Long-Term field testing of the accuracy and HVAC energy savings potential of occupancy presence sensors in A Single-Family home

Pang, Zhihong; Guo, Mingyue; O’Neill, Zheng; Smith-Cortez, Blake; Yang, Zhiyao; Liu, Mingzhe; Dong, Bing

doi:10.1016/j.enbuild.2024.115161

Long-Term field testing of the accuracy and HVAC energy savings potential of occupancy presence sensors in A Single-Family home

Journal Article · Sun Dec 08 23:00:00 EST 2024 · Energy and Buildings

DOI:https://doi.org/10.1016/j.enbuild.2024.115161· OSTI ID:2479675

^[1]; ^[2]; O’Neill, Zheng ^[2]; Smith-Cortez, Blake ^[2]; Yang, Zhiyao ^[2]; ^[2]; Dong, Bing ^[3]

Louisiana State University, Baton Rouge, LA (United States); Texas A&M University, College Station, TX (United States); Texas A&M University
Texas A&M University, College Station, TX (United States)
Syracuse University, NY (United States)

The energy-saving potential of occupancy-centric smart thermostats has been extensively explored in simulations but lacked field testing for energy savings quantification and sensor performance assessment in real buildings. This paper presents a long-term field study conducted in a single-family home in Texas, U.S. to evaluate the performance of occupancy-centric controls (OCC) of HVAC (heating, ventilation, and air-conditioning) system in terms of energy savings, sensor accuracy, and impact on electric peak demand. The test site was equipped with a commercial off-the-shelf (COTS) smart thermostat and multiple occupancy presence sensors for OCC implementation. Additionally, a sub-metering system was installed to monitor electricity consumption of various end-use equipment, including the HVAC system. A supplementary device was installed to track the ground-truth occupancy for the accuracy evaluation of the occupancy presence sensor. Scenarios of baseline and OCC controls were alternated weekly over the 20-month testing period. The results indicated an effective OCC execution, as evidenced by indoor temperature profiles. During the 2023 cooling season, OCC achieved total energy savings of 1,958 kWh, corresponding to a 17.6% energy savings ratio. Under certain conditions, daily HVAC energy savings reached as high as 17 kWh, with a savings ratio of 35%. Sensor performance showed an overall accuracy of 83.8%, a False Positive Rate (FPR) of 12.8%, and a False Negative Rate (FNR) of 47.4%. A key limitation was the sensor’s inability to detect stationary occupants during sleep, leading to a midnight FNR of nearly 100% and significantly compromising thermal comfort. Additionally, the implementation of OCC resulted in extended periods of high electricity demand on summer afternoons, affecting occupant’s thermal comfort and posing potential challenges to community-level grid operations if OCC were widely adopted. Furthermore, this study addresses a critical research gap by empirically investigating energy-saving potential and occupancy sensor performance in residential buildings. Through a comprehensive field-testing study, the research examines the interrelationship between sensor accuracy, energy savings, and thermal comfort, an area that has received limited attention in the current literature.

View Accepted Manuscript (DOE)

Research Organization:: Texas A & M University, College Station, TX (United States)

Sponsoring Organization:: USDOE Advanced Research Projects Agency - Energy (ARPA-E)

Grant/Contract Number:: AR0001316

OSTI ID:: 2479675

Alternate ID(s):: OSTI ID: 2480747

Journal Information:: Energy and Buildings, Journal Name: Energy and Buildings Vol. 328; ISSN 0378-7788

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (32)

