IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i7p1734-d1624566.html
   My bibliography  Save this article

Research Progress on the Performance Enhancement Technology of Ice-on-Coil Energy Storage

Author

Listed:
  • Xinxin Guo

    (Institute of Electrical Engineering, Chinese Academy of Sciences, Haidian District, Beijing 100190, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    Key Laboratory of Long-Duration and Large-Scale Energy Storage (Chinese Academy of Sciences), Beijing 100190, China)

  • Xiaoyu Xu

    (College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China)

  • Zhixin Wang

    (School of Instrument Science and Electrical Engineering, Jilin University, Changchun 130026, China)

  • Zheshao Chang

    (Institute of Electrical Engineering, Chinese Academy of Sciences, Haidian District, Beijing 100190, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    Key Laboratory of Long-Duration and Large-Scale Energy Storage (Chinese Academy of Sciences), Beijing 100190, China)

  • Chun Chang

    (Institute of Electrical Engineering, Chinese Academy of Sciences, Haidian District, Beijing 100190, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    School of Renewable Energy, Inner Mongolia University of Technology, Ordos 017010, China)

Abstract

Ice-on-coil energy storage technology has been widely used in air conditioning systems and industrial refrigeration as an efficient energy storage technology. This paper reviews the research progress of ice-on-coil energy storage technology, including its working principle, system design, key parameter optimization, and practical application challenges and solutions. Three kinds of ice melting systems are introduced. The internal ice melting system has the largest cold storage density and the slowest rate of ice melting. The external ice melting system has the lowest cold storage density and the fastest rate of ice melting. The combined ice melting system can have the highest density of cold storage density and a high rate of ice melting. By comparing the results of different studies, the influence of fin and thin ring application on the heat transfer enhancements of the ice-on-coil storage system is summarized. It is found that the ice storage time can be reduced by 21% and 34% when the annular fin and thin ring are set. Regarding system control, adopting the ice-melting priority strategy increases operating energy consumption, but the economy improves; using the unit priority strategy lowers operating energy consumption, but the economy suffers slightly. When the cooling demand exceeds the cooling capacity of the chiller, an ice melting priority control strategy is more economical. Some suggestions for future research are presented, such as optimizing the shape and arrangement of coil fins and ice storage systems integrated with renewable energy. It provides guidance for the further development of ice storage air conditioning technology.

