IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p11767-d663970.html
   My bibliography  Save this article

Effect of Different HVAC Control Strategies on Thermal Comfort and Adaptive Behavior in High-Rise Apartments

Author

Listed:
  • Jihye Ryu

    (School of Architectural, Civil, Environmental, and Energy Engineering, Kyungpook National University, Daegu 41566, Korea)

  • Jungsoo Kim

    (School of Architecture, Design and Planning, The University of Sydney, Sydney, NSW 2006, Australia)

Abstract

In the residential sector, householders play an active role in regulating the indoor climate via diverse control measures such as the operation of air-conditioners or windows. The main research question asked in this paper is whether control decisions made by householders are rational and effective in terms of achieving comfort and energy efficiency. Based on a field study in South Korea, this paper explores how a HVAC control strategy for high-rise apartment buildings can affect occupant comfort and adaptive behavior. Two different control strategies: (1) occupant control (OC), where occupants were allowed to freely operate the HVAC system and (2) comfort-zone control (CC), where the operation of the HVAC system was determined by the researcher, based on a pre-defined comfort zone, were applied to, and tested within the participating households in summer. The impact of the two control strategies on indoor thermal environments, thermal comfort, and occupant adaptive behavior were analyzed. We find that the CC strategy is more energy/comfort efficient than OC because: (1) comfort was be achieved at a higher indoor temperature, and (2) unnecessary control behaviors leading to cooling load increase can be minimized, which have major implications for energy consumption reduction in the residential sector.

