IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v258y2020ics0306261919317696.html
   My bibliography  Save this article

Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system

Author

Listed:
  • Bai, Hongyu
  • Zhu, Jie
  • Chen, Xiangjie
  • Chu, Junze
  • Cui, Yuanlong
  • Yan, Yuying

Abstract

A complete membrane-based liquid desiccant dehumidification system is investigated under the steady operating condition, which mainly consists of a dehumidifier, a regenerator, three heat exchangers, a cold and a hot water supply units. A finite difference mathematical model is developed for the complete system to investigate the system dehumidification performance and energy requirement, and validated by experimental data. The dehumidification performance is evaluated by the system sensible and latent effectiveness and moisture flux rate, while its energy performance is assessed by the total cooling capacity and coefficient of performance. It is found that the number of heat transfer units in the dehumidifier side and solution to air mass flow rate ratio have the most considerable impact on the system performance, while the number of heat transfer units in the regenerator side and solution inlet concentration in the dehumidifier have comparatively weak influences. The system sensible and latent effectiveness can be improved by increasing the dehumidifier side number of heat transfer units before reaching its critical value of 6. However, the amount of moisture being absorbed, total cooling capacity and coefficient of performance decrease with the dehumidifier side number of heat transfer units at the low air flow rate. The critical value of solution to air mass flow rate ratio varies with number of heat transfer units, and it is preferable to keep the flow rate ratio at or below its critical value as further increasing solution flow rate would reduce the system coefficient of performance.

