Optimizing the Performance of Energy-Intensive Commercial Buildings: Occupancy-Focused Data Collection and Analysis Approach

Abstract

In commercial buildings, energy consumed during operation oftentimes differs from that predicted during design. The discrepancy is specifically large in energy-intensive buildings (e.g., laboratory facilities), which can consume up to five times more energy than other types of commercial facilities (e.g., office buildings). Among different factors that impact building performance, recent studies indicate that how occupants use and how facility managers operate the building highly influence energy consumption levels. Consequently, there is a growing need for post-occupancy evaluation (POE) to investigate how human actions impact building performance and identify energy-saving opportunities. Despite advances in the POE field, researchers are still facing important challenges related to collecting, processing, and analyzing relevant building energy and occupancy data. Consequently, current POE methods are not adequate to investigate human-focused energy conservation opportunities in commercial buildings. This research fills the gap in literature by proposing a framework to collect relevant post-occupancy energy and occupancy data, mine the data, and develop energy analysis methods that uncover the human influence on energy performance and help propose energy-saving actions. The capabilities of the framework are highlighted in a case study on a laboratory facility located in Madison, Wisconsin. Results highlight inefficiencies in the operation of the heating, ventilation, and air conditioning system (HVAC), which are leading to increases in energy consumption levels by as much as 40%.