Sensor impacts on building and HVAC controls: A critical review for building energy performance

Bae, Yeonjin; Bhattacharya, Saptarshi; Cui, Borui; Lee, Seungjae; Li, Yanfei; Zhang, Liang; Im, Piljae; Adetola, Veronica; Vrabie, Draguna; Leach, Matt; Kuruganti, Teja

doi:10.1016/j.adapen.2021.100068

Title: Sensor impacts on building and HVAC controls: A critical review for building energy performance

Journal Article · 06 September 2021 · Advances in Applied Energy

DOI: https://doi.org/10.1016/j.adapen.2021.100068 · OSTI ID:1820780

^[1]; Bhattacharya, Saptarshi ^[2];

^[1]; Lee, Seungjae ^[1];

^[1]; Zhang, Liang ^[3];

^[1]; Adetola, Veronica ^[2]; Vrabie, Draguna ^[2]; Leach, Matt ^[3];

^[1]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Building Technologies Research and Integration Center
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
National Renewable Energy Lab. (NREL), Golden, CO (United States)

Building operations rely heavily on control systems and sensors. This paper provides a sophisticated literature review on sensor systems in building/HVAC systems, particularly in the context of controls, and their impacts on energy efficiency and thermal comfort. This study aims to understand the previous and current research and identify future research opportunities on this subject. The reviewed sensor systems were used for heuristic rule-based controls, local controls, and advanced optimal controls for existing and emerging technologies. Five major aspects of sensors are reviewed here: control loops for sensors, sensor types, sensor locations, sensor data, and a sensor impact evaluation framework. To augment the literature review, comprehensive standardized interviews were also conducted with relevant industry experts and practitioners. These interviews were designed and performed to (1) identify significant factors for selecting sensor sets and current undergoing issues, (2) identify potential improvements in sensor configuration/deployment, and (3) integrate expert (e.g., researcher, building operation practitioner) knowledge and experiences to develop structured use-case scenarios. Researchers collected and analyzed 31 interview responses for this paper.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1820780

Journal Information:: Advances in Applied Energy, Journal Name: Advances in Applied Energy Vol. 4; ISSN 2666-7924

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

References (77)

