IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v254y2022ipcs0360544222012968.html
   My bibliography  Save this article

Anti-frosting operation and regulation technology of air-water dual-source heat pump evaporator

Author

Listed:
  • Zhong, Huihui
  • Zeng, Li
  • Long, Jibo
  • Xia, Kuiming
  • Lu, Haolin
  • Yongga, A.

Abstract

In this study, a dual-source heat pump evaporator was designed using hot water and air as the heat sources. The hot water coil and the refrigerant coil in the evaporator were arranged in sequence along the air flow direction. The air temperature, relative humidity and velocity at the evaporator inlet, and evaporator hot water temperature were taken as the input parameters. The heat and mass transfer model of the dual-source evaporator was established. Based on the 90% relative humidity(RH) line of the psychrometric chart, the relationship between the refrigerant evaporation temperature and the air absolute humidity ratio under the critical frosting condition of the evaporator was fitted. In the cold season, the evaporator anti-frosting performance under the dual-source condition was tested experimentally and simulated. The results showed that the experimentally determined evaporator temperature was in good agreement with the simulated values. Besides, increasing the evaporator hot water temperature or inlet air velocity enabled one to improve the evaporator fin surface temperature. In particular, when the evaporator working temperature rose above the critical frosting temperature, the anti-frosting operation of the evaporator in winter could be achieved. If the ambient temperature was below 0 °C, the anti-frosting was provided by adjusting the refrigerant evaporation temperature.

Suggested Citation

  • Zhong, Huihui & Zeng, Li & Long, Jibo & Xia, Kuiming & Lu, Haolin & Yongga, A., 2022. "Anti-frosting operation and regulation technology of air-water dual-source heat pump evaporator," Energy, Elsevier, vol. 254(PC).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pc:s0360544222012968
    DOI: 10.1016/j.energy.2022.124393
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222012968
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.124393?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. Liang, Jierong & Sun, Li & Li, Tingxun, 2018. "A novel defrosting method in gasoline vapor recovery application," Energy, Elsevier, vol. 163(C), pages 751-765.
    2. Han, Youhua & Liu, Yang & Lu, Shixiang & Basalike, Pie & Zhang, Jili, 2021. "Electrical performance and power prediction of a roll-bond photovoltaic thermal array under dewing and frosting conditions," Energy, Elsevier, vol. 237(C).
    3. Eom, Yong Hwan & Chung, Yoong & Park, Minsu & Hong, Sung Bin & Kim, Min Soo, 2021. "Deep learning-based prediction method on performance change of air source heat pump system under frosting conditions," Energy, Elsevier, vol. 228(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cao, Jingyu & Zheng, Ling & Peng, Jinqing & Wang, Wenjie & Leung, Michael K.H. & Zheng, Zhanying & Hu, Mingke & Wang, Qiliang & Cai, Jingyong & Pei, Gang & Ji, Jie, 2023. "Advances in coupled use of renewable energy sources for performance enhancement of vapour compression heat pump: A systematic review of applications to buildings," Applied Energy, Elsevier, vol. 332(C).
    2. Xiaolei Yuan & Mingya Zhu & Yumin Liang & Mehdi Shahrestani & Risto Kosonen, 2023. "Comparison of Short and Long-Term Energy Performance and Decarbonization Potentials between Cogeneration and GSHP Systems under MARKAL Scenarios," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    3. Li, Yunhai & Cui, Yu & Song, Zhiying & Zhao, Xudong & Li, Jing & Shen, Chao, 2023. "Eco-economic performance and application potential of a novel dual-source heat pump heating system," Energy, Elsevier, vol. 283(C).

    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. Liang, Xing-Yu & Zhang, Bo & Zhang, Chun-Lu, 2024. "Physics-informed deep residual neural network for finned-tube evaporator performance prediction," Energy, Elsevier, vol. 302(C).
    2. Ling, Weihao & Wu, Jingtao & Li, Xuan & Ma, Jianjun & Ding, Yu & Li, Bingcheng & Zeng, Min, 2023. "Numerical prediction of frosting growth characteristics of microchannel louvered fin heat exchanger," Energy, Elsevier, vol. 283(C).
    3. Wang, Zhi & Peng, Xianyong & Zhou, Huaichun & Cao, Shengxian & Huang, Wenbo & Yan, Weijie & Li, Kuangyu & Fan, Siyuan, 2024. "A dynamic modeling method using channel-selection convolutional neural network: A case study of NOx emission," Energy, Elsevier, vol. 290(C).
    4. Xu, Hao & Xu, Xiafan & Chen, Liubiao & Guo, Jia & Wang, Junjie, 2022. "A novel cryogenic condensation system combined with gas turbine with low carbon emission for volatile compounds recovery," Energy, Elsevier, vol. 248(C).
    5. Han, Youhua & Ma, Liangdong & Zhang, Jili & Mi, Peiyuan & Guo, Xiaochao, 2023. "Research on the adaptive proportional-integral control method of a direct-expansion photovoltaic-thermal heat pump system," Energy, Elsevier, vol. 281(C).
    6. Mario Pérez-Gomariz & Antonio López-Gómez & Fernando Cerdán-Cartagena, 2023. "Artificial Neural Networks as Artificial Intelligence Technique for Energy Saving in Refrigeration Systems—A Review," Clean Technol., MDPI, vol. 5(1), pages 1-21, January.
    7. Tomas Kropas & Giedrė Streckienė & Juozas Bielskus, 2021. "Experimental Investigation of Frost Formation Influence on an Air Source Heat Pump Evaporator," Energies, MDPI, vol. 14(18), pages 1-15, September.
    8. Fan, Yi & Zhao, Xudong & Han, Zhonghe & Li, Jing & Badiei, Ali & Akhlaghi, Yousef Golizadeh & Liu, Zhijian, 2021. "Scientific and technological progress and future perspectives of the solar assisted heat pump (SAHP) system," Energy, Elsevier, vol. 229(C).
    9. 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).
    10. Ren, Zhengxiong & Han, Hua & Cui, Xiaoyu & Lu, Hailong & Luo, Mingwen, 2023. "Novel data-pulling-based strategy for chiller fault diagnosis in data-scarce scenarios," Energy, Elsevier, vol. 279(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:254:y:2022:i:pc:s0360544222012968. 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.