Suggested Citation

  • Jihye Ryu & Jungsoo Kim, 2021. "Effect of Different HVAC Control Strategies on Thermal Comfort and Adaptive Behavior in High-Rise Apartments," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:11767-:d:663970
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/11767/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/21/11767/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Roetzel, Astrid & Tsangrassoulis, Aris & Dietrich, Udo & Busching, Sabine, 2010. "A review of occupant control on natural ventilation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1001-1013, April.
    2. Jung, Wooyoung & Jazizadeh, Farrokh, 2019. "Human-in-the-loop HVAC operations: A quantitative review on occupancy, comfort, and energy-efficiency dimensions," Applied Energy, Elsevier, vol. 239(C), pages 1471-1508.
    3. Jazizadeh, Farrokh & Jung, Wooyoung, 2018. "Personalized thermal comfort inference using RGB video images for distributed HVAC control," Applied Energy, Elsevier, vol. 220(C), pages 829-841.
    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. Darowicki, K. & Janicka, E. & Mielniczek, M. & Zielinski, A. & Gawel, L. & Mitzel, J. & Hunger, J., 2019. "The influence of dynamic load changes on temporary impedance in hydrogen fuel cells, selection and validation of the electrical equivalent circuit," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Kristian Fabbri & Jacopo Gaspari & Laura Vandi, 2019. "Indoor Thermal Comfort of Pregnant Women in Hospital: A Case Study Evidence," Sustainability, MDPI, vol. 11(23), pages 1-24, November.
    3. Jung, Wooyoung & Jazizadeh, Farrokh, 2020. "Energy saving potentials of integrating personal thermal comfort models for control of building systems: Comprehensive quantification through combinatorial consideration of influential parameters," Applied Energy, Elsevier, vol. 268(C).
    4. Wenxiao Chu & Maria Vicidomini & Francesco Calise & Neven Duić & Poul Alborg Østergaard & Qiuwang Wang & Maria da Graça Carvalho, 2022. "Recent Advances in Low-Carbon and Sustainable, Efficient Technology: Strategies and Applications," Energies, MDPI, vol. 15(8), pages 1-30, April.
    5. Tarragona, Joan & Pisello, Anna Laura & Fernández, Cèsar & Cabeza, Luisa F. & Payá, Jorge & Marchante-Avellaneda, Javier & de Gracia, Alvaro, 2022. "Analysis of thermal energy storage tanks and PV panels combinations in different buildings controlled through model predictive control," Energy, Elsevier, vol. 239(PC).
    6. Antonio Paone & Jean-Philippe Bacher, 2018. "The Impact of Building Occupant Behavior on Energy Efficiency and Methods to Influence It: A Review of the State of the Art," Energies, MDPI, vol. 11(4), pages 1-19, April.
    7. Nilofar Asim & Marzieh Badiei & Masita Mohammad & Halim Razali & Armin Rajabi & Lim Chin Haw & Mariyam Jameelah Ghazali, 2022. "Sustainability of Heating, Ventilation and Air-Conditioning (HVAC) Systems in Buildings—An Overview," IJERPH, MDPI, vol. 19(2), pages 1-16, January.
    8. Hua Chen & Shuang Dai & Fanlin Meng, 2023. "Smart Building Thermal Management: A Data-Driven Approach Based on Dynamic and Consensus Clustering," Sustainability, MDPI, vol. 15(21), pages 1-25, October.
    9. Sheng-Yuan Wang & Kyung-Tae Lee & Ju-Hyung Kim, 2022. "Green Retrofitting Simulation for Sustainable Commercial Buildings in China Using a Proposed Multi-Agent Evolutionary Game," Sustainability, MDPI, vol. 14(13), pages 1-32, June.
    10. Filipe Soares & André Madureira & Andreu Pagès & António Barbosa & António Coelho & Fernando Cassola & Fernando Ribeiro & João Viana & José Andrade & Marina Dorokhova & Nélson Morais & Nicolas Wyrsch , 2021. "FEEdBACk: An ICT-Based Platform to Increase Energy Efficiency through Buildings’ Consumer Engagement," Energies, MDPI, vol. 14(6), pages 1-43, March.
    11. Cheng, Fanyong & Cui, Can & Cai, Wenjian & Zhang, Xin & Ge, Yuan & Li, Bingxu, 2022. "A novel data-driven air balancing method with energy-saving constraint strategy to minimize the energy consumption of ventilation system," Energy, Elsevier, vol. 239(PB).
    12. Quddus Tushar & Guomin Zhang & Satheeskumar Navaratnam & Muhammed A. Bhuiyan & Lei Hou & Filippo Giustozzi, 2023. "A Review of Evaluative Measures of Carbon-Neutral Buildings: The Bibliometric and Science Mapping Analysis towards Sustainability," Sustainability, MDPI, vol. 15(20), pages 1-31, October.
    13. Idahosa, Love Odion & Akotey, Joseph Oscar, 2021. "A social constructionist approach to managing HVAC energy consumption using social norms – A randomised field experiment," Energy Policy, Elsevier, vol. 154(C).
    14. Hiroshi Mori & Tetsu Kubota & I Gusti Ngurah Antaryama & Sri Nastiti N. Ekasiwi, 2020. "Analysis of Window-Opening Patterns and Air Conditioning Usage of Urban Residences in Tropical Southeast Asia," Sustainability, MDPI, vol. 12(24), pages 1-21, December.
    15. Rempel, Alexandra R. & Danis, Jackson & Rempel, Alan W. & Fowler, Michael & Mishra, Sandipan, 2022. "Improving the passive survivability of residential buildings during extreme heat events in the Pacific Northwest," Applied Energy, Elsevier, vol. 321(C).
    16. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    17. Sarah O’Connell & Marcus Martin Keane, 2021. "Development of a Framework for Activation of Aggregator Led Flexibility," Energies, MDPI, vol. 14(16), pages 1-15, August.
    18. Chenari, Behrang & Dias Carrilho, João & Gameiro da Silva, Manuel, 2016. "Towards sustainable, energy-efficient and healthy ventilation strategies in buildings: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1426-1447.
    19. Chaudhuri, Tanaya & Soh, Yeng Chai & Li, Hua & Xie, Lihua, 2019. "A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings," Applied Energy, Elsevier, vol. 248(C), pages 44-53.
    20. Diaz-Londono, Cesar & Enescu, Diana & Ruiz, Fredy & Mazza, Andrea, 2020. "Experimental modeling and aggregation strategy for thermoelectric refrigeration units as flexible loads," Applied Energy, Elsevier, vol. 272(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:jsusta:v:13:y:2021:i:21:p:11767-:d:663970. 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.