Singular Perturbation Method for Smart Building Temperature Control Using Occupant Feedback Gupta, Santosh K.; Kar, Koushik; Mishra, Sandipan Asian Journal of Control, Vol. 20, Issue 1 https://doi.org/10.1002/asjc.1587	journal	July 2017
Derivation and application of an expert fuzzy optimal control system Shoureshi, Rahmat; Rahmani, Karim Fuzzy Sets and Systems, Vol. 49, Issue 2 https://doi.org/10.1016/0165-0114(92)90316-V	journal	July 1992
Integrated comfort sensing system on indoor climate Kang, Jeongho; Park, Sekwang Sensors and Actuators A: Physical, Vol. 82, Issue 1-3 https://doi.org/10.1016/S0924-4247(00)00289-2	journal	May 2000
Building-to-grid predictive power flow control for demand response and demand flexibility programs Razmara, M.; Bharati, G. R.; Hanover, Drew Applied Energy, Vol. 203 https://doi.org/10.1016/j.apenergy.2017.06.040	journal	October 2017
Brick : Metadata schema for portable smart building applications Balaji, Bharathan; Bhattacharya, Arka; Fierro, Gabriel Applied Energy, Vol. 226 https://doi.org/10.1016/j.apenergy.2018.02.091	journal	September 2018
Data-driven model predictive control using random forests for building energy optimization and climate control Smarra, Francesco; Jain, Achin; de Rubeis, Tullio Applied Energy, Vol. 226 https://doi.org/10.1016/j.apenergy.2018.02.126	journal	September 2018
Approximate model predictive building control via machine learning Drgoňa, Ján; Picard, Damien; Kvasnica, Michal Applied Energy, Vol. 218 https://doi.org/10.1016/j.apenergy.2018.02.156	journal	May 2018
Occupancy-based buildings-to-grid integration framework for smart and connected communities Dong, Bing; Li, Zhaoxuan; Taha, Ahmad Applied Energy, Vol. 219 https://doi.org/10.1016/j.apenergy.2018.03.007	journal	June 2018
Human-in-the-loop HVAC operations: A quantitative review on occupancy, comfort, and energy-efficiency dimensions Jung, Wooyoung; Jazizadeh, Farrokh Applied Energy, Vol. 239 https://doi.org/10.1016/j.apenergy.2019.01.070	journal	April 2019
A novel simulation-based framework for sensor error impact analysis in smart building systems: A case study for a demand-controlled ventilation system Lu, Xing; O'Neill, Zheng; Li, Yanfei Applied Energy, Vol. 263 https://doi.org/10.1016/j.apenergy.2020.114638	journal	April 2020
Retail electricity pricing via online-learning of data-driven demand response of HVAC systems Yoon, Ah-Yun; Kim, Young-Jin; Zakula, Tea Applied Energy, Vol. 265 https://doi.org/10.1016/j.apenergy.2020.114771	journal	May 2020
Bayesian network based FDD strategy for variable air volume terminals Xiao, Fu; Zhao, Yang; Wen, Jin Automation in Construction, Vol. 41 https://doi.org/10.1016/j.autcon.2013.10.019	journal	May 2014
Building automation and control systems: A case study to evaluate the energy and environmental performances of a lighting control system in offices Aghemo, C.; Blaso, L.; Pellegrino, A. Automation in Construction, Vol. 43 https://doi.org/10.1016/j.autcon.2014.02.015	journal	July 2014
Conditional Random Fields - based approach for real-time building occupancy estimation with multi-sensory networks Zikos, Stylianos; Tsolakis, Apostolos; Meskos, Dimitrios Automation in Construction, Vol. 68 https://doi.org/10.1016/j.autcon.2016.05.005	journal	August 2016
Temperature sensor placement optimization for VAV control using CFD–BES co-simulation strategy Du, Zhimin; Xu, Peifan; Jin, Xinqiao Building and Environment, Vol. 85 https://doi.org/10.1016/j.buildenv.2014.11.033	journal	February 2015
Designing sensor sets for capturing energy events in buildings Lovett, Tom; Lee, JeeHang; Gabe-Thomas, Elizabeth Building and Environment, Vol. 110 https://doi.org/10.1016/j.buildenv.2016.09.004	journal	December 2016
Occupancy-based lighting control in open-plan office spaces: A state-of-the-art review de Bakker, Christel; Aries, Myriam; Kort, Helianthe Building and Environment, Vol. 112 https://doi.org/10.1016/j.buildenv.2016.11.042	journal	February 2017
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
Automated mobile sensing: Towards high-granularity agile indoor environmental quality monitoring Jin, Ming; Liu, Shichao; Schiavon, Stefano Building and Environment, Vol. 127 https://doi.org/10.1016/j.buildenv.2017.11.003	journal	January 2018
Occupant comfort and behavior: High-resolution data from a 6-month field study of personal comfort systems with 37 real office workers Kim, Joyce; Bauman, Fred; Raftery, Paul Building and Environment, Vol. 148 https://doi.org/10.1016/j.buildenv.2018.11.012	journal	January 2019
