Energy and demand implication of using recommended practice occupancy diversity factors compared to real occupancy data in whole building energy simulation

Whole building energy simulation tools have become increasingly useful in assessing and improving existing and designing new high-performance buildings. Occupancy diversity factors are one category of parameters needing additional consideration in energy modelling as they can have a large impact on the output of the simulation. In this study, two sources of occupancy diversity factors, American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) references and measured data from Duarte, Van Den Wymelenberg, and Rieger. [2013a. Revealing Occupancy Patterns in an Office Building Through the Use of Occupancy Sensor Data. Energy and Buildings 67 (December): 587-595. doi:10.1016/j.enbuild.2013.08.062], are used in three Department of Energy (DOE) reference office building models and four calibrated models of existing buildings. The total energy consumption between the two schedules for an assumed private office dominate floor plan layout ranges between 21.5-39.1% and 0.8-5.8% for an open office dominate plan in reference buildings. Calibrated models range from 5.5% to 16.8%. These results are meant to represent a reasonable range of potential impacts of occupancy diversity factors, and are thus derived by applying occupancy profiles directly to occupancy, lighting, plug load, and ventilation schedules.