IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v222y2024ics0960148124000016.html
   My bibliography  Save this article

Experimental verification of the novel transcritical CO2 heat pump system and model evaluation method

Author

Listed:
  • Qin, Xiang
  • Shen, Aoqi
  • Duan, Hongxin
  • Wang, Guanghui
  • Chen, Jiaheng
  • Tang, Songzhen
  • Wang, Dingbiao

Abstract

This work proposes a novel method for verifying the accuracy of the numerical simulation model of the compression/ejector transcritical CO2 heat pump system using convolutional neural networks. The method focuses on converting the original unequal input conditions into equal input conditions and comparing the simulation results with the experimental prediction results of each component. The validation results reveal the following findings: 1) The root mean square errors of the gas cooler and the water source evaporator are 9.16 °C and 11.47 °C respectively, indicating that future work should focus on correcting of the CO2 heat transfer coefficient calculation method; 2) The verification results of the evaporator indicate that suggesting the need to incorporate an air dynamic change module in the air source input; 3) The root mean square error of the CO2 outlet pressure in the ejector is 462.45 kPa. It can be inferred from the pressure variation trend that the limit pressure ratio of the compressor is the main factor affecting the accuracy of the ejector model. Overall, this article presents a novel and effective method for verifying the accuracy of numerical models.

Suggested Citation

  • Qin, Xiang & Shen, Aoqi & Duan, Hongxin & Wang, Guanghui & Chen, Jiaheng & Tang, Songzhen & Wang, Dingbiao, 2024. "Experimental verification of the novel transcritical CO2 heat pump system and model evaluation method," Renewable Energy, Elsevier, vol. 222(C).
  • Handle: RePEc:eee:renene:v:222:y:2024:i:c:s0960148124000016
    DOI: 10.1016/j.renene.2024.119936
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124000016
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2024.119936?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.

    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:renene:v:222:y:2024:i:c:s0960148124000016. 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.

    We have no bibliographic references for this item. You can help adding them by using 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/renewable-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.