Rhys Goldstein, Alex Tessier, Azam Khan
Rhys Goldstein, Alex Tessier, Azam Khan
International Conference of the International Building Performance Simulation Association
2011
Occupant behavior is widely regarded as one of the most significant sources of uncertainty in the prediction of building energy use. Preexisting simulation methods address this issue by automatically reproducing patterns of behavior found in historical occupant schedules. We extend these methods to incorporate spatial information. In our work, space layout influences the selection of individuals who participate in an activity, and the location where the activity occurs. Participants and locations are randomly selected based on probabilities derived from cost functions. One of these cost functions encourages participation between occupants of nearby workstations. Another discourages overcrowding. We apply the method to an existing office building to study how effectively an occupant model can be customized, and how accurately it can predict space utilization.
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Buildings are the largest consumers of energy responsible for 48% of all Green House Gas (GHG) emissions. Due to the complexity and multidisciplinary aspects of architectural design, construction, urban design, and building occupant behavior, simulation has gained attention as a means of addressing this enormous challenge. The idea is to model a building’s many interacting subsystems, including its occupants, electrical equipment, and indoor and outdoor climate. With simulation results in hand, an architect is better able to predict the energy demand associated with various designs, and choose from among the more sustainable options.