IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v87y2010i4p1198-1206.html
   My bibliography  Save this article

Simulation and electricity savings estimation of air-cooled centrifugal chiller system with mist pre-cooling

Author

Listed:
  • Yu, F.W.
  • Chan, K.T.

Abstract

This paper analyses how to apply mist pre-cooling coupled with condensing temperature control to enhance the coefficient of performance (COP) of an air-cooled chiller system and hence achieve electricity savings. A modified DOE-2.1E chiller model was developed to predict the change of chiller COP due to various set points of condensing temperature and pre-cooling of air stream entering the condenser. The model was calibrated by using manufacturer's data and used to estimate the annual electricity consumption of a chiller system serving an office building under four operating schemes: traditional head pressure control (HPC); HPC with a fixed mist generation rate; condensing temperature control (CTC) with a fixed mist generation rate; CTC with an optimal mist generation rate. It was estimated that using optimal mist control with CTC could achieve a 19.84% reduction in the annual electricity consumption of the system. Considerations when using mist pre-cooling to maximize electricity savings have been discussed.

Suggested Citation

  • Yu, F.W. & Chan, K.T., 2010. "Simulation and electricity savings estimation of air-cooled centrifugal chiller system with mist pre-cooling," Applied Energy, Elsevier, vol. 87(4), pages 1198-1206, April.
  • Handle: RePEc:eee:appene:v:87:y:2010:i:4:p:1198-1206
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306-2619(09)00358-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. 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.
    2. Lee, Wen-Shing & Chen, Yi -Ting & Wu, Ting-Hau, 2009. "Optimization for ice-storage air-conditioning system using particle swarm algorithm," Applied Energy, Elsevier, vol. 86(9), pages 1589-1595, September.
    3. Lam, Joseph C. & Wan, Kevin K.W. & Cheung, K.L., 2009. "An analysis of climatic influences on chiller plant electricity consumption," Applied Energy, Elsevier, vol. 86(6), pages 933-940, June.
    4. Yu, F.W. & Chan, K.T., 2007. "Modelling of a condenser-fan control for an air-cooled centrifugal chiller," Applied Energy, Elsevier, vol. 84(11), pages 1117-1135, November.
    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. Yang, L.J. & Wang, M.H. & Du, X.Z. & Yang, Y.P., 2012. "Trapezoidal array of air-cooled condensers to restrain the adverse impacts of ambient winds in a power plant," Applied Energy, Elsevier, vol. 99(C), pages 402-413.
    2. Wang, Yijun & Jin, Xinqiao & Shi, Wantao & Wang, Jiangqing, 2019. "Online chiller loading strategy based on the near-optimal performance map for energy conservation," Applied Energy, Elsevier, vol. 238(C), pages 1444-1451.