A transfer operator methodology for optimal sensor placement accounting for uncertainty Sharma, Himanshu; Vaidya, Umesh; Ganapathysubramanian, Baskar Building and Environment, Vol. 155 https://doi.org/10.1016/j.buildenv.2019.03.054	journal	May 2019
Real-time daylight glare control using a low-cost, window-mounted HDRI sensor Kim, Michael; Konstantzos, Iason; Tzempelikos, Athanasios Building and Environment, Vol. 177 https://doi.org/10.1016/j.buildenv.2020.106912	journal	June 2020
A Review on Internet of Things Solutions for Intelligent Energy Control in Buildings for Smart City Applications Khajenasiri, Iman; Estebsari, Abouzar; Verhelst, Marian Energy Procedia, Vol. 111 https://doi.org/10.1016/j.egypro.2017.03.239	journal	March 2017
Predictive controllers for thermal comfort optimization and energy savings Freire, Roberto Z.; Oliveira, Gustavo H. C.; Mendes, Nathan Energy and Buildings, Vol. 40, Issue 7, p. 1353-1365 https://doi.org/10.1016/j.enbuild.2007.12.007	journal	January 2008
Towards a sensor for detecting human presence and characterizing activity Benezeth, Y.; Laurent, H.; Emile, B. Energy and Buildings, Vol. 43, Issue 2-3 https://doi.org/10.1016/j.enbuild.2010.09.014	journal	February 2011
A robust CO2-based demand-controlled ventilation control strategy for multi-zone HVAC systems Nassif, Nabil Energy and Buildings, Vol. 45 https://doi.org/10.1016/j.enbuild.2011.10.018	journal	February 2012
Practical application of a sensor overlay system for building monitoring and commissioning Painter, Birgit; Brown, Neil; Cook, Malcolm J. Energy and Buildings, Vol. 48 https://doi.org/10.1016/j.enbuild.2012.01.003	journal	May 2012
Handling model uncertainty in model predictive control for energy efficient buildings Maasoumy, M.; Razmara, M.; Shahbakhti, M. Energy and Buildings, Vol. 77 https://doi.org/10.1016/j.enbuild.2014.03.057	journal	July 2014
Energy-efficient control of under-actuated HVAC zones in commercial buildings Brooks, Jonathan; Kumar, Saket; Goyal, Siddharth Energy and Buildings, Vol. 93 https://doi.org/10.1016/j.enbuild.2015.01.050	journal	April 2015
Occupancy measurement in commercial office buildings for demand-driven control applications—A survey and detection system evaluation Labeodan, Timilehin; Zeiler, Wim; Boxem, Gert Energy and Buildings, Vol. 93 https://doi.org/10.1016/j.enbuild.2015.02.028	journal	April 2015
Practical implementation and evaluation of model predictive control for an office building in Brussels De Coninck, Roel; Helsen, Lieve Energy and Buildings, Vol. 111 https://doi.org/10.1016/j.enbuild.2015.11.014	journal	January 2016
Indoor air quality and energy management through real-time sensing in commercial buildings Kumar, Prashant; Martani, Claudio; Morawska, Lidia Energy and Buildings, Vol. 111 https://doi.org/10.1016/j.enbuild.2015.11.037	journal	January 2016
The role of smart grids in the building sector Kolokotsa, Dionysia Energy and Buildings, Vol. 116 https://doi.org/10.1016/j.enbuild.2015.12.033	journal	March 2016
Building energy metering and environmental monitoring – A state-of-the-art review and directions for future research Ahmad, Muhammad Waseem; Mourshed, Monjur; Mundow, David Energy and Buildings, Vol. 120 https://doi.org/10.1016/j.enbuild.2016.03.059	journal	May 2016
On the application of wireless sensors and actuators network in existing buildings for occupancy detection and occupancy-driven lighting control Labeodan, Timilehin; De Bakker, Christel; Rosemann, Alexander Energy and Buildings, Vol. 127 https://doi.org/10.1016/j.enbuild.2016.05.077	journal	September 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
Occupancy behavior based model predictive control for building indoor climate—A critical review Mirakhorli, Amin; Dong, Bing Energy and Buildings, Vol. 129 https://doi.org/10.1016/j.enbuild.2016.07.036	journal	October 2016
Predictive control of indoor environment using occupant number detected by video data and CO 2 concentration Wang, Fulin; Feng, Qingqing; Chen, Zheliang Energy and Buildings, Vol. 145 https://doi.org/10.1016/j.enbuild.2017.04.014	journal	June 2017
WinLight: A WiFi-based occupancy-driven lighting control system for smart building Zou, Han; Zhou, Yuxun; Jiang, Hao Energy and Buildings, Vol. 158 https://doi.org/10.1016/j.enbuild.2017.09.001	journal	January 2018
