journal article·2022-05-28Open access

A Review of Recent Literature on Systems and Methods for the Control of Thermal Comfort in Buildings

Benedetta Grassi, Edoardo Alessio Piana, Adriano Maria Lezzi, Mariagrazia Pilotelli

Applied Sciences· Volume 12· Issue 11

Abstract

Thermal comfort in indoor environments is perceived as an important factor for the well-being and productivity of the occupants. To practically create a comfortable environment, a combination of models, systems, and procedures must be applied. This systematic review collects recent studies proposing complete thermal-comfort-based control strategies, extracted from a scientific database for the period 2017–2021. The study consists of this paper and of a spreadsheet recording all the 166 reviewed works. After a general introduction, the content of the papers is analyzed in terms of thermal comfort models, indoor environment control strategies, and correlation between these two aspects. Practical considerations on scope, required inputs, level of readiness, and, where available, estimated cost are also given. It was found that the predicted mean vote is the preferred thermal comfort modeling approach, followed by data-driven and adaptive methods. Thermal comfort is controlled mainly through indoor temperature, although a wide range of options are explored, including the comfort-based design of building elements. The most popular field of application of advanced control strategies is office/commercial buildings with air conditioning systems, which can be explained by budget and impact considerations. The analysis showed that few works envisaging practical implementations exist that address the needs of vulnerable people. A section is, therefore, dedicated to this issue.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Building Energy and Comfort Optimization · Urban Heat Island Mitigation · Infection Control and Ventilation

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Mechanical and Industrial Engineering, University of Brescia, Via Branze 38, 25123 Brescia, Italy

References (100+)