    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. He, Zhaoyu & Guo, Weimin & Zhang, Peng, 2022. "Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    2. Chan, Wai Mun & Leong, Yik Teeng & Foo, Ji Jinn & Chew, Irene Mei Leng, 2017. "Synthesis of energy efficient chilled and cooling water network by integrating waste heat recovery refrigeration system," Energy, Elsevier, vol. 141(C), pages 1555-1568.
    3. Abou-Ziyan, Hosny Z. & Alajmi, Ali F., 2014. "Effect of load-sharing operation strategy on the aggregate performance of existed multiple-chiller systems," Applied Energy, Elsevier, vol. 135(C), pages 329-338.
    4. Wang, Zhe & Hong, Tianzhen & Piette, Mary Ann, 2019. "Predicting plug loads with occupant count data through a deep learning approach," Energy, Elsevier, vol. 181(C), pages 29-42.
    5. Lee, W.L. & Lee, S.H., 2007. "Developing a simplified model for evaluating chiller-system configurations," Applied Energy, Elsevier, vol. 84(3), pages 290-306, March.
    6. Zhu, Dan & Tao, Shu & Wang, Rong & Shen, Huizhong & Huang, Ye & Shen, Guofeng & Wang, Bin & Li, Wei & Zhang, Yanyan & Chen, Han & Chen, Yuanchen & Liu, Junfeng & Li, Bengang & Wang, Xilong & Liu, Wenx, 2013. "Temporal and spatial trends of residential energy consumption and air pollutant emissions in China," Applied Energy, Elsevier, vol. 106(C), pages 17-24.
    7. Kyriakarakos, George & Dounis, Anastasios I. & Rozakis, Stelios & Arvanitis, Konstantinos G. & Papadakis, George, 2011. "Polygeneration microgrids: A viable solution in remote areas for supplying power, potable water and hydrogen as transportation fuel," Applied Energy, Elsevier, vol. 88(12), pages 4517-4526.
    8. Lam, Joseph C. & Wan, Kevin K.W. & Wong, S.L. & Lam, Tony N.T., 2010. "Long-term trends of heat stress and energy use implications in subtropical climates," Applied Energy, Elsevier, vol. 87(2), pages 608-612, February.
    9. Pu, Jing & Liu, Guilian & Feng, Xiao, 2012. "Cumulative exergy analysis of ice thermal storage air conditioning system," Applied Energy, Elsevier, vol. 93(C), pages 564-569.
    10. Gao, Dian-ce & Wang, Shengwei & Shan, Kui, 2016. "In-situ implementation and evaluation of an online robust pump speed control strategy for avoiding low delta-T syndrome in complex chilled water systems of high-rise buildings," Applied Energy, Elsevier, vol. 171(C), pages 541-554.
    11. Chammy Lau & Irini Lai Fun Tang & Wilco Chan, 2021. "Waterfront Hotels’ Chillers: Energy Benchmarking and ESG Reporting," Sustainability, MDPI, vol. 13(11), pages 1-15, June.
    12. Chen, Lei & Yang, Lijun & Du, Xiaoze & Yang, Yongping, 2016. "A novel layout of air-cooled condensers to improve thermo-flow performances," Applied Energy, Elsevier, vol. 165(C), pages 244-259.
    13. Chi-Chun Lo & Shang-Ho Tsai & Bor-Shyh Lin, 2016. "Ice Storage Air-Conditioning System Simulation with Dynamic Electricity Pricing: A Demand Response Study," Energies, MDPI, vol. 9(2), pages 1-16, February.
    14. Niknam, Taher & Firouzi, Bahman Bahmani & Ostadi, Amir, 2010. "A new fuzzy adaptive particle swarm optimization for daily Volt/Var control in distribution networks considering distributed generators," Applied Energy, Elsevier, vol. 87(6), pages 1919-1928, June.
    15. Lam, Joseph C. & Wan, Kevin K.W. & Lam, Tony N.T. & Wong, S.L., 2010. "An analysis of future building energy use in subtropical Hong Kong," Energy, Elsevier, vol. 35(3), pages 1482-1490.
    16. 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.
    17. Chan, K.T. & Yu, F.W., 2006. "Thermodynamic-behaviour model for air-cooled screw chillers with a variable set-point condensing temperature," Applied Energy, Elsevier, vol. 83(3), pages 265-279, March.
    18. Hu, Mengqi & Weir, Jeffery D. & Wu, Teresa, 2012. "Decentralized operation strategies for an integrated building energy system using a memetic algorithm," European Journal of Operational Research, Elsevier, vol. 217(1), pages 185-197.
    19. Ebrahimi, Mahyar, 2020. "Storing electricity as thermal energy at community level for demand side management," Energy, Elsevier, vol. 193(C).
    20. Luo, Na & Hong, Tianzhen & Li, Hui & Jia, Ruoxi & Weng, Wenguo, 2017. "Data analytics and optimization of an ice-based energy storage system for commercial buildings," Applied Energy, Elsevier, vol. 204(C), pages 459-475.

    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:87:y:2010:i:4:p:1198-1206. 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.