Room-level domestic occupancy simulation model using time use survey data

Abstract

To minimize the energy performance gap between expected and actual energy usage in buildings, it is crucial to accurately represent occupant behaviour, which significantly impacts building performance. With improved building insulation standards, the impact of occupant actions becomes more pronounced. Most domestic occupancy models use three general states: present & awake, present & sleeping, and absent. However, in residential buildings, room-level presence information is essential for accurately evaluating energy demands, as specific activities occur in specific rooms. The novelty of this study lies in the simulation of occupancy at the room level. Using data from a Danish time-use survey, a hidden Markov model was fitted to estimate transition probabilities between five states: bedroom, kitchen, bathroom, living room, and not present, based on recorded activities. An online application of the model is available (Link: https://proccs.compute.dtu.dk), enabling researchers or building designers to create room-level occupancy profiles for use in building energy performance tools, providing a more accurate representation of household occupancy.