A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Modeling window and thermostat use behavior to inform sequences of operation in mixed-mode ventilation buildings
Operable windows have become desirable design features of modern mechanically ventilated office buildings in North America. While they improve perceived control and adaptive comfort, their inappropriate use poses risks associated with increased heating and cooling energy use. Therefore, the sequence of operations for terminal devices serving zones with operable windows should be designed in recognition of these risks, which in turn should be informed by research investigating occupants’ window and thermostat use behavior. To this end, this paper examines window and thermostat use data collected from two mixed-mode ventilation buildings in Ottawa, Canada. Discrete-time Markov logistic regression models and decision tree models were established to predict the likelihood of thermostat keypress and window opening/closing instances and identify the indoor conditions that trigger these actions. Based on this analysis, a set of preliminary recommendations is developed to improve terminal device sequencing in mixed-mode ventilation buildings in cold climates such that the comfort and energy savings potential of operable windows can be fully realized. The recommendations include applying thermostat setpoint setback to encourage occupants to open windows when conditions are advantageous for saving energy and discourage occupants from opening windows when energy penalties may be caused.
Modeling window and thermostat use behavior to inform sequences of operation in mixed-mode ventilation buildings
Operable windows have become desirable design features of modern mechanically ventilated office buildings in North America. While they improve perceived control and adaptive comfort, their inappropriate use poses risks associated with increased heating and cooling energy use. Therefore, the sequence of operations for terminal devices serving zones with operable windows should be designed in recognition of these risks, which in turn should be informed by research investigating occupants’ window and thermostat use behavior. To this end, this paper examines window and thermostat use data collected from two mixed-mode ventilation buildings in Ottawa, Canada. Discrete-time Markov logistic regression models and decision tree models were established to predict the likelihood of thermostat keypress and window opening/closing instances and identify the indoor conditions that trigger these actions. Based on this analysis, a set of preliminary recommendations is developed to improve terminal device sequencing in mixed-mode ventilation buildings in cold climates such that the comfort and energy savings potential of operable windows can be fully realized. The recommendations include applying thermostat setpoint setback to encourage occupants to open windows when conditions are advantageous for saving energy and discourage occupants from opening windows when energy penalties may be caused.
Modeling window and thermostat use behavior to inform sequences of operation in mixed-mode ventilation buildings
Liu, Weihao (author) / Gunay, H. Burak (author) / Ouf, Mohamed M. (author)
Science and Technology for the Built Environment ; 27 ; 1204-1220
2021-09-13
17 pages
Article (Journal)
Electronic Resource
Unknown
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