Potential energy savings from high-resolution sensor controls for LED lighting Dikel, Erhan E.; Newsham, Guy R.; Xue, Henry Energy and Buildings, Vol. 158 https://doi.org/10.1016/j.enbuild.2017.09.048	journal	January 2018
Optimal sensor placement strategy for office buildings using clustering algorithms Yoganathan, Duwaraka; Kondepudi, Sekhar; Kalluri, Balaji Energy and Buildings, Vol. 158 https://doi.org/10.1016/j.enbuild.2017.10.074	journal	January 2018
Building occupancy estimation and detection: A review Chen, Zhenghua; Jiang, Chaoyang; Xie, Lihua Energy and Buildings, Vol. 169 https://doi.org/10.1016/j.enbuild.2018.03.084	journal	June 2018
Using thermostats for indoor climate control in offices: The effect on thermal comfort and heating/cooling energy use Wang, Haiying; Olesen, Bjarne W.; Kazanci, Ongun B. Energy and Buildings, Vol. 188-189 https://doi.org/10.1016/j.enbuild.2018.12.030	journal	April 2019
A novel occupancy detection solution using low-power IR-FPA based wireless occupancy sensor Mikkilineni, Aravind K.; Dong, Jin; Kuruganti, Teja Energy and Buildings, Vol. 192 https://doi.org/10.1016/j.enbuild.2019.03.022	journal	June 2019
Implementation of a self-tuned HVAC controller to satisfy occupant thermal preferences and optimize energy use Lee, Seungjae; Joe, Jaewan; Karava, Panagiota Energy and Buildings, Vol. 194 https://doi.org/10.1016/j.enbuild.2019.04.016	journal	July 2019
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
An optimization platform based on coupled indoor environment and HVAC simulation and its application in optimal thermostat placement Tian, Wei; Han, Xu; Zuo, Wangda Energy and Buildings, Vol. 199 https://doi.org/10.1016/j.enbuild.2019.07.002	journal	September 2019
An innovative fault impact analysis framework for enhancing building operations Li, Yanfei; O'Neill, Zheng Energy and Buildings, Vol. 199 https://doi.org/10.1016/j.enbuild.2019.07.011	journal	September 2019
The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: energy implications of AI-based thermal comfort controls Ngarambe, Jack; Yun, Geun Young; Santamouris, Mat Energy and Buildings, Vol. 211 https://doi.org/10.1016/j.enbuild.2020.109807	journal	March 2020
Towards smart buildings with self-tuned indoor thermal environments – A critical review Lee, Seungjae; Karava, Panagiota Energy and Buildings, Vol. 224 https://doi.org/10.1016/j.enbuild.2020.110172	journal	October 2020
Learning decision rules for energy efficient building control Domahidi, Alexander; Ullmann, Fabian; Morari, Manfred Journal of Process Control, Vol. 24, Issue 6 https://doi.org/10.1016/j.jprocont.2014.01.006	journal	June 2014
Cloud-based implementation of white-box model predictive control for a GEOTABS office building: A field test demonstration Drgoňa, Ján; Picard, Damien; Helsen, Lieve Journal of Process Control, Vol. 88 https://doi.org/10.1016/j.jprocont.2020.02.007	journal	April 2020
Evaluation of thermal environment by coupling CFD analysis and wireless-sensor measurements of a full-scale room with cooling system Shan, Xiaofang; Xu, Wei; Lee, Yi-Kuen Sustainable Cities and Society, Vol. 45 https://doi.org/10.1016/j.scs.2018.12.011	journal	February 2019
An Analysis of the Energy and Cost Savings Potential of Occupancy Sensors for Commercial Lighting Systems Von Neida, Bill; Maniccia, Dorene; Tweed, Allan Journal of the Illuminating Engineering Society, Vol. 30, Issue 2 https://doi.org/10.1080/00994480.2001.10748357	journal	July 2001
Estimating the Size of Incipient Faults in HVAC Equipment Zhou, Yimin; Dexter, Arthur HVAC&R Research, Vol. 15, Issue 1 https://doi.org/10.1080/10789669.2009.10390830	journal	January 2009
Fault-tolerant optimal control of a building HVAC system Bengea, Sorin C.; Li, Pengfei; Sarkar, Soumik Science and Technology for the Built Environment, Vol. 21, Issue 6 https://doi.org/10.1080/23744731.2015.1057085	journal	March 2015
HVAC control loop performance assessment: A critical review (1587-RP) O’Neill, Zheng; Li, Yanfei; Williams, Keith Science and Technology for the Built Environment, Vol. 23, Issue 4 https://doi.org/10.1080/23744731.2016.1239466	journal	October 2016
Development of control quality factor for HVAC control loop performance assessment I—Methodology (ASHRAE RP-1587) Li, Yanfei; O'Neill, Zheng D.; Zhou, Xiaohui Science and Technology for the Built Environment, Vol. 25, Issue 5 https://doi.org/10.1080/23744731.2018.1556055	journal	January 2019