Show source-provided references
1. Literature survey on how different factors influence human comfort in indoor environments10.1016/j.buildenv.2010.10.021 ↗
2. Fanger, P.O. (1970). Thermal Comfort: Analysis and Applications in Environmental Engineering, McGraw-Hill.
3. Developing an adaptive model of thermal comfort and preference
4. ASHRAE (2020). Standard 55: Thermal Environmental Conditions for Human Occupancy, American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE).
5. ISO/TC 159/SC 5 (2005). Ergonomics of the Thermal Environment—Analytical Determination and Interpretation of tHermal Comfort Using Calculation of the PMV and PPD Indices and Local Thermal Comfort Criteria (Standard No. ISO 7730:2005).
6. CEN/TC 156 (2019). Energy performance of buildings—Ventilation for Buildings—Part 1: Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics (Standard No. EN 16798-1:2019).
7. Thermal comfort models and their developments: A review10.1016/j.enbenv.2020.05.007 ↗
8. A systematic review of personal thermal comfort models10.1016/j.buildenv.2021.108502 ↗
9. Bean, R. (2020). Thermal Comfort Principles and Practical Applications for Residential Buildings, Indoor Climate Consultants Inc.
10. Comprehensive analysis of the relationship between thermal comfort and building control research—A data-driven literature review10.1016/j.rser.2017.09.102 ↗
11. On the link between energy performance of building and thermal comfort: An example10.1063/1.5116993 ↗
12. Thermal and acoustic performance expectations on timber buildings10.1177/1351010X17740477 ↗
13. A review of thermal comfort models and indicators for indoor environments10.1016/j.rser.2017.05.175 ↗
14. Turning up the heat on obsolete thermostats: A simulation-based comparison of intelligent control approaches for residential heating systems10.1016/j.rser.2016.11.112 ↗
15. Individual difference in thermal comfort: A literature review10.1016/j.buildenv.2018.04.040 ↗
16. Personal comfort models—A new paradigm in thermal comfort for occupant-centric environmental control10.1016/j.buildenv.2018.01.023 ↗
17. Review on occupant-centric thermal comfort sensing, predicting, and controlling10.1016/j.enbuild.2020.110392 ↗
18. Human-in-the-loop HVAC operations: A quantitative review on occupancy, comfort, and energy-efficiency dimensions10.1016/j.apenergy.2019.01.070 ↗
19. Tomat, V., Ramallo-González, A.P., and Skarmeta Gómez, A.F. (2020). A Comprehensive Survey about Thermal Comfort under the IoT Paradigm: Is Crowdsensing the New Horizon?. Sensors, 20.10.3390/s20164647 ↗
20. Intelligent building control systems for thermal comfort and energy-efficiency: A systematic review of artificial intelligence-assisted techniques10.1016/j.rser.2021.110969 ↗
21. Smart monitoring technologies for personal thermal comfort: A review10.1016/j.jclepro.2021.127685 ↗
22. A review of select human-building interfaces and their relationship to human behavior, energy use and occupant comfort10.1016/j.buildenv.2020.106920 ↗
23. Framework for communicating with consumers using an expectation interface in smart thermostats10.1016/j.enbuild.2017.03.065 ↗
24. A social constructionist approach to managing HVAC energy consumption using social norms—A randomised field experiment10.1016/j.enpol.2021.112293 ↗
25. Li, Z., Loveday, D., and Demian, P. (2021). Nudging and usage of thermal comfort-related systems. Energy Build., 252.10.1016/j.enbuild.2021.111480 ↗
26. Software survey: VOSviewer, a computer program for bibliometric mapping10.1007/s11192-009-0146-3 ↗
27. Forty years of Fanger’s model of thermal comfort: Comfort for all?10.1111/j.1600-0668.2007.00516.x ↗
28. A comfort-based approach to smart heating and air conditioning10.1145/3057730 ↗
29. Li, D., Menassa, C., and Kamat, V. (2018). Framework for improved indoor thermal comfort through personalized HVAC control. Routledge Handbook of Sustainable and Resilient Infrastructure, Routledge.10.4324/9781315142074-36 ↗
30. Thermal comfort optimisation of vernacular rural buildings: Passive solutions to retrofit a typical farmhouse in central Italy10.4081/jae.2017.668 ↗
31. Frǎtean, A., and Dobra, P. (2018, January 24–26). The impact of control strategies upon the energy flexibility of nearly zero-energy buildings: Energy consumption minimization versus indoor thermal comfort maximization. Proceedings of the 2018 IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR 2018—THETA 21st Edition, Cluj-Napoca, Romania.10.1109/AQTR.2018.8402759 ↗
32. A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings10.1016/j.apenergy.2019.04.065 ↗
33. Development and evaluation of a comfort-oriented control strategy for thermal management of mixed-mode ventilated buildings10.1016/j.enbuild.2019.109347 ↗
34. Optimization of room air temperature in stratum-ventilated rooms for both thermal comfort and energy saving10.1016/j.apenergy.2017.07.064 ↗