Extracting typical occupancy schedules from social media (TOSSM) and its integration with building energy modeling Lu, Xing; Feng, Fan; Pang, Zhihong Building Simulation, Vol. 14, Issue 1 https://doi.org/10.1007/s12273-020-0637-y	journal	May 2020
To be or not to be Cohen, Patricia Evaluation and Program Planning, Vol. 5, Issue 3 https://doi.org/10.1016/0149-7189(82)90076-3	journal	January 1982
Conditions for a cost-effective application of smart thermostat systems in residential buildings Schäuble, Dominik; Marian, Adela; Cremonese, Lorenzo Applied Energy, Vol. 262 https://doi.org/10.1016/j.apenergy.2020.114526	journal	March 2020
Nationwide HVAC energy-saving potential quantification for office buildings with occupant-centric controls in various climates Pang, Zhihong; Chen, Yan; Zhang, Jian Applied Energy, Vol. 279 https://doi.org/10.1016/j.apenergy.2020.115727	journal	December 2020
How much HVAC energy could be saved from the occupant-centric smart home thermostat: A nationwide simulation study Pang, Zhihong; Chen, Yan; Zhang, Jian Applied Energy, Vol. 283 https://doi.org/10.1016/j.apenergy.2020.116251	journal	February 2021
Energy-saving potential evaluation for primary schools with occupant-centric controls Ye, Yunyang; Chen, Yan; Zhang, Jian Applied Energy, Vol. 293 https://doi.org/10.1016/j.apenergy.2021.116854	journal	July 2021
Energy saving potential and repercussions on indoor air quality of demand controlled residential ventilation strategies Laverge, J.; Van Den Bossche, N.; Heijmans, N. Building and Environment, Vol. 46, Issue 7 https://doi.org/10.1016/j.buildenv.2011.01.023	journal	July 2011
Usability of residential thermostats: Preliminary investigations Meier, Alan; Aragon, Cecilia; Peffer, Therese Building and Environment, Vol. 46, Issue 10 https://doi.org/10.1016/j.buildenv.2011.03.009	journal	October 2011
Method for room occupancy detection based on trajectory of indoor climate sensor data Pedersen, Theis Heidmann; Nielsen, Kasper Ubbe; Petersen, Steffen Building and Environment, Vol. 115 https://doi.org/10.1016/j.buildenv.2017.01.023	journal	April 2017
Application of mobile positioning occupancy data for building energy simulation: An engineering case study Pang, Zhihong; Xu, Peng; O'Neill, Zheng Building and Environment, Vol. 141 https://doi.org/10.1016/j.buildenv.2018.05.030	journal	August 2018
Occupancy estimation with environmental sensors: The possibilities and limitations Chitnis, Shubham; Somu, Nivethitha; Kowli, Anupama Energy and Built Environment, Vol. 6, Issue 1 https://doi.org/10.1016/j.enbenv.2023.09.003	journal	February 2025
Assessment of the physical part of the temperature takeback for residential retrofits Deurinck, Mieke; Saelens, Dirk; Roels, Staf Energy and Buildings, Vol. 52 https://doi.org/10.1016/j.enbuild.2012.05.024	journal	September 2012
Experimental evaluation of the performance of chair sensors in an office space for occupancy detection and occupancy-driven control Labeodan, Timilehin; Aduda, Kennedy; Zeiler, Wim Energy and Buildings, Vol. 111 https://doi.org/10.1016/j.enbuild.2015.11.054	journal	January 2016
Estimating occupancy in heterogeneous sensor environment Amayri, Manar; Arora, Abhay; Ploix, Stephane Energy and Buildings, Vol. 129 https://doi.org/10.1016/j.enbuild.2016.07.026	journal	October 2016
Testing the accuracy of low-cost data streams for determining single-person office occupancy and their use for energy reduction of building services Newsham, Guy R.; Xue, Henry; Arsenault, Chantal Energy and Buildings, Vol. 135 https://doi.org/10.1016/j.enbuild.2016.11.029	journal	January 2017
Extracting typical occupancy data of different buildings from mobile positioning data Jiefan, Gu; Peng, Xu; Zhihong, Pang Energy and Buildings, Vol. 180 https://doi.org/10.1016/j.enbuild.2018.09.002	journal	December 2018
A review of smart building sensing system for better indoor environment control Dong, Bing; Prakash, Vishnu; Feng, Fan Energy and Buildings, Vol. 199 https://doi.org/10.1016/j.enbuild.2019.06.025	journal	September 2019
Multimodal sensor fusion framework for residential building occupancy detection Tan, Sin Yong; Jacoby, Margarite; Saha, Homagni Energy and Buildings, Vol. 258 https://doi.org/10.1016/j.enbuild.2021.111828	journal	March 2022
