02408nas a2200229   4500008003900000022001400039245011700053210006900170260001200239300001200251490000600263520165000269653002401919653002001943653002201963653002201985653002102007653002502028100002002053700001902073856008602092       2013                          d  a1996-874400aStatistical Analysis and Modeling of Occupancy Patterns in Open-Plan Offices using Measured Lighting-Switch Data0 aStatistical Analysis and Modeling of Occupancy Patterns in OpenP  c03/2013  a23–320 v63 a<p>Occupancy profile is one of the driving factors behind discrepancies between the measured and simulated energy consumption of buildings. The frequencies of occupants leaving their offices and the corresponding durations of absences have significant impact on energy use and the operational controls of buildings. This study used statistical methods to analyze the occupancy status, based on measured lighting-switch data in five-minute intervals, for a total of 200 open-plan (cubicle) offices. Five typical occupancy patterns were identified based on the average daily 24-hour profiles of the presence of occupants in their cubicles. These statistical patterns were represented by a one-square curve, a one-valley curve, a two-valley curve, a variable curve, and a flat curve. The key parameters that define the occupancy model are the average occupancy profile together with probability distributions of absence duration, and the number of times an occupant is absent from the cubicle. The statistical results also reveal that the number of absence occurrences decreases as total daily presence hours decrease, and the duration of absence from the cubicle decreases as the frequency of absence increases. The developed occupancy model captures the stochastic nature of occupants moving in and out of cubicles, and can be used to generate a more realistic occupancy schedule. This is crucial for improving the evaluation of the energy saving potential of occupancy based technologies and controls using building simulations. Finally, to demonstrate the use of the occupancy model, weekday occupant schedules were generated and discussed.</p>10abuilding simulation10aoccupancy model10aoccupancy pattern10aoccupant schedule10aoffice buildings10astatistical analysis1 aChang, Wen-Kuei1 aHong, Tianzhen  uhttps://simulationresearch.lbl.gov/publications/statistical-analysis-and-modeling