IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v347y2026ics0360544226004706.html

Comparative energy performance evaluation of high-density data centers using air- and immersion-cooling systems with various economizers

Author

Listed:
  • Ham, Se Hyeon
  • Jang, Dong Soo
  • Kwon, Soonbum
  • Chung, Jun Yeob
  • Kim, Yongchan

Abstract

With increasing demand for high-density data centers, immersion-cooling systems and economizers have emerged as energy-efficient alternatives to conventional air-cooling systems. A comprehensive analysis of the combined adoption of immersion-cooling and economizer systems is essential for reducing energy consumption in data centers. This study analyzed the annual energy performance of a data center using immersion-cooling systems with economizers in various climatic regions. Specifically, the energy performance of the immersion-cooling system with economizers was compared with that of a conventional air-cooling system. Using economizers in the air-cooling system decreased annual power consumption by up to 40%, with the lowest monthly power usage effectiveness (PUE) values of 1.257, 1.195, and 1.146 with a non-economizer (NE), water-side economizer (WSE), and air-side economizer (ASE), respectively. The annual PUEs of the immersion-cooling systems with an NE and a WSE were 0.052 and 0.078, respectively, lower than that of the air-cooling system with an NE. Moreover, the influence of climatic conditions on the energy performance of air- and immersion-cooling systems with economizers was analyzed. The immersion-cooling system with a WSE exhibited a lower PUE than that with an ASE under most climatic conditions. In addition, a comparative life-cycle cost (LCC) analysis showed that the immersion-cooling system was economically superior to the air-cooling system specifically in climate zones at MATs above 14.4 °C.

