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Optimization of reversibly used cooling tower with downward spraying

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  • Cui, Haijiao
  • Li, Nianping
  • Wang, Xinlei
  • Peng, Jinqing
  • Li, Yuan
  • Wu, Zhibin

Abstract

Heat pumps associated with reversibly used cooling towers present great potential for energy saving in subtropical areas. To study the heat and mass transfer characteristics of reversibly used cooling towers with downward spraying (DSRUCT) and optimize its thermal performance, a mathematical model was developed and validated through field experiments. Then a parametric study was conducted to study the impacts of initial solution temperature (−4 to −1 °C), gas velocity (2.5–4 m/s), initial droplet velocity (4–10 m/s) and droplet diameter (0.65–1.2 mm) on the heat rate, tower effectiveness and solution temperature distribution. According to the results of the parametric study, we proposed an optimization method established on the concepts of critical gas velocity and critical height. This method was based on multivariable analysis. Two operating parameters (gas velocity and droplet diameter) and one structural parameter (tower height) were simultaneously concerned. The results of this work provided a theoretical foundation for optimizing the thermal performance and saving initial investment of DSRUCT and other counter-current spray systems, e.g., dehumidification, desulfurization, spray cooling, and carbon capture.

Suggested Citation

  • Cui, Haijiao & Li, Nianping & Wang, Xinlei & Peng, Jinqing & Li, Yuan & Wu, Zhibin, 2017. "Optimization of reversibly used cooling tower with downward spraying," Energy, Elsevier, vol. 127(C), pages 30-43.
  • Handle: RePEc:eee:energy:v:127:y:2017:i:c:p:30-43
    DOI: 10.1016/j.energy.2017.03.074
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    References listed on IDEAS

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    1. Yang, Zili & Zhang, Kaisheng & Hwang, Yunho & Lian, Zhiwei, 2016. "Performance investigation on the ultrasonic atomization liquid desiccant regeneration system," Applied Energy, Elsevier, vol. 171(C), pages 12-25.
    2. Niksiar, Arezou & Rahimi, Amir, 2009. "Energy and exergy analysis for cocurrent gas spray cooling systems based on the results of mathematical modeling and simulation," Energy, Elsevier, vol. 34(1), pages 14-21.
    3. Yuan, Fang & Chen, Qun, 2012. "A global optimization method for evaporative cooling systems based on the entransy theory," Energy, Elsevier, vol. 42(1), pages 181-191.
    4. Cui, Haijiao & Li, Nianping & Peng, Jinqing & Cheng, Jianlin & Li, Shengbing, 2016. "Study on the dynamic and thermal performances of a reversibly used cooling tower with upward spraying," Energy, Elsevier, vol. 96(C), pages 268-277.
    5. Chen, Qun & Pan, Ning & Guo, Zeng-Yuan, 2011. "A new approach to analysis and optimization of evaporative cooling system II: Applications," Energy, Elsevier, vol. 36(5), pages 2890-2898.
    6. Chen, Qun & Yang, Kangding & Wang, Moran & Pan, Ning & Guo, Zeng-Yuan, 2010. "A new approach to analysis and optimization of evaporative cooling system I: Theory," Energy, Elsevier, vol. 35(6), pages 2448-2454.
    7. Qi, Xiaoni & Liu, Yongqi & Guo, Qianjian & Yu, Jie & Yu, Shanshan, 2016. "Performance prediction of seawater shower cooling towers," Energy, Elsevier, vol. 97(C), pages 435-443.
    8. Yajima, Satoshi & Givoni, Baruch, 1997. "Experimental performance of the shower cooling tower in Japan," Renewable Energy, Elsevier, vol. 10(2), pages 179-183.
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    Cited by:

    1. Ayoub, Ali & Gjorgiev, Blaže & Sansavini, Giovanni, 2018. "Cooling towers performance in a changing climate: Techno-economic modeling and design optimization," Energy, Elsevier, vol. 160(C), pages 1133-1143.
    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. Yifei Lv & Jun Lu & Yongcai Li & Ling Xie & Lulu Yang & Linlin Yuan, 2020. "Comparative Study of the Heat and Mass Transfer Characteristics between Counter-Flow and Cross-Flow Heat Source Towers," Energies, MDPI, vol. 13(11), pages 1-29, May.
    4. Men, Yiyu & Liu, Xiaohua & Zhang, Tao, 2020. "Analytical solutions of heat and mass transfer process in combined gas-water heat exchanger applied for waste heat recovery," Energy, Elsevier, vol. 206(C).
    5. Cui, Haijiao & Li, Nianping & Peng, Jinqing & Yin, Rongxin & Li, Jingming & Wu, Zhibin, 2018. "Investigation on the thermal performance of a novel spray tower with upward spraying and downward gas flow," Applied Energy, Elsevier, vol. 231(C), pages 12-21.
    6. Ma, Jiaze & Wang, Yufei & Feng, Xiao, 2017. "Energy recovery in cooling water system by hydro turbines," Energy, Elsevier, vol. 139(C), pages 329-340.
    7. Qingqing Liu & Nianping Li & Yongga A & Jiaojiao Duan & Wenyun Yan, 2021. "The Evaluation of the Corrosion Rates of Alloys Applied to the Heating Tower Heat Pump (HTHP) by Machine Learning," Energies, MDPI, vol. 14(7), pages 1-13, April.
    8. Li, Hailong & Wang, Bin & Yan, Jinying & Salman, Chaudhary Awais & Thorin, Eva & Schwede, Sebastian, 2019. "Performance of flue gas quench and its influence on biomass fueled CHP," Energy, Elsevier, vol. 180(C), pages 934-945.

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