IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v274y2023ics0360544223007995.html
   My bibliography  Save this article

On-site fault experiment and diagnosis research of the carbon dioxide transcritical heat pump system for energy saving

Author

Listed:
  • Guo, Yabin
  • Li, Yuduo
  • Li, Weilin

Abstract

Carbon dioxide transcritical heat pump air conditioning has an excellent performance in heating conditions, and is a very potential heating alternative, which will help to improve the energy saving level of buildings. The occurrence of the fault will lead to an increase of energy consumption, damage of system components and other consequences. However, the current research focuses on the heat pump system with Freon as refrigerant, and the experimental research on the fault of the carbon dioxide transcritical heat pump system has not been studied. Therefore, this research carried out the operation experiment of the carbon dioxide heat pump with eight fault types under the actual conditions in winter. The operation characteristics under different fault conditions are analyzed. Based on the fault characteristics, a causality table is proposed, which can quickly identify the fault type when there are at least 6 characteristic variables. Besides, it is concluded that after the fault occurs, the energy consumption will increase directly or indirectly. Most of the faults will directly cause the decrease of system heating capacity and reduce indoor thermal comfort. The research results will contribute to the early identification of carbon dioxide system faults and the improvement of building energy efficiency.

Suggested Citation

  • Guo, Yabin & Li, Yuduo & Li, Weilin, 2023. "On-site fault experiment and diagnosis research of the carbon dioxide transcritical heat pump system for energy saving," Energy, Elsevier, vol. 274(C).
    • Handle: RePEc:eee:energy:v:274:y:2023:i:c:s0360544223007995
    DOI: 10.1016/j.energy.2023.127405
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223007995
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127405?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eom, Yong Hwan & Yoo, Jin Woo & Hong, Sung Bin & Kim, Min Soo, 2019. "Refrigerant charge fault detection method of air source heat pump system using convolutional neural network for energy saving," Energy, Elsevier, vol. 187(C).
    2. Guo, Yabin & Tan, Zehan & Chen, Huanxin & Li, Guannan & Wang, Jiangyu & Huang, Ronggeng & Liu, Jiangyan & Ahmad, Tanveer, 2018. "Deep learning-based fault diagnosis of variable refrigerant flow air-conditioning system for building energy saving," Applied Energy, Elsevier, vol. 225(C), pages 732-745.
    3. Austin, Brian T. & Sumathy, K., 2011. "Transcritical carbon dioxide heat pump systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 4013-4029.
    4. Zhong, Fangliang & Calautit, John Kaiser & Wu, Yupeng, 2022. "Assessment of HVAC system operational fault impacts and multiple faults interactions under climate change," Energy, Elsevier, vol. 258(C).
    5. Winkler, Jon & Das, Saptarshi & Earle, Lieko & Burkett, Lena & Robertson, Joseph & Roberts, David & Booten, Charles, 2020. "Impact of installation faults in air conditioners and heat pumps in single-family homes on U.S. energy usage," Applied Energy, Elsevier, vol. 278(C).
    6. Jiang, Jiatong & Hu, Bin & Wang, R.Z. & Deng, Na & Cao, Feng & Wang, Chi-Chuan, 2022. "A review and perspective on industry high-temperature heat pumps," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    7. Aguilera, José Joaquín & Meesenburg, Wiebke & Ommen, Torben & Markussen, Wiebke Brix & Poulsen, Jonas Lundsted & Zühlsdorf, Benjamin & Elmegaard, Brian, 2022. "A review of common faults in large-scale heat pumps," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    8. Chen, Jianli & Zhang, Liang & Li, Yanfei & Shi, Yifu & Gao, Xinghua & Hu, Yuqing, 2022. "A review of computing-based automated fault detection and diagnosis of heating, ventilation and air conditioning systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    9. Livio de Santoli & Gianluigi Lo Basso & Davide Astiaso Garcia & Giuseppe Piras & Giulia Spiridigliozzi, 2019. "Dynamic Simulation Model of Trans-Critical Carbon Dioxide Heat Pump Application for Boosting Low Temperature Distribution Networks in Dwellings," Energies, MDPI, vol. 12(3), pages 1-20, February.
    10. Adamson, Keri-Marie & Walmsley, Timothy Gordon & Carson, James K. & Chen, Qun & Schlosser, Florian & Kong, Lana & Cleland, Donald John, 2022. "High-temperature and transcritical heat pump cycles and advancements: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    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. Chen, Zhelun & O’Neill, Zheng & Wen, Jin & Pradhan, Ojas & Yang, Tao & Lu, Xing & Lin, Guanjing & Miyata, Shohei & Lee, Seungjae & Shen, Chou & Chiosa, Roberto & Piscitelli, Marco Savino & Capozzoli, , 2023. "A review of data-driven fault detection and diagnostics for building HVAC systems," Applied Energy, Elsevier, vol. 339(C).
