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Experimental determination of the energy efficiency of an air-cooled chiller under part load conditions

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  • Yu, F.W.
  • Chan, K.T.

Abstract

In cities located in a subtropical climate, air-cooled chillers are commonly used to provide cooling to the indoor environment. This accounts for the increasing electricity demand of buildings over the decades. This paper investigates how the condensing temperature serves to accurately determine the energy efficiency, or coefficient of performance (COP), of air-cooled chillers under part load conditions. An experiment on an air-cooled reciprocating chiller showed that for any given operating condition, the COP of the chiller varies, depending on how the condensing temperature is controlled. A sensitivity analysis is implemented to investigate to what extent COP is responding to changes in operating variables and confirms that the condensing temperature is an adequate variable to gauge COP under various operating conditions. The specifications of the upper limit for the condensing temperature in order to improve the energy efficiency of air-cooled chillers are discussed. The results of this work will give designers and researchers a good idea about how to model chiller energy performance curves in the thermal and energy computation exercises.

Suggested Citation

  • Yu, F.W. & Chan, K.T., 2005. "Experimental determination of the energy efficiency of an air-cooled chiller under part load conditions," Energy, Elsevier, vol. 30(10), pages 1747-1758.
    • Handle: RePEc:eee:energy:v:30:y:2005:i:10:p:1747-1758
    DOI: 10.1016/j.energy.2004.11.007
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    References listed on IDEAS

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    1. Lee, W.L. & Yik, F.W.H. & Jones, P., 2003. "A strategy for prioritising interactive measures for enhancing energy efficiency of air-conditioned buildings," Energy, Elsevier, vol. 28(8), pages 877-893.
    2. Chan, K. T. & Yu, F. W., 2002. "Applying condensing-temperature control in air-cooled reciprocating water chillers for energy efficiency," Applied Energy, Elsevier, vol. 72(3-4), pages 565-581, July.
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    2. Yu, F.W. & Chan, K.T., 2006. "Improved condenser design and condenser-fan operation for air-cooled chillers," Applied Energy, Elsevier, vol. 83(6), pages 628-648, June.
    3. Deymi-Dashtebayaz, Mahdi & Kheir Abadi, Majid & Asadi, Mostafa & Khutornaya, Julia & Sergienko, Olga, 2024. "Investigation of a new solar-wind energy-based heat pump dryer for food waste drying based on different weather conditions," Energy, Elsevier, vol. 290(C).
    4. Izquierdo, M. & Moreno-Rodríguez, A. & González-Gil, A. & García-Hernando, N., 2011. "Air conditioning in the region of Madrid, Spain: An approach to electricity consumption, economics and CO2 emissions," Energy, Elsevier, vol. 36(3), pages 1630-1639.
    5. Deymi-Dashtebayaz, Mahdi & Davoodi, Vajihe & Khutornaya, Julia & Sergienko, Olga, 2023. "Parametric analysis and multi-objective optimization of a heat pump dryer based on working conditions and using different refrigerants," Energy, Elsevier, vol. 284(C).
    6. Yang, Tingting & Wang, Wei & Zeng, Deliang & Liu, Jizhen & Cui, Can, 2017. "Closed-loop optimization control on fan speed of air-cooled steam condenser units for energy saving and rapid load regulation," Energy, Elsevier, vol. 135(C), pages 394-404.
    7. Chua, K.J. & Chou, S.K. & Yang, W.M. & Yan, J., 2013. "Achieving better energy-efficient air conditioning – A review of technologies and strategies," Applied Energy, Elsevier, vol. 104(C), pages 87-104.
    8. DeForest, Nicholas & Mendes, Gonçalo & Stadler, Michael & Feng, Wei & Lai, Judy & Marnay, Chris, 2014. "Optimal deployment of thermal energy storage under diverse economic and climate conditions," Applied Energy, Elsevier, vol. 119(C), pages 488-496.
    9. Kusiak, Andrew & Tang, Fan & Xu, Guanglin, 2011. "Multi-objective optimization of HVAC system with an evolutionary computation algorithm," Energy, Elsevier, vol. 36(5), pages 2440-2449.
    10. Ma, Zhenjun & Wang, Shengwei, 2011. "Enhancing the performance of large primary-secondary chilled water systems by using bypass check valve," Energy, Elsevier, vol. 36(1), pages 268-276.
    11. Serafín Alonso & Antonio Morán & Miguel Ángel Prada & Perfecto Reguera & Juan José Fuertes & Manuel Domínguez, 2019. "A Data-Driven Approach for Enhancing the Efficiency in Chiller Plants: A Hospital Case Study," Energies, MDPI, vol. 12(5), pages 1-28, March.
    12. Zhuang, Chaoqun & Wang, Shengwei & Shan, Kui, 2020. "A risk-based robust optimal chiller sequencing control strategy for energy-efficient operation considering measurement uncertainties," Applied Energy, Elsevier, vol. 280(C).
    13. Ma, Zhenjun & Wang, Shengwei, 2009. "Building energy research in Hong Kong: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 1870-1883, October.
    14. Kheir Abadi, Majid & Davoodi, Vajihe & Deymi-Dashtebayaz, Mahdi & Ebrahimi-Moghadam, Amir, 2023. "Determining the best scenario for providing electrical, cooling, and hot water consuming of a building with utilizing a novel wind/solar-based hybrid system," Energy, Elsevier, vol. 273(C).

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