[1] J. A. Leech,W. C. Nelson, R. T. Burnett, S. Aaron, and M. E. Raizenne, “It’s about time: A comparison of Canadian and American time-activity patterns,” Journal of Exposure Analysis and Environmental Epidemiology, vol. 12, no. 6, pp. 427–432, 2002.
[2] Office of Energy Efficiency, “Energy Use Data Handbook Tables – 1990 to 2017,” National Resources Canada, Tech. Rep., 2019. [Online]. Available: https : / / oee.nrcan.gc.ca/corporate/statistics/neud/dpa/menus/trends/
handbook/tables.cfm.
[3] U.S. Energy Information Administration, “April 2019 Monthly Energy Review,” U.S.
Department of Energy, Tech. Rep., 2019. [Online]. Available: https://www.eia.gov/totalenergy/data/monthly/.
[4] U.S. Environmental Protection Agency, Greenhouse Gas Emissions : Sources of Greenhouse Gas Emissions, 2020. [Online]. Available: https://www.epa.gov/ghgemissions/sources-greenhouse-gas-emissions (visited on 07/01/2020).
[5] U.S. Energy Information Administration, “2015 Residential Energy Consumption Survey,” U.S. Department of Energy, Tech. Rep., 2018. [Online]. Available: https://www.eia.gov/consumption/residential/data/2015/.
[6] Canada Energy Regulator, “Canada’s Energy Future 2019 Energy Supply and Demand Projections to 2040,” Canada Energy Regulator, Tech. Rep., 2019. [Online]. Available: https://www.cer-rec.gc.ca/en/data-analysis/canada-energyfuture/2019/index.html.
[7] U.S. Energy Information Administration, “Annual Energy Outlook 2019 with projections to 2050,” U.S. Department of Energy, Tech. Rep., 2019. [Online]. Available: https://www.eia.gov/outlooks/aeo/pdf/0383(2017).pdf.
[8] J. Manyika, M. Chui, P. Bisson, J. Woetzel, R. Dobbs, J. Bughin, and D. Aharon, “The Internet of Things: Mapping the value beyond the hype,” Tech. Rep. June, 2015, p. 144. [Online]. Available: https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-internet-of-things-thevalue-of-digitizing-the-physical-world.
[9] Statistics Canada, Table 11-10-0222-01: Household spending, Canada, regions and provinces, 2019. [Online]. Available: https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=1110022201.
[10] Canada Energy Regulator, Market Snapshot: Fuel poverty across Canada – lower energy efficiency in lower income households, 2017. [Online]. Available: https://www.cer-rec.gc.ca/nrg/ntgrtd/mrkt/snpsht/2017/08-05flpvrt-eng.html?=undefined%7B%5C&%7Dwbdisable=true (visited on 07/01/2018).
[11] D. J. Bednar and T. G. Reames, “Recognition of and response to energy poverty in the United States,” Nature Energy, vol. 5, no. June, pp. 432–439, 2020.
[12] S. Jessel, S. Sawyer, and D. Hern´andez, “Energy, Poverty, and Health in Climate Change: A Comprehensive Review of an Emerging Literature,” Frontiers in Public Health, vol. 7,
no. December, 2019.
[13] A. T. D. Perera, V. M. Nik, D. Chen, J.-L. Scartezzini, and T. Hong, “Quantifying the impacts of climate change and extreme climate events on energy systems,” Nature Energy,
vol. 5, no. 2, pp. 150–159, 2020.
[14] W. Maclay and Maclay Architects, The New Net Zero: Leading-Edge Design and Construction of Homes and Buildings for a Renewable Energy Future. White River Junction, VT: Chelsea Green Publishing, 2014.
[15] J. Zheng, D. W. Gao, and L. Lin, “Smart meters in smart grid: An overview,” in IEEE Green Technologies Conference, Denver, CO, United states, 2013, pp. 57–64.
[16] J. Rotondo, R. Johnson, N. Gonzalez, A. Waranowski, C. Badger, N. Lange, E. Goldman, and R. Foster, “Overview of Existing and Future Residential Use Cases for Connected
Thermostats,” U.S. Department of Energy, Tech. Rep., 2016. [Online]. Available:https://www.energy.gov/sites/prod/files/2016/12/f34/
Overview%20of%20Existing%20Future%20Residential%20Use%20Cases%20for%20CT%7B%5C_%7D2016-12-16.pdf.
[17] A. Gonzalez-Vidal, A. P. Ramallo-Gonzalez, F. Terroso-Saenz, and A. Skarmeta, “Data driven modeling for energy consumption prediction in smart buildings,” in 2017 IEEE International Conference on Big Data (Big Data), Piscataway, NJ, USA, 2017, pp. 4562–9.
