is further adapted to integrate more readily with transport models, to ensure that arrivals and departures to and from the building are consistent with the situation of the surrounding transport systems. The proposed framework and occupancy models are calibrated and validated using Wi-Fi data and other variables, such as transport and weather parameters, harvested from the South Kensington campus of Imperial College London. In addition to calibrating the occupancy model, integrating a travel simulator produces synthetic arrivals into or around the campus, which are further distributed over campus buildings via an adapted technique and feed the occupancy simulations. The model estimation results reveal the causal reasons for or exogenous effects on individual occupancy states. The validation results confirm the ability of the proposed models to predict building occupancy accurately both on average and day by day across the future dataset. Finally, evaluating occupancy simulations for various hypothetical scenarios provides valuable suggestions for efficient building design and facility operation.Open Acces