Typical weekly occupancy profiles in non-residential buildings based on mobile positioning data

Abstract Occupancy schedule is one of the essential inputs for building performance simulation. Current designers and researchers refer to the occupancy schedules from energy standards such as ASHRAE 90.1, which was initially published in 1989 and may not apply to the occupancy profiles of the current circumstances. With the advances of mobile communication networks and positioning services, the mobile positioning data has been made available for researchers to obtain and extract real occupancy profiles for buildings of various types. This research utilizes mobile positioning data from social media platforms to extract typical weekly occupancy profiles of non-residential buildings by cluster analysis. The paper investigated the temporal distributions and heterogeneous features for typical profiles with the perspective of two descriptive parameters: peak ratio and daily total occupancy ratio, which represent the deviation of occupancy across the different days of a week. The proposed typical profiles are then compared with the reference profiles from ASRHAE Standards and the impact on energy simulation results is evaluated. Results suggests significant difference on energy load profiles and load distributions with the real occupancy profiles, and this method can prominently contribute to optimal building design strategies.