Quantification of HVAC energy savings through occupancy presence sensors in an apartment setting: Field testing and inverse modeling approach Pang, Zhihong; Guo, Mingyue; Smith-Cortez, Blake Energy and Buildings, Vol. 302 https://doi.org/10.1016/j.enbuild.2023.113752	journal	January 2024
Urban building energy performance prediction and retrofit analysis using data-driven machine learning approach Ali, Usman; Bano, Sobia; Shamsi, Mohammad Haris Energy and Buildings, Vol. 303 https://doi.org/10.1016/j.enbuild.2023.113768	journal	January 2024
Household transitions to energy efficient lighting Mills, Bradford; Schleich, Joachim Energy Economics, Vol. 46 https://doi.org/10.1016/j.eneco.2014.08.022	journal	November 2014
Energy efficiency and the misuse of programmable thermostats: The effectiveness of crowdsourcing for understanding household behavior Pritoni, Marco; Meier, Alan K.; Aragon, Cecilia Energy Research & Social Science, Vol. 8 https://doi.org/10.1016/j.erss.2015.06.002	journal	July 2015
Going smart, staying confused: Perceptions and use of smart thermostats in British homes Miu, Luciana M.; Mazur, Christoph M.; van Dam, Koen H. Energy Research & Social Science, Vol. 57 https://doi.org/10.1016/j.erss.2019.101228	journal	November 2019
Economic feasibility of energy efficiency measures in residential buildings Sadineni, Suresh B.; France, Todd M.; Boehm, Robert F. Renewable Energy, Vol. 36, Issue 11 https://doi.org/10.1016/j.renene.2011.04.006	journal	November 2011
Reducing U.S. Residential Energy Use and CO ₂ Emissions: How Much, How Soon, and at What Cost? Lima Azevedo, Inês; Morgan, M. Granger; Palmer, Karen Environmental Science & Technology, Vol. 47, Issue 6 https://doi.org/10.1021/es303688k	journal	February 2013
The carbon footprint of household energy use in the United States Goldstein, Benjamin; Gounaridis, Dimitrios; Newell, Joshua P. Proceedings of the National Academy of Sciences, Vol. 117, Issue 32 https://doi.org/10.1073/pnas.1922205117	journal	July 2020
Facilitating energy savings with programmable thermostats: evaluation and guidelines for the thermostat user interface Peffer, Therese; Perry, Daniel; Pritoni, Marco Ergonomics, Vol. 56, Issue 3 https://doi.org/10.1080/00140139.2012.718370	journal	March 2013
Quantifying the nationwide HVAC energy savings in large hotels: the role of occupant-centric controls Pang, Zhihong; Chen, Yan; Zhang, Jian Journal of Building Performance Simulation, Vol. 14, Issue 6 https://doi.org/10.1080/19401493.2021.1994650	journal	November 2021
The ASHRAE Great Energy Predictor III competition: Overview and results Miller, Clayton; Arjunan, Pandarasamy; Kathirgamanathan, Anjukan Science and Technology for the Built Environment, Vol. 26, Issue 10 https://doi.org/10.1080/23744731.2020.1795514	journal	August 2020
Reduction of HVAC system runtime due to occupancy-controlled smart thermostats in contemporary multi-unit residential building suites Stopps, H.; Touchie, M. F. IOP Conference Series: Materials Science and Engineering, Vol. 609 https://doi.org/10.1088/1757-899X/609/6/062013	journal	September 2019
Indoor Occupancy Estimation Using Particle Filter and SLEEPIR Sensor System Emad-ud-Din, Muhammad; Chen, Zhangjie; Wu, Libo IEEE Sensors Journal, Vol. 22, Issue 17 https://doi.org/10.1109/JSEN.2022.3192270	journal	September 2022
Improved Occupancy Detection Accuracy using PIR and Door Sensors for a Smart Thermostat Ho Kim, Sun; Jun Moon, Hyeun; Ran Yoon, Young Building Simulation Conference Proceedings https://doi.org/10.26868/25222708.2017.811	conference	August 2017

Similar Records

IoT-Based Comfort Control and Fault Diagnostics System for Energy-Efficient Homes

Technical Report · Fri Apr 19 00:00:00 EDT 2024 · OSTI ID:2338244

Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort

Journal Article · Thu Oct 15 00:00:00 EDT 2020 · Energies · OSTI ID:1721752

Nationwide HVAC Energy-Saving Potential Quantification for Office Buildings with Occupant-Centric Controls in Various Climates

Journal Article · Mon Nov 30 23:00:00 EST 2020 · Applied Energy · OSTI ID:1671034

Related Subjects

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Occupancy presence sensor
Occupancy-centric control
Residential building
Sensor error
Smart thermostat

Long-Term field testing of the accuracy and HVAC energy savings potential of occupancy presence sensors in A Single-Family home

Citation Formats

References (32)

Similar Records

Related Subjects