Non-Intrusive Data Monitoring and Analysis of Occupant Energy-Use Behaviors in Shared Office Spaces

Abstract

A non-intrusive data collection framework is developed to analyze the desk-level occupancy and energy use patterns of occupants in shared office spaces. The framework addresses the limitations of previous studies in the literature, which either lacked the granularity to study individual occupants' behaviors or relied on data from complex Building Management Systems (BMS). The framework is applied to a shared office space of an academic institution in the United Arab Emirates (UAE), where occupancy, lighting, and plug-load data were collected from individual desks for 6 months. The results highlight weak relationships between the occupancy status and the total electric loads, with 35% of the total electric loads consumed when the area is completely vacant, and 64% of the plug-load energy consumed when the desks were reported as unoccupied. While specific to the studied building, the results highlight the role that a high-resolution data monitoring framework plays in capturing inefficient consumption patterns. The findings also confirm the contribution of occupant behavior (OB) to the energy performance gap commonly observed between predicted and actual energy levels.