[18] G. Baasch, P. Westermann, and R. Evins, “Identifying whole-building heat loss coefficient from heterogeneous sensor data: An empirical survey of gray and black box approaches,” Energy and Buildings, vol. 241, p. 110 889, 2021.
[19] C. Miller, Z. Nagy, and A. Schlueter, “A review of unsupervised statistical learning and visual analytics techniques applied to performance analysis of non-residential buildings,” Renewable and Sustainable Energy Reviews, pp. 1–13, 2017.
[20] A. Kavousian, R. Rajagopal, and M. Fischer, “Determinants of residential electricity consumption: using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants’ behavior,” Energy (UK), vol. 55, pp. 184–94, 2013.
[21] S. Verbeke and A. Audenaert, “Thermal inertia in buildings: A review of impacts across climate and building use,” Renewable and Sustainable Energy Reviews, vol. 82, no. August 2017, pp. 2300–2318, 2018.
[22] Building Science Corporation, “Thermal Metric Summary Report,” Tech. Rep., 2013, p. 153. [Online]. Available: https://www.buildingscience.com/documents/special/thermal- metric- documents/thermal- metric- summaryreport.
[23] A. J. Ghajar and Y. A. Cengel, Heat and Mass Transfer: Fundamentals and Applications. McGraw-Hill Education, 2014.
[24] J. Straube, Thermal Control in Buildings, 2006. [Online]. Available: https://www.buildingscience.com/documents/digests/bsd-011-thermal-controlin-buildings (visited on 04/01/2018).
[25] T. Kesik, L. O’Brien, A. Ozkan, and A. Chong, “Thermal Resilience Design Guide,” University of Toronto, Tech. Rep., 2019. [Online]. Available: https://pbs.daniels.utoronto.ca/faculty/kesik%7B%5C_%7Dt/PBS/Kesik-Resources/Thermal-Resilience-Guide-v1.0-May2019.pdf.
[26] P. Gass, D. Echeverr´ıa, and A. Asadollahi, “Cities and Smart Grids in Canada,” International Institute for Sustainable Development, Tech. Rep. September, 2017, p. 36. [Online].
Available: https://www.iisd.org/system/files/publications/cities-smart-grids-canada.pdf.
[27] W. A. Beckman, L. Broman, A. Fiksel, S. A. Klein, E. Lindberg, M. Schuler, and J. Thornton, “TRNSYS. Most complete solar energy system modeling and simulation software,” Renewable energy, vol. 5, no. 1 -4 pt 1, pp. 486–488, 1994.
[28] D. B. Crawley, L. K. Lawrie, F. C.Winkelmann,W. F. Buhl, Y. J. Huang, C. O. Pedersen, R. K. Strand, R. J. Liesen, D. E. Fisher, M. J.Witte, and J. Glazer, “EnergyPlus: Creating a new-generation building energy simulation program,” Energy and Buildings, vol. 33,
no. 4, pp. 319–331, 2001.
[29] James J. Hirsh and Associates, The Home of DOE-2 based Building Energy Use and Cost Analysis Software. [Online]. Available: https://doe2.com/ (visited on 06/01/2019).
[30] D. Coakley, P. Raftery, and M. Keane, A review of methods to match building energy simulation models to measured data, 2014.
[31] M. R. Braun, H. Altan, and S. B. Beck, “Using regression analysis to predict the future energy consumption of a supermarket in the UK,” Applied Energy, vol. 130, pp. 305–313, 2014.
[32] A. S. Ahmad, M. Y. Hassan, M. P. Abdullah, H. A. Rahman, F. Hussin, H. Abdullah, and R. Saidur, “A review on applications of ANN and SVM for building electrical energy consumption forecasting,” Renewable and Sustainable Energy Reviews, vol. 33, pp. 102–109, 2014.
[33] R. Kramer, J. van Schijndel, and H. Schellen, “Simplified thermal and hygric building models: A literature review,” Frontiers of Architectural Research, pp. 318–325, 2012.
[34] A. Athienitis and W. O’Brien, Modeling, design, and optimization of net-zero energy buildings. 2015.
[35] G. Burnand, “The study of the thermal behaviour of structures by electrical analogy,” British Journal of Applied Physics, vol. 3, no. 2, pp. 50–53, 1952.
[36] K. A. Antonopoulos and E. P. Koronaki, “Effect of indoor mass on the time constant and thermal delay of buildings,” International Journal of Energy Research, vol. 24, no. 5, pp. 391–402, 2000.
