Siva Barathi
Indian Institute for Human Settlements, Bangalore, India
Thounaojam Amanda
Indian Institute for Human Settlements, Bangalore, India
Corresponding Author: amandat@iihs.ac.in
Prasad Vaidya
Indian Institute for Human Settlements, Bangalore, India
A Gopikrishna
Indian Institute for Human Settlements, Bangalore, India
Dalavai Uthej
Indian Institute for Human Settlements, Bangalore, India
Tandon Vipin
Manipal School of Architecture and Planning, Manipal, India
Cite this article
Barathi, S., Amanda, T., Vaidya, P., Gopikrishna, A., Uthej, D., Vipin, T. (2024). A Control Sequence for Prioritising Ceiling Fan Operation Over Air Conditioners Using Machine Learning to Determine Thermal Comfort. In Proceedings of Energise 2023- Lifestyle, Energy Efficiency, and Climate Action, pp 93–99, Alliance for an Energy Efficient Economy. https://doi.org/10.62576/BOWF7492
Highlights
- Machine learning for predicting OT as a scalable approach for adaptive comfort controls.
- Using the corrective power index for cooling to adjust the upper limit of the thermal comfort band based on air speed achieved by ceiling fans.
- Thermal comfort study of comfort votes and energy consumption, compared to a 24ºC constant setpoint.
- Cooling energy savings of more than 97% with higher comfort votes for the demonstrated control sequence.
Abstract
This study aims to use the corrective power of personal comfort systems of -1K to -6K [2] and prioritise ceiling fan operation over AC to reduce energy consumption and implement controls based on Operative temperature (OT). We use a machine learning algorithm that takes indoor air temperature and outdoor values for air temperature, wind speed, and relative humidity as inputs and predicts the indoor OT of a space. The predicted OT is used to determine thermal comfort according to the India Model for Adaptive Comfort (IMAC). We have developed a control sequence that automates ceiling fan speed operation and air-conditioning (AC) set-points. The control sequence is tested in two different rooms; one, a passively designed building with an insulated envelope, and another, a typical uninsulated building, tested against a base case of 24°C set-point suggested by the Bureau of Energy Efficiency (BEE), India, with no ceiling fans operating. The testing shows that the control sequence that prioritises ceiling fan operation has higher comfort votes than the BEE base case, and the control sequence provided more than 80% cooling energy savings compared to the BEE base case.
Keywords
Adaptive Thermal Comfort, Operative Temperature, Corrective Power Index, Machine Learning, Ceiling Fans
References
- International Energy Agency, “World Energy Outlook 2018. IEA, 2018. iea.org/weo
- Ozone Cell Ministry of Environment, “INDIA COOLING ACTION PLAN,” MOEFCC, 2019.
- A. De, A. Thounaojam, P. Vaidya, D. Sinha, and S. M. Raveendran, “Predicting Operative Temperature with Machine Learning,” 2020.
- ASHRAE. (2020). ANSI/ASHRAE Standard 55-2020. ASHRAE Standards. www.ashrae.org
- H. Zhang, E. Arens, and Y. Zhai, “A review of the corrective power of personal comfort systems in non-neutral ambient environments,” Build Environ, vol. 91, pp. 15-41, Sep. 2015. https://doi.org/10.1016/j.buildenv.2015.03.013
- R. de Dear, and G.S. Brager, “Developing an Adaptive Model of Thermal Comfort and Preference-Final Report on RP-884, 1997. In Macquarie Research Ltd., Center for Environmental Design Research. https://www.researchgate.net/publication/269097185
- S. Manu, Y. Shukla, Y., R. Rawal, L. E. Thomas, and R. de Dear, “Field studies of thermal comfort across multiple climate zones for the subcontinent: India Model for Adaptive Comfort (IMAC)” Buil. Env. vol. 98, pp. 55-70, 2016. https://doi.org/10.1016/j.buildenv.2015.12.019
- ASHRAE. (2017). ANSI/ASHRAE Standard 55-2017. ASHRAE Standards. www.ashrae.org
- P. O. Fanger, and J. Toftum, “Extension of the PMV model to non-air-conditioned buildings in warm climates.” Ener. Build., vol. 34, pp. 533-536, 2002. https://doi.org/10.1016/S0378-7788(02)00003-8
- C. Candido, and R. de Dear, “From thermal boredom to thermal pleasure: a brief literature review. Ambiente Construído,” vol. 12, pp. 81-90, 2012. https://doi.org/10.1590/s1678-86212012000100006.