Suggested Citation

  • Xinxin Guo & Xiaoyu Xu & Zhixin Wang & Zheshao Chang & Chun Chang, 2025. "Research Progress on the Performance Enhancement Technology of Ice-on-Coil Energy Storage," Energies, MDPI, vol. 18(7), pages 1-22, March.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:7:p:1734-:d:1624566
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/7/1734/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/7/1734/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gao, Mingfei & Han, Zhonghe & Zhang, Ce & Li, Peng & Wu, Di & Li, Peng, 2023. "Optimal configuration for regional integrated energy systems with multi-element hybrid energy storage," Energy, Elsevier, vol. 277(C).
    2. Candanedo, J.A. & Dehkordi, V.R. & Stylianou, M., 2013. "Model-based predictive control of an ice storage device in a building cooling system," Applied Energy, Elsevier, vol. 111(C), pages 1032-1045.
    3. Lu, Zhe & Wang, Sheliang & Ying, Honghao & Liu, Bo & Jia, Wurong & Xie, Jiangsheng & Sun, Yanwen, 2024. "Preparation and thermal properties of eutectic phase change materials (EPCMs) with nanographite addition for cold thermal energy storage," Energy, Elsevier, vol. 290(C).
    4. Lu, Yuehong & Wang, Shengwei & Sun, Yongjun & Yan, Chengchu, 2015. "Optimal scheduling of buildings with energy generation and thermal energy storage under dynamic electricity pricing using mixed-integer nonlinear programming," Applied Energy, Elsevier, vol. 147(C), pages 49-58.
    5. Gao, Jiajia & Kang, Jing & Zhang, Chong & Gang, Wenjie, 2018. "Energy performance and operation characteristics of distributed energy systems with district cooling systems in subtropical areas under different control strategies," Energy, Elsevier, vol. 153(C), pages 849-860.
    6. Wenninger, Simon & Kaymakci, Can & Wiethe, Christian, 2022. "Explainable long-term building energy consumption prediction using QLattice," Applied Energy, Elsevier, vol. 308(C).
    7. Karlilar Pata, Selin & Pata, Ugur Korkut & Wang, Qiang, 2025. "Ecological power of energy storage, clean fuel innovation, and energy-related research and development technologies," Renewable Energy, Elsevier, vol. 241(C).
    8. Cui, Borui & Wang, Shengwei & Sun, Yongjun, 2014. "Life-cycle cost benefit analysis and optimal design of small scale active storage system for building demand limiting," Energy, Elsevier, vol. 73(C), pages 787-800.
    9. Tay, N.H.S. & Bruno, F. & Belusko, M., 2013. "Comparison of pinned and finned tubes in a phase change thermal energy storage system using CFD," Applied Energy, Elsevier, vol. 104(C), pages 79-86.
    10. Cui, Borui & Gao, Dian-ce & Xiao, Fu & Wang, Shengwei, 2017. "Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings," Applied Energy, Elsevier, vol. 201(C), pages 382-396.
    11. Ren, Hongbo & Jiang, Zipei & Wu, Qiong & Li, Qifen & Yang, Yongwen, 2022. "Integrated optimization of a regional integrated energy system with thermal energy storage considering both resilience and reliability," Energy, Elsevier, vol. 261(PB).
    12. 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.
    13. Ahmad, Ejaz & Khan, Dilawar & Anser, Muhammad Khalid & Nassani, Abdelmohsen A. & Hassan, Syeda Anam & Zaman, Khalid, 2024. "The influence of grid connectivity, electricity pricing, policy-driven power incentives, and carbon emissions on renewable energy adoption: Exploring key factors," Renewable Energy, Elsevier, vol. 232(C).
    14. Zhang, Yafei & Liu, Zedong & Chen, Hua & Li, Guangkang & Zhang, Jiaming, 2024. "Experimental study on the influence of gas-blowing flow rate on the cold discharge characteristics of external ice-melting ice storage system," Renewable Energy, Elsevier, vol. 230(C).
    15. Sciacovelli, A. & Gagliardi, F. & Verda, V., 2015. "Maximization of performance of a PCM latent heat storage system with innovative fins," Applied Energy, Elsevier, vol. 137(C), pages 707-715.
    16. Dovrtel, Klemen & Medved, Sašo, 2011. "Weather-predicted control of building free cooling system," Applied Energy, Elsevier, vol. 88(9), pages 3088-3096.
    17. Xiaoyu Xu & Chun Chang & Xinxin Guo & Mingzhi Zhao, 2023. "Experimental and Numerical Study of the Ice Storage Process and Material Properties of Ice Storage Coils," Energies, MDPI, vol. 16(14), pages 1-18, July.
    18. Cox, Sam J. & Kim, Dongsu & Cho, Heejin & Mago, Pedro, 2019. "Real time optimal control of district cooling system with thermal energy storage using neural networks," Applied Energy, Elsevier, vol. 238(C), pages 466-480.
    19. Ashok, S. & Banerjee, R., 2003. "Optimal cool storage capacity for load management," Energy, Elsevier, vol. 28(2), pages 115-126.
    20. Cheng, Chuanxiao & Wang, Fan & Tian, Yongjia & Wu, Xuehong & Zheng, Jili & Zhang, Jun & Li, Longwei & Yang, Penglin & Zhao, Jiafei, 2020. "Review and prospects of hydrate cold storage technology," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
    21. Jannesari, Hamid & Abdollahi, Naeim, 2017. "Experimental and numerical study of thin ring and annular fin effects on improving the ice formation in ice-on-coil thermal storage systems," Applied Energy, Elsevier, vol. 189(C), pages 369-384.
    Full references (including those not matched with items on IDEAS)