[37] G. Reynders, J. Diriken, and D. Saelens, “Quality of grey-box models and identified parameters as function of the accuracy of input and observation signals,” Energy Build. (Netherlands), vol. 82, pp. 263–74, 2014.
[38] H. Harb, N. Boyanov, L. Hernandez, R. Streblow, and D. M¨uller, “Development and validation of grey-box models for forecasting the thermal response of occupied buildings,” Energy and Buildings, vol. 117, pp. 199–207, 2016.
[39] G. E. Box, “Science and statistics,” Journal of the American Statistical Association, vol. 71, no. 356, pp. 791–799, 1976.
[40] T. Hong and S. H. Lee, “Integrating physics-based models with sensor data: An inverse modeling approach,” Building and Environment, vol. 154, no. March, pp. 23–31, 2019.
[41] K. A. Antonopoulos and C. Tzivanidis, “Time constant of Greek buildings,” Energy (Oxford), vol. 20, no. 8, p. 785, 1995.
[42] ——, “Finite-difference prediction of transient indoor temperature and related correlation based on the building time constant,” International Journal of Energy Research, vol. 20, no. 6, pp. 507–520, 1996.
[43] T. Catalina, J. Virgone, and E. Blanco, “Development and validation of regression models to predict monthly heating demand for residential buildings,” Energy and Buildings, vol. 40, no. 10, pp. 1825–1832, 2008.
[44] J. Karlsson, L.Wadso, and M. Oberg, “A conceptual model that simulates the influence of high thermal inertia in building structures,” in fib Symposium 2012: Concrete Structures for Sustainable Community - Proceedings, Stockholm, Sweden, 2012, pp. 631–634.
[45] I. S. Walker and A. K. Meier, “Residential Thermostats : Comfort Controls in California Homes,” Lawrence Berkeley National Laboratory, Tech. Rep., 2008.
[46] Honeywell International Inc, Non-Programmable Thermostats. [Online]. Available: https://www.honeywellhome.com/us/en/products/air/thermostats/
non-programmable-thermostats/manual-4-wire-premium-baseboardthermostat-ct410b1017-e1/ (visited on 05/01/2021).
[47] ——, Thermostat. [Online]. Available:https://www.honeywellhome.com/us/en/products/air/thermostats/non-programmable-thermostats/the-round-mercury-free-thermostat-manual-changeover-singlestage-ct87n1001-u1/ (visited on 05/01/2021).
[48] M. Pritoni, A. K. Meier, C. Aragon, D. Perry, and T. Peffer, “Energy efficiency and the misuse of programmable thermostats: The effectiveness of crowdsourcing for understanding household behavior,” Energy Research & Social Science, vol. 8, pp. 190–197,
2015.
[49] ecobee Inc, Smart Thermostat with voice control and Smart Sensor. [Online]. Available:https://www.ecobee.com/en-us/smart-thermostats/smart-wifithermostat-with-voice-control/ (visited on 05/01/2021).
[50] Sensibo, Sensibo: Smart Air Sensing&Control. [Online]. Available: https://sensibo.com/products/sensibo-air-bundle (visited on 05/01/2021).
[51] Honeywell International Inc, T5+ Smart Home Thermostat. [Online]. Available: https://www.honeywellhome.com/us/en/products/air/thermostats/
wifi-thermostats/t5-smart-thermostat-with-c-wire-adapterrcht8612wf2005-u/ (visited on 05/01/2021).
[52] Mysa Smart Thermostats, Mysa for Electric Baseboard Heaters. [Online]. Available:https://shop.getmysa.com/products/mysa- baseboard (visited on 05/01/2021).
[53] Google Inc, Nest thermostats. [Online]. Available: https://store.google.com/ca/magazine/compare%7B%5C_%7Dthermostats?hl=en-GB (visited on 05/01/2021).
[54] T. A. Reddy, Applied Data Analysis and Modeling for Energy Engineers and Scientists.
2011.
[55] J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques. 2012.
[56] Z. Yu, F. Haghighat, and B. C. Fung, “Advances and challenges in building engineering and data mining applications for energy-efficient communities,” Sustainable Cities and Society, vol. 25, pp. 33–38, 2016.
[57] P. Chapman, J. Clinton, R. Kerber, T. Khabaza, T. Reinartz, C. Shearer, and R. Wirth, “Step-by-step data mining guide,” SPSS inc, Tech. Rep., 2000, pp. 1–78. [Online]. Available: http://www.crisp-dm.org/CRISPWP-0800.pdf.
[58] D. T. Larose and C. D. Larose, Data mining and predictive analytics, English, Hoboken, New Jersey, 2015.
