IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i4p1634-d1059971.html
   My bibliography  Save this article

A Review of Different Methodologies to Study Occupant Comfort and Energy Consumption

Author

Listed:
  • Antonella Yaacoub

    (Computer Science and Digital Society Laboratory (LIST3N), Université de Technologie de Troyes, 10300 Troyes, France)

  • Moez Esseghir

    (Computer Science and Digital Society Laboratory (LIST3N), Université de Technologie de Troyes, 10300 Troyes, France)

  • Leila Merghem-Boulahia

    (Computer Science and Digital Society Laboratory (LIST3N), Université de Technologie de Troyes, 10300 Troyes, France)

Abstract

The goal of this work is to give a full review of how machine learning (ML) is used in thermal comfort studies, highlight the most recent techniques and findings, and lay out a plan for future research. Most of the researchers focus on developing models related to thermal comfort prediction. However, only a few works look at the current state of adaptive thermal comfort studies and the ways in which it could save energy. This study showed that using ML control schemas to make buildings more comfortable in terms of temperature could cut energy by more than 27%. Finally, this paper identifies the remaining difficulties in using ML in thermal comfort investigations, including data collection, thermal comfort indices, sample size, feature selection, model selection, and real-world application.

Suggested Citation

  • Antonella Yaacoub & Moez Esseghir & Leila Merghem-Boulahia, 2023. "A Review of Different Methodologies to Study Occupant Comfort and Energy Consumption," Energies, MDPI, vol. 16(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1634-:d:1059971
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/4/1634/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/4/1634/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Naja Aqilah & Hom Bahadur Rijal & Sheikh Ahmad Zaki, 2022. "A Review of Thermal Comfort in Residential Buildings: Comfort Threads and Energy Saving Potential," Energies, MDPI, vol. 15(23), pages 1-23, November.
    2. Christina Turley & Margarite Jacoby & Gregory Pavlak & Gregor Henze, 2020. "Development and Evaluation of Occupancy-Aware HVAC Control for Residential Building Energy Efficiency and Occupant Comfort," Energies, MDPI, vol. 13(20), pages 1-30, October.
    3. Kong, Meng & Dong, Bing & Zhang, Rongpeng & O'Neill, Zheng, 2022. "HVAC energy savings, thermal comfort and air quality for occupant-centric control through a side-by-side experimental study," Applied Energy, Elsevier, vol. 306(PA).
    4. Michael M. Santos & Ana Vaz Ferreira & João C. G. Lanzinha, 2022. "Passive Solar Systems for the Promotion of Thermal Comfort in African Countries: A Review," Energies, MDPI, vol. 15(23), pages 1-37, December.
    5. Giulia Lamberti & Giacomo Salvadori & Francesco Leccese & Fabio Fantozzi & Philomena M. Bluyssen, 2021. "Advancement on Thermal Comfort in Educational Buildings: Current Issues and Way Forward," Sustainability, MDPI, vol. 13(18), pages 1-29, September.
    6. Mehzabeen Mannan & Sami G. Al-Ghamdi, 2021. "Indoor Air Quality in Buildings: A Comprehensive Review on the Factors Influencing Air Pollution in Residential and Commercial Structure," IJERPH, MDPI, vol. 18(6), pages 1-25, March.
    7. Djongyang, Noël & Tchinda, René & Njomo, Donatien, 2010. "Thermal comfort: A review paper," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 2626-2640, December.
    8. Fang, Xi & Gong, Guangcai & Li, Guannan & Chun, Liang & Li, Wenqiang & Peng, Pei, 2021. "A hybrid deep transfer learning strategy for short term cross-building energy prediction," Energy, Elsevier, vol. 215(PB).
    9. Noor Muhammad Abd Rahman & Lim Chin Haw & Ahmad Fazlizan, 2021. "A Literature Review of Naturally Ventilated Public Hospital Wards in Tropical Climate Countries for Thermal Comfort and Energy Saving Improvements," Energies, MDPI, vol. 14(2), pages 1-22, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Panagiotis Michailidis & Iakovos Michailidis & Dimitrios Vamvakas & Elias Kosmatopoulos, 2023. "Model-Free HVAC Control in Buildings: A Review," Energies, MDPI, vol. 16(20), pages 1-45, October.