    2. Gómez-Hernández, J. & Grimes, R. & Briongos, J.V. & Marugán-Cruz, C. & Santana, D., 2023. "Carbon dioxide and acetone mixtures as refrigerants for industry heat pumps to supply temperature in the range 150–220 oC," Energy, Elsevier, vol. 269(C).
    3. Zhong, Fangliang & Calautit, John Kaiser & Wu, Yupeng, 2023. "Fault data seasonal imbalance and insufficiency impacts on data-driven heating, ventilation and air-conditioning fault detection and diagnosis performances for energy-efficient building operations," Energy, Elsevier, vol. 282(C).
    4. Simon P. Melgaard & Kamilla H. Andersen & Anna Marszal-Pomianowska & Rasmus L. Jensen & Per K. Heiselberg, 2022. "Fault Detection and Diagnosis Encyclopedia for Building Systems: A Systematic Review," Energies, MDPI, vol. 15(12), pages 1-50, June.
    5. Adamson, Keri-Marie & Walmsley, Timothy Gordon & Carson, James K. & Chen, Qun & Schlosser, Florian & Kong, Lana & Cleland, Donald John, 2022. "High-temperature and transcritical heat pump cycles and advancements: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. Weigert, Andreas & Hopf, Konstantin & Günther, Sebastian A. & Staake, Thorsten, 2022. "Heat pump inspections result in large energy savings when a pre-selection of households is performed: A promising use case of smart meter data," Energy Policy, Elsevier, vol. 169(C).
    7. Li, Guannan & Chen, Liang & Liu, Jiangyan & Fang, Xi, 2023. "Comparative study on deep transfer learning strategies for cross-system and cross-operation-condition building energy systems fault diagnosis," Energy, Elsevier, vol. 263(PD).
    8. Lo Basso, Gianluigi & de Santoli, Livio & Paiolo, Romano & Losi, Claudio, 2021. "The potential role of trans-critical CO2 heat pumps within a solar cooling system for building services: The hybridised system energy analysis by a dynamic simulation model," Renewable Energy, Elsevier, vol. 164(C), pages 472-490.
    9. Zhong, Fangliang & Calautit, John Kaiser & Wu, Yupeng, 2022. "Assessment of HVAC system operational fault impacts and multiple faults interactions under climate change," Energy, Elsevier, vol. 258(C).
    10. Rongjiang Ma & Shen Yang & Xianlin Wang & Xi-Cheng Wang & Ming Shan & Nanyang Yu & Xudong Yang, 2020. "Systematic Method for the Energy-Saving Potential Calculation of Air-Conditioning Systems via Data Mining. Part I: Methodology," Energies, MDPI, vol. 14(1), pages 1-15, December.
    11. Shariq, M. Hasan & Hughes, Ben Richard, 2020. "Revolutionising building inspection techniques to meet large-scale energy demands: A review of the state-of-the-art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    12. Ahmad, Tanveer & Chen, Huanxin, 2019. "Deep learning for multi-scale smart energy forecasting," Energy, Elsevier, vol. 175(C), pages 98-112.
    13. Zhang, Zhenying & Wang, Jiayu & Feng, Xu & Chang, Li & Chen, Yanhua & Wang, Xingguo, 2018. "The solutions to electric vehicle air conditioning systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 443-463.
    14. Mohanraj, M. & Belyayev, Ye. & Jayaraj, S. & Kaltayev, A., 2018. "Research and developments on solar assisted compression heat pump systems – A comprehensive review (Part A: Modeling and modifications)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 90-123.
    15. Sarkar, Jahar, 2015. "Review and future trends of supercritical CO2 Rankine cycle for low-grade heat conversion," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 434-451.
    16. Schlosser, F. & Jesper, M. & Vogelsang, J. & Walmsley, T.G. & Arpagaus, C. & Hesselbach, J., 2020. "Large-scale heat pumps: Applications, performance, economic feasibility and industrial integration," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
    17. Fei Mei & Yong Ren & Qingliang Wu & Chenyu Zhang & Yi Pan & Haoyuan Sha & Jianyong Zheng, 2018. "Online Recognition Method for Voltage Sags Based on a Deep Belief Network," Energies, MDPI, vol. 12(1), pages 1-16, December.
    18. Abdellatif Elmouatamid & Brian Fricke & Jian Sun & Philip W. T. Pong, 2023. "Air Conditioning Systems Fault Detection and Diagnosis-Based Sensing and Data-Driven Approaches," Energies, MDPI, vol. 16(12), pages 1-20, June.
    19. Ifaei, Pouya & Tayerani Charmchi, Amir Saman & Loy-Benitez, Jorge & Yang, Rebecca Jing & Yoo, ChangKyoo, 2022. "A data-driven analytical roadmap to a sustainable 2030 in South Korea based on optimal renewable microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    20. Bode, Gerrit & Thul, Simon & Baranski, Marc & Müller, Dirk, 2020. "Real-world application of machine-learning-based fault detection trained with experimental data," Energy, Elsevier, vol. 198(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:eee:energy:v:274:y:2023:i:c:s0360544223007995. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.