[59] ecobee Inc, Installation Guide ecobee 3, 2014. [Online]. Available: https://www.ecobee.com/wp-content/uploads/2013/12/ecobee3%7B%5C_%7DInstallationGuide.
pdf.
[60] NumFocus, Pandas - Python Data Analysis Library. [Online]. Available: https://pandas.pydata.org/ (visited on 12/01/2020).
[61] American Society of Heating Refrigerating and Air-Conditioning Engineers, ANSI/ASHRAE Standard 90.2-2018: Energy-Efficient Design of Low-Rise Residential Buildings. Atlanta, GA, 2018.
[62] National Renewable Energy Laboratory, Ashrae Climate Zones, 2011. [Online]. Available: https://openei.org/wiki/ASHRAE%7B%5C_%7DClimate%7B%5C_
%7DZones (visited on 10/01/2018).
[63] R. Talami, C. Karmann, F. Bauman, S. Schiavon, and P. Raftery, “Recent trends in radiant system technology in North America,” Tech. Rep., 2017.
[64] J. Vivian, A. Zarrella, G. Emmi, and M. De Carli, “An evaluation of the suitability of lumped-capacitance models in calculating energy needs and thermal behaviour of buildings,” Energy and Buildings, vol. 150, pp. 447–465, 2017.
[65] C. John, C. Vallianos, J. Candanedo, and A. Athienitis, “Estimating time constants for over 10,000 residential buildings in North America: towards a statistical characterization of thermal dynamics,” in Proceedings of the 7th International Building Physics Conference - Healthy, Intelligent and Resilient Buildings and Urban Environments, 2018.
[66] The SciPy Community, scipy.stats.kstest - Scipy v1.6.1 Reference Guide. [Online]. Available:
https://docs.scipy.org/doc/scipy/reference/generated/
scipy.stats.kstest.html (visited on 03/01/2020).
[67] ——, scipy.stats.johnsonsb - SciPy v1.6.1 Reference Guide. [Online]. Available: https:/ / docs. scipy.org/doc/scipy/reference/ generated/scipy.stats.johnsonsb.html (visited on 03/01/2021).
[68] M. J. Oliveira Pan˜ao, N. M. Mateus, and G. Carrilho da Grac¸a, “Measured and modeled performance of internal mass as a thermal energy battery for energy flexible residential buildings,” Applied Energy, vol. 239, no. October 2018, pp. 252–267, 2019.
[69] P. Palensky and D. Dietrich, “Demand side management: Demand response, intelligent energy systems, and smart loads,” IEEE Transactions on Industrial Informatics, vol. 7, no. 3, pp. 381–388, 2011.
[70] E. Chung, What caused the deadly power outages in Texas and how Canada’s grid compares, 2021. [Online]. Available: https://www.cbc.ca/news/technology/power-outages-texas-canada-1.5920833 (visited on 02/01/2021).
[71] J. A. Candanedo, V. R. Dehkordi, and P. Lopez, “A multi-level architecture to facilitate MPC implementation in commercial buildings : basic principles and case study,” no. May, 2013.
[72] N. Henao, M. Fournier, S. Kelouwani, and T. De, Characterizing Smart Thermostats Operation in Residential Zoned Heating Systems and its Impact on Energy Saving Metrics,” in Proceedings of eSim 2018, the 10 conference of IBPSA-Canada, 2018, pp. 17–
25.
[73] American Society of Heating Refrigerating and Air-Conditioning Engineers, 2017 ASHRAE Handbook: Fundamentals. Atlanta, GA, 2017.
[74] J. Date, J. A. Candanedo, and A. K. Athienitis, “Control-Oriented Modelling of Thermal Zones in a House : A Multi-Level Approach,” in International High Performance Buildings Conference, 2016, pp. 1–10.
[75] Y. Chen, Z. Tong, W. Wu, H. Samuelson, A. Malkawi, and L. Norford, “Achieving natural ventilation potential in practice: Control schemes and levels of automation,” Applied Energy, vol. 235, no. November 2018, pp. 1141–1152, 2019.
[76] A. Rabl and L. K. Norford, “Peak load reduction by preconditioning buildings at night,” International Journal of Energy Research, vol. 15, no. 9, pp. 781–98, 1991.
[77] C. John, “Grey-box models: toward a systematic approach for design and operation of thermal zones,” Countribution to foundation paper by J. A. Candanedo, A. K. Athienitis et al., in preparation,
[78] ecobee Inc, How accurate is the temperature sensor in the ecobee? [Online]. Available:https://support.ecobee.com/hc/en- us/articles/227869067-How-accurate-is-the-temperature-sensor-in-the-ecobee- (visited
on 07/01/2018).