    2. Shengqiang Wei & Yiping Lu & Wei Yang & Yubin Ke & Haibiao Zheng & Lingbo Zhu & Jianfei Tong & Longwei Mei & Shinian Fu & Congju Yao, 2022. "Comparative Research on Ventilation Characteristics of Scattering and Sample Room from Chinese Spallation Neutron Source," Energies, MDPI, vol. 15(11), pages 1-16, May.
    3. Laura J. Elstub & Shimra J. Fine & Karl E. Zelik, 2021. "Exoskeletons and Exosuits Could Benefit from Mode-Switching Body Interfaces That Loosen/Tighten to Improve Thermal Comfort," IJERPH, MDPI, vol. 18(24), pages 1-12, December.
    4. Ribeiro, Thatiana Jessica da Silva & Mady, Carlos Eduardo Keutenedjian, 2022. "Comparison among exergy analysis methods applied to a human body thermal model," Energy, Elsevier, vol. 239(PE).
    5. Bruno Malet-Damour & Jean-Pierre Habas & Dimitri Bigot, 2023. "Is Loose-Fill Plastic Waste an Opportunity for Thermal Insulation in Cold and Humid Tropical Climates?," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
    6. Djamila, Harimi, 2017. "Indoor thermal comfort predictions: Selected issues and trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 569-580.
    7. Francesco Asdrubali & Cinzia Buratti & Franco Cotana & Giorgio Baldinelli & Michele Goretti & Elisa Moretti & Catia Baldassarri & Elisa Belloni & Francesco Bianchi & Antonella Rotili & Marco Vergoni &, 2013. "Evaluation of Green Buildings’ Overall Performance through in Situ Monitoring and Simulations," Energies, MDPI, vol. 6(12), pages 1-23, December.
    8. Amir Faraji & Maria Rashidi & Fatemeh Rezaei & Payam Rahnamayiezekavat, 2023. "A Meta-Synthesis Review of Occupant Comfort Assessment in Buildings (2002–2022)," Sustainability, MDPI, vol. 15(5), pages 1-36, February.
    9. Wenbo Zhao & Ling Fan, 2024. "Short-Term Load Forecasting Method for Industrial Buildings Based on Signal Decomposition and Composite Prediction Model," Sustainability, MDPI, vol. 16(6), pages 1-21, March.
    10. Feng, Yanxiao & Liu, Shichao & Wang, Julian & Yang, Jing & Jao, Ying-Ling & Wang, Nan, 2022. "Data-driven personal thermal comfort prediction: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    11. Michael Short & Sergio Rodriguez & Richard Charlesworth & Tracey Crosbie & Nashwan Dawood, 2019. "Optimal Dispatch of Aggregated HVAC Units for Demand Response: An Industry 4.0 Approach," Energies, MDPI, vol. 12(22), pages 1-20, November.
    12. Susanne Jochner-Oette & Johanna Jetschni & Petra Liedl & Annette Menzel, 2022. "Indoor Pollen Concentrations of Mountain Cedar ( Juniperus ashei ) during Rainy Episodes in Austin, Texas," IJERPH, MDPI, vol. 19(3), pages 1-11, January.
    13. Melania Maria Serafini & Ambra Maddalon & Martina Iulini & Valentina Galbiati, 2022. "Air Pollution: Possible Interaction between the Immune and Nervous System?," IJERPH, MDPI, vol. 19(23), pages 1-24, November.
    14. Van Craenendonck, Stijn & Lauriks, Leen & Vuye, Cedric & Kampen, Jarl, 2018. "A review of human thermal comfort experiments in controlled and semi-controlled environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3365-3378.
    15. Mark B. Luther & Igor Martek & Mehdi Amirkhani & Gerhard Zucker, 2022. "Special Issue “Environmental Technology Applications in the Retrofitting of Residential Buildings”," Energies, MDPI, vol. 15(16), pages 1-4, August.
    16. Enescu, Diana, 2017. "A review of thermal comfort models and indicators for indoor environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 1353-1379.
    17. Li, Guannan & Wu, Yubei & Yoon, Sungmin & Fang, Xi, 2024. "Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning," Energy, Elsevier, vol. 299(C).
    18. Escandón, Rocío & Suárez, Rafael & Sendra, Juan José, 2019. "Field assessment of thermal comfort conditions and energy performance of social housing: The case of hot summers in the Mediterranean climate," Energy Policy, Elsevier, vol. 128(C), pages 377-392.
    19. Azar, Elie & Nikolopoulou, Christina & Papadopoulos, Sokratis, 2016. "Integrating and optimizing metrics of sustainable building performance using human-focused agent-based modeling," Applied Energy, Elsevier, vol. 183(C), pages 926-937.
    20. Tian, Chenlu & Liu, Yechun & Zhang, Guiqing & Yang, Yalong & Yan, Yi & Li, Chengdong, 2024. "Transfer learning based hybrid model for power demand prediction of large-scale electric vehicles," Energy, Elsevier, vol. 300(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1634-:d:1059971. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.