Supervisory Control for Resilient Chiller Plants Under Condenser Fouling Mittal, Khushboo; Wilson, James P.; Baillie, Brian P. IEEE Access, Vol. 5 https://doi.org/10.1109/ACCESS.2017.2726017	journal	January 2017
Ramping Services from Grid-interactive Buildings Adetola, Veronica; Lin, Fu; Yuan, Shui 2019 IEEE Conference on Control Technology and Applications (CCTA) https://doi.org/10.1109/CCTA.2019.8920453	conference	August 2019
An Internet of Things Framework for Smart Energy in Buildings: Designs, Prototype, and Experiments Pan, Jianli; Jain, Raj; Paul, Subharthi IEEE Internet of Things Journal, Vol. 2, Issue 6 https://doi.org/10.1109/JIOT.2015.2413397	journal	December 2015
IoT Considerations, Requirements, and Architectures for Smart Buildings—Energy Optimization and Next-Generation Building Management Systems Minoli, Daniel; Sohraby, Kazem; Occhiogrosso, Benedict IEEE Internet of Things Journal, Vol. 4, Issue 1 https://doi.org/10.1109/JIOT.2017.2647881	journal	February 2017
A Low Cost, Highly Scalable Wireless Sensor Network Solution to Achieve Smart LED Light Control for Green Buildings Magno, Michele; Polonelli, Tommaso; Benini, Luca IEEE Sensors Journal, Vol. 15, Issue 5 https://doi.org/10.1109/JSEN.2014.2383996	journal	May 2015
Occupancy Estimation Using a Low-Pixel Count Thermal Imager Tyndall, Ash; Cardell-Oliver, Rachel; Keating, Adrian IEEE Sensors Journal, Vol. 16, Issue 10 https://doi.org/10.1109/JSEN.2016.2530824	journal	May 2016
From Buildings to Smart Buildings—Sensing and Actuation to Improve Energy Efficiency Weng, Thomas; Agarwal, Yuvraj IEEE Design & Test of Computers, Vol. 29, Issue 4 https://doi.org/10.1109/MDT.2012.2211855	journal	August 2012
A Road Map to Integration: Perspectives on Smart Grid Development Farhangi, Hassan IEEE Power and Energy Magazine, Vol. 12, Issue 3 https://doi.org/10.1109/MPE.2014.2301515	journal	May 2014
Collaborative Energy and Thermal Comfort Management Through Distributed Consensus Algorithms Gupta, Santosh K.; Kar, Koushik; Mishra, Sandipan IEEE Transactions on Automation Science and Engineering, Vol. 12, Issue 4 https://doi.org/10.1109/TASE.2015.2468730	journal	October 2015
Minimum-Cost Sensor Placement for Required Lifetime in Wireless Sensor-Target Surveillance Networks Liu, Hai; Chu, Xiaowen; Leung, Yiu-Wing IEEE Transactions on Parallel and Distributed Systems, Vol. 24, Issue 9 https://doi.org/10.1109/TPDS.2012.263	journal	September 2013
An Energy Scheduling Algorithm Supporting Power Quality Management in Commercial Building Microgrids Hong, Mingguo; Yu, Xiangyang; Yu, Nan-Peng IEEE Transactions on Smart Grid, Vol. 7, Issue 2 https://doi.org/10.1109/TSG.2014.2379582	journal	March 2016
Experimental Evaluation of Frequency Regulation From Commercial Building HVAC Systems Lin, Yashen; Barooah, Prabir; Meyn, Sean IEEE Transactions on Smart Grid, Vol. 6, Issue 2 https://doi.org/10.1109/TSG.2014.2381596	journal	March 2015
VOLTTRON™: Using distributed control and sensing to integrate buildings and the grid Haack, Jereme; Akyol, Bora; Allwardt, Craig 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT) https://doi.org/10.1109/WF-IoT.2016.7845495	conference	December 2016
Efficient Operation of Air-Side Economizer Using Extremum Seeking Control Li, Pengfei; Li, Yaoyu; Seem, John E. Journal of Dynamic Systems, Measurement, and Control, Vol. 132, Issue 3 https://doi.org/10.1115/1.4001216	journal	April 2010
Sensor placement optimization in buildings Bianco, Simone; Tisato, Francesco IS&T/SPIE Electronic Imaging, SPIE Proceedings https://doi.org/10.1117/12.911021	conference	February 2012
Sensor network data fault types Ni, Kevin; Ramanathan, Nithya; Chehade, Mohamed Nabil Hajj ACM Transactions on Sensor Networks, Vol. 5, Issue 3 https://doi.org/10.1145/1525856.1525863	journal	May 2009
The performance of occupancy-based lighting control systems: A review Guo, X.; Tiller, Dk; Henze, Gp Lighting Research & Technology, Vol. 42, Issue 4 https://doi.org/10.1177/1477153510376225	journal	August 2010
Occupancy-Based HVAC Control with Short-Term Occupancy Prediction Algorithms for Energy-Efficient Buildings Dong, Jin; Winstead, Christopher; Nutaro, James Energies, Vol. 11, Issue 9 https://doi.org/10.3390/en11092427	journal	September 2018
Abnormal Activity Detection Using Pyroelectric Infrared Sensors Luo, Xiaomu; Tan, Huoyuan; Guan, Qiuju Sensors, Vol. 16, Issue 6 https://doi.org/10.3390/s16060822	journal	June 2016

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