Accounting for the Occupancy Variable in Inverse Building Energy Baselining Models

Abstract

The occupancy factor is often underestimated in inverse modeling of building energy use, or accounted for by grouping the daily data in occupied and unoccupied groups which are modeled separately. For instance, in institutional buildings it is common to identify "weekdays/weekends", "semester breaks", and "holidays" daytypes. In order to develop one model that accounts for all periods, i.e., occupied and unoccupied, at an hourly time scale, a dummy variable (regressor) can be used. The dummy variable is often used in a simplified way; for instance, having a value of 0 between 8:00 AM and 5:00 PM, and 1 between 5:00 PM and 8:00 AM, for an office building. In this paper, the effect of using different alternatives in accounting for the occupancy variable in inverse modeling of building energy use is investigated, and the resulting uncertainty in the predictions, using the SMLP inverse method are presented.