Suggested Citation

  • Bai, Hongyu & Zhu, Jie & Chen, Xiangjie & Chu, Junze & Cui, Yuanlong & Yan, Yuying, 2020. "Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system," Applied Energy, Elsevier, vol. 258(C).
  • Handle: RePEc:eee:appene:v:258:y:2020:i:c:s0306261919317696
    DOI: 10.1016/j.apenergy.2019.114082
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919317696
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.114082?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. Lim, Dae Kyu & Ahn, Byoung Ha & Jeong, Ji Hwan, 2018. "Method to control an air conditioner by directly measuring the relative humidity of indoor air to improve the comfort and energy efficiency," Applied Energy, Elsevier, vol. 215(C), pages 290-299.
    2. Zhong, Hai & Wang, Jiajun & Jia, Hongjie & Mu, Yunfei & Lv, Shilei, 2019. "Vector field-based support vector regression for building energy consumption prediction," Applied Energy, Elsevier, vol. 242(C), pages 403-414.
    3. Liu, X.H. & Jiang, Y. & Yi, X.Q., 2009. "Effect of regeneration mode on the performance of liquid desiccant packed bed regenerator," Renewable Energy, Elsevier, vol. 34(1), pages 209-216.
    4. Rafique, M. Mujahid & Gandhidasan, P. & Bahaidarah, Haitham M.S., 2016. "Liquid desiccant materials and dehumidifiers – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 179-195.
    5. Ghadiri Moghaddam, Davood & Besant, Robert W. & Simonson, Carey J., 2014. "Solution-side effectiveness for a liquid-to-air membrane energy exchanger used as a dehumidifier/regenerator," Applied Energy, Elsevier, vol. 113(C), pages 872-882.
    6. Huang, Yanjun & Khajepour, Amir & Bagheri, Farshid & Bahrami, Majid, 2016. "Optimal energy-efficient predictive controllers in automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 184(C), pages 605-618.
    7. Islam, M.R. & Alan, S.W.L. & Chua, K.J., 2018. "Studying the heat and mass transfer process of liquid desiccant for dehumidification and cooling," Applied Energy, Elsevier, vol. 221(C), pages 334-347.
    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. Dai, Yuze & Liu, Feng & Sui, Jun & Wang, Dandan & Han, Wei & Jin, Hongguang, 2020. "Hybrid liquid desiccant air-conditioning system combined with marine aerosol removal driven by low-temperature heat source," Applied Energy, Elsevier, vol. 275(C).
    2. Dong, Honglin & Wang, Dandan & Niu, Xiaofeng & Zhang, Yue & He, Xu & Ke, Qing & Lu, Zhiheng, 2022. "Experimental study on the liquid desiccant dehumidification performance of microencapsulated phase change materials slurry," Energy, Elsevier, vol. 239(PC).
    3. Shukla, D.L. & Modi, K.V., 2022. "Influence of distinct input parameters on performance indices of dehumidifier, regenerator and on liquid desiccant-operated evaporative cooling system – A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(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. Wen, Tao & Lu, Lin, 2019. "A review of correlations and enhancement approaches for heat and mass transfer in liquid desiccant dehumidification system," Applied Energy, Elsevier, vol. 239(C), pages 757-784.
    2. Su, Wei & Lu, Zhifei & She, Xiaohui & Zhou, Junming & Wang, Feng & Sun, Bo & Zhang, Xiaosong, 2022. "Liquid desiccant regeneration for advanced air conditioning: A comprehensive review on desiccant materials, regenerators, systems and improvement technologies," Applied Energy, Elsevier, vol. 308(C).
    3. Zhang, Ning & Yin, Shao-You & Zhang, Li-Zhi, 2016. "Performance study of a heat pump driven and hollow fiber membrane-based two-stage liquid desiccant air dehumidification system," Applied Energy, Elsevier, vol. 179(C), pages 727-737.
    4. Gurubalan, A. & Maiya, M.P. & Geoghegan, Patrick J., 2019. "A comprehensive review of liquid desiccant air conditioning system," Applied Energy, Elsevier, vol. 254(C).
    5. Tao Wen & Lin Lu & Hongxing Yang & Yimo Luo, 2018. "Investigation on the Regeneration and Corrosion Characteristics of an Anodized Aluminum Plate Regenerator," Energies, MDPI, vol. 11(5), pages 1-15, May.
    6. Chen, Q. & Kum Ja, M. & Li, Y. & Chua, K.J., 2018. "Thermodynamic optimization of a vacuum multi-effect membrane distillation system for liquid desiccant regeneration," Applied Energy, Elsevier, vol. 230(C), pages 960-973.
    7. Giampieri, Alessandro & Ma, Zhiwei & Ling Chin, Janie & Smallbone, Andrew & Lyons, Padraig & Khan, Imad & Hemphill, Stephen & Roskilly, Anthony Paul, 2019. "Techno-economic analysis of the thermal energy saving options for high-voltage direct current interconnectors," Applied Energy, Elsevier, vol. 247(C), pages 60-77.
    8. Liu, Xiaoli & Qu, Ming & Liu, Xiaobing & Wang, Lingshi, 2019. "Membrane-based liquid desiccant air dehumidification: A comprehensive review on materials, components, systems and performances," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 444-466.
    9. Fekadu, Geleta & Subudhi, Sudhakar, 2018. "Renewable energy for liquid desiccants air conditioning system: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 364-379.
    10. Zeng, Sheng & Su, Bin & Zhang, Minglong & Gao, Yuan & Liu, Jun & Luo, Song & Tao, Qingmei, 2021. "Analysis and forecast of China's energy consumption structure," Energy Policy, Elsevier, vol. 159(C).
    11. Wang, Ran & Lu, Shilei & Feng, Wei, 2020. "A novel improved model for building energy consumption prediction based on model integration," Applied Energy, Elsevier, vol. 262(C).
    12. Imed Khabbouchi & Dhaou Said & Aziz Oukaira & Idir Mellal & Lyes Khoukhi, 2023. "Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP)," Energies, MDPI, vol. 16(5), pages 1-15, February.
    13. Zhaocheng Li & Yu Song, 2022. "Energy Consumption Linkages of the Chinese Construction Sector," Energies, MDPI, vol. 15(5), pages 1-13, February.
    14. Huang, Yanjun & Khajepour, Amir & Ding, Haitao & Bagheri, Farshid & Bahrami, Majid, 2017. "An energy-saving set-point optimizer with a sliding mode controller for automotive air-conditioning/refrigeration systems," Applied Energy, Elsevier, vol. 188(C), pages 576-585.
    15. Shen, Suping & Cai, Wenjian & Wang, Xinli & Wu, Qiong & Yon, Haoren, 2017. "Investigation of liquid desiccant regenerator with fixed-plate heat recovery system," Energy, Elsevier, vol. 137(C), pages 172-182.
    16. Guan, Bowen & Zhang, Tao & Jun, Liu & Liu, Xiaohua, 2020. "Exergy analysis and performance improvement of liquid-desiccant deep-dehumidification system: An engineering case study," Energy, Elsevier, vol. 196(C).
    17. Angel Andrade & Juan Zapata-Mina & Alvaro Restrepo, 2023. "Assessment of the Correlation between Energy Rating Labeling Regulations and Performance Metrics for Residential Air Conditioning Units: Case Study Variable Type Air Conditioners," International Journal of Energy Economics and Policy, Econjournals, vol. 13(5), pages 432-441, September.
    18. Wu, Qiong & Cai, WenJian & Shen, Suping & Wang, Xinli & Ren, Haoren, 2017. "A regulation strategy of working concentration in the dehumidifier of liquid desiccant air conditioner," Applied Energy, Elsevier, vol. 202(C), pages 648-661.
    19. Fateme Dinmohammadi & Yuxuan Han & Mahmood Shafiee, 2023. "Predicting Energy Consumption in Residential Buildings Using Advanced Machine Learning Algorithms," Energies, MDPI, vol. 16(9), pages 1-23, April.
    20. Zhang, Xinru & Hou, Lei & Liu, Jiaquan & Yang, Kai & Chai, Chong & Li, Yanhao & He, Sichen, 2022. "Energy consumption prediction for crude oil pipelines based on integrating mechanism analysis and data mining," Energy, Elsevier, vol. 254(PB).

    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:appene:v:258:y:2020:i:c:s0306261919317696. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.