    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. Chang, Chun & Xu, Xiaoyu & Guo, Xinxin & Yu, Rong & Rasakhodzhaev, Bakhramzhan & Bao, Daorina & Zhao, Mingzhi, 2024. "Experimental and numerical study during the solidification process of a vertical and horizontal coiled ice storage system," Energy, Elsevier, vol. 298(C).
    2. Xiaoyu Xu & Chun Chang & Xinxin Guo & Mingzhi Zhao, 2023. "Experimental and Numerical Study of the Ice Storage Process and Material Properties of Ice Storage Coils," Energies, MDPI, vol. 16(14), pages 1-18, July.
    3. 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.
    4. Wan, Hang & Gong, Yuyang & Dang, Chuangyin & Wang, Shengwei & Huang, Gongsheng, 2025. "Power control of latent heat thermal energy storage units using a model-based predictive strategy," Applied Energy, Elsevier, vol. 382(C).
    5. Cao, Hui & Lin, Jiajing & Li, Nan, 2023. "Optimal control and energy efficiency evaluation of district ice storage system," Energy, Elsevier, vol. 276(C).
    6. Cui, Borui & Gao, Dian-ce & Xiao, Fu & Wang, Shengwei, 2017. "Model-based optimal design of active cool thermal energy storage for maximal life-cycle cost saving from demand management in commercial buildings," Applied Energy, Elsevier, vol. 201(C), pages 382-396.
    7. Fanghan Su & Zhiyuan Wang & Yue Yuan & Chengcheng Song & Kejun Zeng & Yixing Chen & Rongpeng Zhang, 2023. "Enhanced Operation of Ice Storage System for Peak Load Management in Shopping Malls across Diverse Climate Zones," Sustainability, MDPI, vol. 15(20), pages 1-23, October.
    8. Cox, Sam J. & Kim, Dongsu & Cho, Heejin & Mago, Pedro, 2019. "Real time optimal control of district cooling system with thermal energy storage using neural networks," Applied Energy, Elsevier, vol. 238(C), pages 466-480.
    9. Du, Kun & Calautit, John & Eames, Philip & Wu, Yupeng, 2021. "A state-of-the-art review of the application of phase change materials (PCM) in Mobilized-Thermal Energy Storage (M-TES) for recovering low-temperature industrial waste heat (IWH) for distributed heat," Renewable Energy, Elsevier, vol. 168(C), pages 1040-1057.
    10. 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).
    11. Gruber, J.K. & Huerta, F. & Matatagui, P. & Prodanović, M., 2015. "Advanced building energy management based on a two-stage receding horizon optimization," Applied Energy, Elsevier, vol. 160(C), pages 194-205.
    12. Yang, Xiaohu & Guo, Junfei & Yang, Bo & Cheng, Haonan & Wei, Pan & He, Ya-Ling, 2020. "Design of non-uniformly distributed annular fins for a shell-and-tube thermal energy storage unit," Applied Energy, Elsevier, vol. 279(C).
    13. Liu, Zhan & Liu, Zihui & Guo, Junfei & Wang, Fan & Yang, Xiaohu & Yan, Jinyue, 2022. "Innovative ladder-shaped fin design on a latent heat storage device for waste heat recovery," Applied Energy, Elsevier, vol. 321(C).
    14. Chai, Jiale & Huang, Pei & Sun, Yongjun, 2019. "Investigations of climate change impacts on net-zero energy building lifecycle performance in typical Chinese climate regions," Energy, Elsevier, vol. 185(C), pages 176-189.
    15. 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.
    16. Wang, Chengshan & Jiao, Bingqi & Guo, Li & Tian, Zhe & Niu, Jide & Li, Siwei, 2016. "Robust scheduling of building energy system under uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 366-376.
    17. Georg Scharinger-Urschitz & Heimo Walter & Markus Haider, 2019. "Heat Transfer in Latent High-Temperature Thermal Energy Storage Systems—Experimental Investigation," Energies, MDPI, vol. 12(7), pages 1-19, April.
    18. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu, 2023. "Globally optimal control of hybrid chilled water plants integrated with small-scale thermal energy storage for energy-efficient operation," Energy, Elsevier, vol. 262(PA).
    19. Yang, Jialin & Yang, Lijun & Xu, Chao & Du, Xiaoze, 2016. "Experimental study on enhancement of thermal energy storage with phase-change material," Applied Energy, Elsevier, vol. 169(C), pages 164-176.
    20. Barzin, Reza & Chen, John J.J. & Young, Brent R. & Farid, Mohammed M, 2016. "Application of weather forecast in conjunction with price-based method for PCM solar passive buildings – An experimental study," Applied Energy, Elsevier, vol. 163(C), pages 9-18.

    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:gam:jeners:v:18:y:2025:i:7:p:1734-:d:1624566. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.