35. Hang, L., and Kim, D.H. (2018). Enhanced model-based predictive control system based on fuzzy logic for maintaining thermal comfort in IoT smart space. Appl. Sci., 8.10.3390/app8071031 ↗
36. Numerical modeling and optimization of thermal comfort in building: Central composite design and CFD simulation10.1016/j.enbuild.2018.01.006 ↗
37. A day-ahead scheduling framework for thermostatically controlled loads with thermal inertia and thermal comfort model10.1007/s40565-018-0431-3 ↗
38. HVAC systems testing and check: A simplified model to predict thermal comfort conditions in moderate environments10.1016/j.apenergy.2012.11.015 ↗
39. Hybrid ventilation in an institutional building: Modeling and predictive control10.1016/j.buildenv.2019.106405 ↗
40. A theoretical adaptive model of thermal comfort—Adaptive Predicted Mean Vote (aPMV)10.1016/j.buildenv.2009.02.014 ↗
41. On the interaction between personal comfort systems and centralized HVAC systems in office buildings10.1080/17512549.2018.1505654 ↗
42. Carli, R., Cavone, G., Othman, S., and Dotoli, M. (2020). IoT based architecture for model predictive control of HVAC systems in smart buildings. Sensors, 20.10.3390/s20030781 ↗
43. Identification of the optimal control strategies for the energy-efficient ventilation under the model predictive control10.1016/j.scs.2019.101908 ↗
44. Development of a novel method to detect clothing level and facial skin temperature for controlling HVAC systems10.1016/j.enbuild.2021.110859 ↗
45. Impact of ventilation rates on indoor thermal comfort and energy efficiency of ground-source heat pump system10.1016/j.scs.2017.11.014 ↗
46. Experiment study of machine-learning-based approximate model predictive control for energy-efficient building control10.1016/j.apenergy.2021.116648 ↗
47. A state-space thermal model incorporating humidity and thermal comfort for model predictive control in buildings10.1016/j.enbuild.2018.03.082 ↗
48. 2011 compendium of physical activities: A second update of codes and MET values10.1249/MSS.0b013e31821ece12 ↗
49. Measuring metabolic rate to improve comfort management in buildings10.30638/eemj.2018.227 ↗
50. IoT-Based Smart Building Environment Service for Occupants’ Thermal Comfort10.1155/2018/1757409 ↗
51. Tanaka, K., Wada, K., Kikuchi, T., Kawakami, H., Tanaka, K., and Takai, H. (2019). Study on air-conditioning control system considering individual thermal sensation. IOP Conference Series: Earth and Environmental Science, Institute of Physics Publishing.10.1088/1755-1315/294/1/012066 ↗
52. Vision-based estimation of clothing insulation for building control: A case study of residential buildings10.1016/j.buildenv.2021.108036 ↗
53. IoT-based personal thermal comfort control for livable environment10.1177/1550147719865506 ↗
54. Park, J., Kim, T., and Lee, C.S. (2019). Development of thermal comfort-based controller and potential reduction of the cooling energy consumption of a residential building in Kuwait. Energies, 12.10.3390/en12173348 ↗
55. Energy efficient thermal comfort in open-plan office buildings10.1016/j.enbuild.2017.01.043 ↗
56. Optimized scheduling for an air-conditioning system based on indoor thermal comfort using the multi-objective improved global particle swarm optimization10.1007/s12053-018-9734-5 ↗
57. Lou, R., Hallinan, K., Huang, K., and Reissman, T. (2020). Smart wifi thermostat-enabled thermal comfort control in residences. Sustainability, 12.10.3390/su12051919 ↗
58. Development of novel PMV-based HVAC control strategies using a mean radiant temperature prediction model by machine learning in Kuwaiti climate10.1016/j.buildenv.2021.108357 ↗
59. An analysis of the impact of PMV-based thermal comfort control during heating period: A case study of highly glazed room10.1016/j.jobe.2018.08.010 ↗
60. Hong, S., Lee, J., Moon, J., and Lee, K. (2018). Thermal comfort, energy and cost impacts of PMV control considering individual metabolic rate variations in residential building. Energies, 11.10.3390/en11071767 ↗
61. ClimaCon: An Autonomous Energy Efficient Climate Control Solution for Smart Buildings10.1002/asjc.1426 ↗
62. Experimental implementation of whole building MPC with zone based thermal comfort adjustments10.1016/j.buildenv.2017.09.003 ↗
63. Personalized human comfort in indoor building environments under diverse conditioning modes10.1016/j.buildenv.2017.10.004 ↗
64. A multi-occupants’ comfort-driven and energy-efficient control strategy of VAV system based on learned thermal comfort profiles10.1080/23744731.2018.1474690 ↗
65. A satisfaction-range approach for achieving thermal comfort level in a shared office10.1016/j.buildenv.2018.06.008 ↗
66. Incentive-Based Mechanism for Truthful Occupant Comfort Feedback in Human-in-the-Loop Building Thermal Management10.1109/JSYST.2017.2771528 ↗
