Estimating time constants for over 10,000 residential buildings in North America: towards a statistical characterization of thermal dynamics
Open accessAbstract
Understanding the dynamic response of a building is essential in the design of sustainable energy-efficient buildings. Using data from over 10,000 smart thermostats, this study identifies patterns in the dynamic thermal response of residential buildings in Canada and the United States (US). The data set consists of one year of measurements recorded at 5-minute intervals for the indoor and outdoor air temperature as well as HVAC equipment run times. This study focuses on identifying effective values of time constants for the houses by applying the following procedure. First, periods complying with the following basic criteria are identified: a) the house is under free-floating conditions (i.e. when the HVAC system is switched off) for more than three hours and b) the outdoor temperature remains approximately constant (the outdoor temperature change is smaller than or equal to 2°C). Second, for each identified period, time constant values are determined by tracking the temperature responses of the house. These values are determined assuming the characteristic exponential decay of a first-order resistance-capacitance (RC) thermal model. Finally, a statistical analysis is applied to identify a typical range of effective time constant values according to month. Consequently, calculations show significant differences between estimated values for the summer and winter months, which may be attributed to occupant behaviour. In winter, the majority of time constants range from 15 to 55 hours. In summer, most of time constants vary between less than 1 hour and 18 hours due to occupants opening windows. In addition, the dependence of the time constant on the age of the home is investigated.
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Heat loss coefficients and time constants used in the simulation of the park of buildings correspond to typical values for Canadian detached houses, as confirmed by field measurements [14,33,34].
“The heat loss coefficients and time constants used in the simulation of the park of buildings correspond to typical values for Canadian detached houses as confirmed by field measurements reported in [14,33,34] and illustrated by Figure 3.”
From EV Overnight Charging Strategy in Residential Sector: Case of Winter Season in Quebec (2021) · cites this paper as [34]
The Abstract and Results (pages not specified in our copy) derive typical residential time constants from smart-thermostat measurements in Canada and the US. The paper does not report heat loss coefficients or establish values specifically for Canadian detached houses; the Discussion says analysis by home type is future work. (LLM, conf=0.88)
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Research works printed but not linked: 3
- Miller, C., Nagy, Z., & Schlueter, A. (2017). A review of unsupervised statistical learning and visual analytics techniques applied to performance analysis of non-residential buildings. Renewable and Sustainable Energy Reviews, 1-13.
- Palensky, P., & Dietrich, D. (2011). Demand side management: Demand response, intelligent energy systems, and smart loads. IEEE Transactions on Industrial Informatics, 7(3), 381- 388.
- Zawada, B. (2017). Experimental determination of parameters in models of indoor air temperature response to reduction in supplied energy. Journal of Building Physics, 40(4), 346-371.
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EV Overnight Charging Strategy in Residential Sector: Case of Winter Season in Quebec
Cardenas, A., Guzman, C., & Martinez, W. (2021) · Vehicles · doi:10.3390/vehicles3030034 · Cited by 19 · see citing works
“Heat loss coefficients and time constants distribution for the emulated park of residential buildings (from [14,33,34]).”
BackgroundMethodHuman-in-the-Loop AI for HVAC Management Enhancing Comfort and Energy Efficiency
Liang, X., de Nijs, F., Say, B., & Wang, H. (2025) · Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems · doi:10.1145/3679240.3734587 · Cited by 14 · see citing works
- Authors
- John, C., Vallianos, C., Candanedo, J., & Athienitis, A.
- Affiliations
- Concordia University (CA)
- Corresponding author
- John, Camille
- Venue
- Healthy, Intelligent and Resilient Buildings and Urban Environments
- Published
- 2018
- Pages
- 1383-1388
- OpenAlex
- W2964399403
- Cited by
- 17
- References
- 0
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 1 · 2023: 7 · 2022: 1 · 2021: 2 · 2020: 1
- FWCI
- 1.48
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc-sa
- Locations
- Healthy, Intelligent and Resilient Buildings and Urban Environments (publishedVersion, cc-by-nc-sa)
- Syracuse University Libraries (Syracuse University) (submittedVersion, cc-by-nc-sa)
- Syracuse University Libraries
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Topics
- Physical Sciences › Engineering › Building and Construction › Building Energy and Comfort Optimization
- Physical Sciences › Engineering › Building and Construction › Building energy efficiency and sustainability
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Keywords
- building thermal dynamics, time constant, residential buildings, smart thermostats, seasonal variation, occupant behavior, window openings, energy-efficient building design, Canada, United States
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