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This paper examines temperature, airflow, and binary window position data of several rooms in an institutional building in Canada during three months of the summer to identify possible motivations for window usage and to estimate cooling energy usage. Window state change information was collected from contact sensors for 27 rooms, 16 of which had window openings and closings during the three-month period. Thermostat and air handling data were utilized to estimate the room level cooling energy usage. The resulting data was analyzed to determine if patterns in the window state and intuitive thermal behavior could be observed. A total of 197 window openings and closings occurred for all the rooms. It was found that indoor and outdoor air temperature did not correlate well with window opening, and that window state changes cannot be reliably predicted with the data collected. A significant number of occupants (25%) were found to change their window position when the outdoor temperature was higher than the indoor temperature over the three-month period. Occupant preferences were found to be unpredictable. Increasing window usage was found to decrease cooling energy usage at the room level. Instrumentation bias error was high relative to the measurements obtained in this study and limits the conclusiveness of results.
Citation: 2019 Annual Conference, Kansas City, MO, Conference Papers
Product Details
- Published:
- 2019
- Number of Pages:
- 9
- Units of Measure:
- Dual
- File Size:
- 1 file , 2.1 MB
- Product Code(s):
- D-KC-19-C038