67. A novel spatiotemporal home heating controller design: System emulation and field testing10.1016/j.buildenv.2018.02.027 ↗
68. Data-driven approach to optimal control of ACC systems and layout design in large rooms with thermal comfort consideration by using PSO10.1016/j.jclepro.2019.07.053 ↗
69. Comparative assessment of HVAC control strategies using personal thermal comfort and sensitivity models10.1016/j.buildenv.2019.04.043 ↗
70. Data-driven simulation of a thermal comfort-based temperature set-point control with ASHRAE RP88410.1016/j.buildenv.2019.03.010 ↗
71. Thermal adaptation in occupant-driven HVAC control10.1016/j.jobe.2019.100846 ↗
72. Implementation of a self-tuned HVAC controller to satisfy occupant thermal preferences and optimize energy use10.1016/j.enbuild.2019.04.016 ↗
73. DeepComfort: Energy-Efficient Thermal Comfort Control in Buildings Via Reinforcement Learning10.1109/JIOT.2020.2992117 ↗
74. Thermal comfort control via air conditioning system using fuzzy neural network feedback controller
75. An IoT Framework for Modeling and Controlling Thermal Comfort in Buildings10.3389/fbuil.2020.00087 ↗
76. User comfort driven time-table linked AHU scheduling for ancillary service maximization of an educational building10.1016/j.enbuild.2020.110317 ↗
77. Development and validation of a smart HVAC control system for multi-occupant offices by using occupants’ physiological signals from wristband10.1016/j.enbuild.2020.109872 ↗
78. Experimental study of an indoor temperature fuzzy control method for thermal comfort and energy saving using wristband device10.1016/j.buildenv.2020.107432 ↗
79. Intelligent Agents to Improve Thermal Satisfaction by Controlling Personal Comfort Systems under Different Levels of Automation
80. Review of adaptive thermal comfort models in built environmental regulatory documents10.1016/j.buildenv.2018.03.053 ↗
81. Outdoor temperatures and comfort indoors10.1080/09613217808550656 ↗
82. Dynamic Thermal Comfort Optimization for Groups
83. Arballo, B., Kuchen, E., and Chuk, D. (2017, January 2–5). An energy efficiency optimization method applying adaptive thermal comfort in a public office building in San Juan-Argentina. Proceedings of the 33rd PLEA International Conference: Design to Thrive, PLEA 2017, NCEUB 2017—Network for Comfort and Energy Use in Buildings, Edinburgh, Scotland.
84. Kuchen, E. (2008). Spot-Monitoring zum Thermischen Komfort in Bürogebäuden, Der Andere Verlag.
85. Dynamic setpoint control for museum indoor climate conditioning integrating collection and comfort requirements: Development and energy impact for Europe10.1016/j.buildenv.2017.03.028 ↗
86. CEN/TC 156 (2007). Indoor Environmental Input Parameters for Design and Assessment of Energy Performance of Buildings Addressing Indoor Air Quality, Thermal Environment, Lighting and Acoustics (Standard No. EN 15251:2007).
87. Indoor air quality and thermal comfort optimization in classrooms developing an automatic system for windows opening and closing10.1016/j.enbuild.2017.01.017 ↗
88. CIBSE (2007). Guide A Environmental Design, Chartered Institution of Building Services Engineers. [8th ed.].
89. Building automation system with adaptive comfort in mixed mode buildings10.1016/j.scs.2018.07.028 ↗
90. Field study on adaptive thermal comfort in mixed mode office buildings in southwestern area of Spain10.1016/j.buildenv.2017.06.042 ↗
91. Shading devices optimization to enhance thermal comfort and energy performance of a residential building in Morocco10.1016/j.jobe.2018.03.018 ↗
92. Gabsi, F., Hamelin, F., Sauer, N., and Yame, J. (2020). ℓε Regularized Economic Model Predictive Control for Thermal Comfort in Multizone Buildings. SMARTGREENS 2020—Proceedings of the 9th International Conference on Smart Cities and Green ICT Systems, Virtual, 2–4 May 2020, SciTePress.10.5220/0009392801370148 ↗
93. Developing an adaptive control algorithm for Europe10.1016/S0378-7788(02)00013-0 ↗
94. A comparative study on energy demand through the adaptive thermal comfort approach considering climate change in office buildings of Spain10.1007/s12273-019-0560-2 ↗
95. An optimised window control strategy for naturally ventilated residential buildings in warm climates10.1016/j.scs.2020.102118 ↗
96. Estimating natural ventilation potential for high-rise buildings considering boundary layer meteorology10.1016/j.apenergy.2017.02.041 ↗
97. Comfort-based control for mixed-mode buildings10.1016/j.enbuild.2021.111465 ↗
98. HouseTalk: A House That Comforts You10.1109/ACCESS.2021.3058364 ↗
99. Natural Ventilation Strategy in a Social Housing with Sub-humid Warm Climate Based on Thermal Comfort10.2478/rtuect-2021-0037 ↗
100. Szokolay, S. (2003). Introduction to Architectural Science: The Basis of Sustainable Design, Architectural Press. [1st ed.].