- Y. Zhai, E. Arens, E., K. Elsworth, and H. Zhang, “Selecting air speeds for cooling at sedentary and nonsedentary office activity levels,” Buil. Env., vol 122, pp. 247-257, 2017. https://doi.org/10.1016/j.buildenv.2017.06.027
- H. Zhang, E. Arens, and Y. Zhai, “A review of the corrective power of personal comfort systems in non-neutral ambient environments.” Build. Env., vol. 91, pp. 15-41, 2015. https://doi.org/10.1016/j.buildenv.2015.03.013
- D. Miller, P. Raftery, M. Nakajima, S. Salo, L. T. Graham, T. Peffer, M. Delgado, H. Zhang, G. Brager, D. Douglass-Jaimes, G. Paliaga, S. Cohn, M. Greene, and A. Brooks, “Cooling energy savings and occupant feedback in a two year retrofit evaluation of 99 automated ceiling fans staged with air conditioning.” Energ. Build., vol 251, 111319, 2021. https://doi.org/10.1016/j.enbuild.2021.111319
- P. Raftery, D. Miller, and H. Zhang, “Integrating Smart Ceiling Fans and Communicating Thermostats to Provide Energy-Efficient Comfort,” Final Report. UC Berkeley: Center for the Built Environmentvol, 2020. https://escholarship.org/uc/item/91z0m3xw
- A. Lipczynska, S. Schiavon, L. T. Graham, „Thermal comfort and self-reported productivity in an office with ceiling fans in the tropics.” Build. Env., vol. 135, pp. 202-212, 2018. https://doi.org/10.1016/j.buildenv.2018.03.013
- A. Malik, C. Bongers, B. McBain, O. Rey-Lescure, R. de Dear, A. Capon, and M. Lenzen, “The potential for indoor fans to change air conditioning use while maintaining human thermal comfort during hot weather: an analysis of energy demand and associated greenhouse gas emissions.” Lancet. Planetary health, vol. 6, pp. E301-E309, 2022. https://doi.org/10.1016/S2542-5196(22)00042-0
- F. Tartarini, S. Schiavon, T. Cheung, T. Hoyt, “CBE Thermal Comfort Tool: Online tool for thermal comfort calculations and visualizations.” SoftwareX, vol. 12, 100563, 2020. https://doi.org/10.1016/j.softx.2020.100563
- Y. Gao, H. Zhang, E. Arens, E. Present, B. Ning, Y. Zhai, J. Pantelic, M. Luo, L. Zhao, P. Raftery, and S. Liu, “Ceiling fan air speeds around desks and office partitions.” Build. Env., vol. 124, pp. 412-440, 2017. https://doi.org/10.1016/j.buildenv.2017.08.029
Bishal Thapa
Fred Sherman
Sumedha Malaviya
Satish Kumar
The three main global energy concerns of providing access to modern energy, enhancing the security of the energy supply, and minimising the impact of energy systems on the climate have an impact on both national and international energy governance. To develop solutions that address the many facets of these difficulties, however, a variety of actors and stakeholders must be included due to the complexity of the energy challenges.
Cities are responsible for more than 70% of the world’s energy consumption and 40% to 50% of its greenhouse gas emissions. Managing increasing urbanisation is a challenge, and nations must deal with the effects it will have on the environment in terms of energy and climate.
Our transition to a future with lower carbon emissions depends heavily on buildings. They are our places of residence, rest, and employment; they also account for around one-third of the world’s greenhouse gas emissions and nearly 40% of the world’s energy usage.