Occupancy Diversity Factor for University Buildings and Its Influence on Energy Simulation

Abstract

Buildings are huge energy consumers. In order to achieve reduction in building energy consumption, many building energy simulations are performed. Occupancy profile plays a significant role in energy simulations. Although there are many existing studies on occupancy, many of them focus on commercial buildings such as offices. Institutional buildings such as university buildings, though they consume a significant amount of energy, are less focused by researchers. Thus, this paper adopts an existing occupancy model technique, and selects NUS SDE 2 as a case study to study the impact of occupancy profile on energy consumption.

The occupancy model is developed based on data from field study in four active classrooms in SDE 2 building. After the occupancy model is developed, it serves as input to SDE 2 model in IES-VE software. Several occupancy profile settings including calendar year and daily operation schedule are adjusted based on the data collected. Statistical indices including Mean Bias Error (MBE) and Coefficient of Variation of the Root Mean Square Error [CV(RMSE)] are used to evaluate the impact of occupancy profile on energy simulation. The final model based on data from SDE 2 improves CV(RMSE) from 27.1% to 24.5%. Besides, data from Building Data Genome (BDG) project is processed by Python to develop another diversity factor model to serve as a comparison between SDE 2 building and other university buildings around the world. The comparison shows that buildings in BDG project generally possesses greater occupancy rate than SDE 2 building.

In short, this paper has achieved multiple objectives of occupancy model development, model calibration, data process and energy simulation results comparison. Future studies on occupancy model of university buildings are also proposed.