Integrating probabilistic methods for describing occupant presence with building energy simulation models

Abstract

This paper presents a method for developing a probabilistic-based occupancy model that focuses on occupants’ long vacancy activities (greater than 1 week) and other potential building underutilization that is further integrated with a building energy simulation model. The combined model is then applied toward an existing Leadership in Energy and Environmental Design (LEED) certified military dormitory and later compared with corresponding values from the energy model's original prediction as well as actual building energy data. The occupancy model simulates annual building occupancy rates comprised of weekly values based on the frequency, duration, and seasonality of occupants’ long vacancy activities. The energy model uses the simulated occupancy rates to yield the building's predicted range of energy performance. Applying the combined model to the existing LEED building resulted in an improved, predicted Energy Use Intensity (EUI) mean value of 612MJ/m2 as compared to the original model and actual EUI values of 691 and 590, respectively. While the model also demonstrated its utility in describing the change in predicted performance over a range of probabilities associated with certain long vacancy activities, efforts to incorporate other occupant behavior-related aspects such occupant schedules and thermal set points could further improve modeling efforts.