Suggested Citation

  • Ham, Se Hyeon & Jang, Dong Soo & Kwon, Soonbum & Chung, Jun Yeob & Kim, Yongchan, 2026. "Comparative energy performance evaluation of high-density data centers using air- and immersion-cooling systems with various economizers," Energy, Elsevier, vol. 347(C).
    • Handle: RePEc:eee:energy:v:347:y:2026:i:c:s0360544226004706
    DOI: 10.1016/j.energy.2026.140367
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544226004706
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2026.140367?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Hainan & Shao, Shuangquan & Xu, Hongbo & Zou, Huiming & Tian, Changqing, 2014. "Free cooling of data centers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 35(C), pages 171-182.
    2. Han, Zongwei & Xue, Da & Wei, Haotian & Ji, Qiang & Sun, Xiaoqing & Li, Xiuming, 2021. "Study on operation strategy of evaporative cooling composite air conditioning system in data center," Renewable Energy, Elsevier, vol. 177(C), pages 1147-1160.
    3. Kandasamy, Ranjith & Ho, Jin Yao & Liu, Pengfei & Wong, Teck Neng & Toh, Kok Chuan & Chua, Sunshine Jr, 2022. "Two-phase spray cooling for high ambient temperature data centers: Evaluation of system performance," Applied Energy, Elsevier, vol. 305(C).
    4. Fulpagare, Yogesh & Bhargav, Atul, 2015. "Advances in data center thermal management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 981-996.
    5. Zimmermann, Severin & Meijer, Ingmar & Tiwari, Manish K. & Paredes, Stephan & Michel, Bruno & Poulikakos, Dimos, 2012. "Aquasar: A hot water cooled data center with direct energy reuse," Energy, Elsevier, vol. 43(1), pages 237-245.
    6. Mitchell-Jackson, J. & Koomey, J.G. & Nordman, B. & Blazek, M., 2003. "Data center power requirements: measurements from Silicon Valley," Energy, Elsevier, vol. 28(8), pages 837-850.
    7. Cho, Jinkyun & Kim, Yundeok, 2016. "Improving energy efficiency of dedicated cooling system and its contribution towards meeting an energy-optimized data center," Applied Energy, Elsevier, vol. 165(C), pages 967-982.
    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. Cheung, Howard & Wang, Shengwei & Zhuang, Chaoqun & Gu, Jiefan, 2018. "A simplified power consumption model of information technology (IT) equipment in data centers for energy system real-time dynamic simulation," Applied Energy, Elsevier, vol. 222(C), pages 329-342.
    2. Lee, Yee-Ting & Wen, Chih-Yung & Shih, Yang-Cheng & Li, Zhengtong & Yang, An-Shik, 2022. "Numerical and experimental investigations on thermal management for data center with cold aisle containment configuration," Applied Energy, Elsevier, vol. 307(C).
    3. Di Salvo, André L.A. & Agostinho, Feni & Almeida, Cecília M.V.B. & Giannetti, Biagio F., 2017. "Can cloud computing be labeled as “green”? Insights under an environmental accounting perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 514-526.
    4. Jerez Monsalves, Juan & Bergaentzlé, Claire & Keles, Dogan, 2023. "Impacts of flexible-cooling and waste-heat recovery from data centres on energy systems: A Danish case study," Energy, Elsevier, vol. 281(C).
    5. Xiaofei Huang & Junwei Yan & Xuan Zhou & Yixin Wu & Shichen Hu, 2023. "Cooling Technologies for Internet Data Center in China: Principle, Energy Efficiency, and Applications," Energies, MDPI, vol. 16(20), pages 1-31, October.
    6. Lu, Gui & Liu, Yan & Jiang, Can & Yang, Zi-Jing & Meng, Jing-Hui, 2025. "A deep agent reinforcement learning-based early adaptive multivariate state estimation fault diagnosis method for multi-mode cooling system in data center," Energy, Elsevier, vol. 334(C).
    7. Chu, Wen-Xiao & Wang, Chi-Chuan, 2019. "A review on airflow management in data centers," Applied Energy, Elsevier, vol. 240(C), pages 84-119.
    8. Wansheng Yang & Lin Yang & Junjie Ou & Zhongqi Lin & Xudong Zhao, 2019. "Investigation of Heat Management in High Thermal Density Communication Cabinet by a Rear Door Liquid Cooling System," Energies, MDPI, vol. 12(22), pages 1-25, November.
    9. Sijun Xu & Hua Zhang & Zilong Wang, 2023. "Thermal Management and Energy Consumption in Air, Liquid, and Free Cooling Systems for Data Centers: A Review," Energies, MDPI, vol. 16(3), pages 1-25, January.
    10. Liu, Pengfei & Kandasamy, Ranjith & Ho, Jin Yao & Wong, Teck Neng & Toh, Kok Chuan, 2023. "Dynamic performance analysis and thermal modelling of a novel two-phase spray cooled rack system for data center cooling," Energy, Elsevier, vol. 269(C).
    11. Graamans, Luuk & Tenpierik, Martin & van den Dobbelsteen, Andy & Stanghellini, Cecilia, 2020. "Plant factories: Reducing energy demand at high internal heat loads through façade design," Applied Energy, Elsevier, vol. 262(C).
    12. Habibi Khalaj, Ali & Halgamuge, Saman K., 2017. "A Review on efficient thermal management of air- and liquid-cooled data centers: From chip to the cooling system," Applied Energy, Elsevier, vol. 205(C), pages 1165-1188.
    13. Oró, Eduard & Depoorter, Victor & Garcia, Albert & Salom, Jaume, 2015. "Energy efficiency and renewable energy integration in data centres. Strategies and modelling review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 429-445.
    14. Cho, Jinkyun & Kim, Youngmo, 2021. "Development of modular air containment system: Thermal performance optimization of row-based cooling for high-density data centers," Energy, Elsevier, vol. 231(C).
    15. Shuja, Junaid & Gani, Abdullah & Shamshirband, Shahaboddin & Ahmad, Raja Wasim & Bilal, Kashif, 2016. "Sustainable Cloud Data Centers: A survey of enabling techniques and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 195-214.
    16. Kanbur, Baris Burak & Wu, Chenlong & Fan, Simiao & Duan, Fei, 2021. "System-level experimental investigations of the direct immersion cooling data center units with thermodynamic and thermoeconomic assessments," Energy, Elsevier, vol. 217(C).
    17. Matteo Manganelli & Alessandro Soldati & Luigi Martirano & Seeram Ramakrishna, 2021. "Strategies for Improving the Sustainability of Data Centers via Energy Mix, Energy Conservation, and Circular Energy," Sustainability, MDPI, vol. 13(11), pages 1-25, May.
    18. Ding, Tao & Chen, Xiaoxuan & Cao, Hanwen & He, Zhiguang & Wang, Jianmin & Li, Zhen, 2021. "Principles of loop thermosyphon and its application in data center cooling systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    19. Zhang, Hainan & Shao, Shuangquan & Tian, Changqing & Zhang, Kunzhu, 2018. "A review on thermosyphon and its integrated system with vapor compression for free cooling of data centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 789-798.
    20. Jing Yin & Shangming Wang & Xuehao Sang & Zhifu Zhou & Bin Chen & Panidis Thrassos & Alexandros Romeos & Athanasios Giannadakis, 2022. "Spray Cooling as a High-Efficient Thermal Management Solution: A Review," Energies, MDPI, vol. 15(22), pages 1-29, November.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:energy:v:347:y:2026:i:c:s0360544226004706. 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.journals.elsevier.com/energy .

    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.