IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v285y2023ics0360544223027640.html

Balanced comparative assessment of thermal performance and energy efficiency for three cooling solutions in data centers

Author

Listed:
  • Cho, Jinkyun
  • Lim, Seung-beom

Abstract

As the demand for data centers rises, efficient cooling systems become increasingly vital to ensure uninterrupted operations and adaptability to IT service changes. The research focuses on quantitatively comparing the thermal performance and energy efficiency of cooling systems capable of handling high-density IT power. It aims to provide objective criteria for selecting suitable cooling solutions, including an assessment of three 150 kW-class IT and facility modules, a novel contribution not extensively explored in previous studies. The study evaluates room-based, row-based, and rack-based cooling options based on the configured ITE power density, ensuring that all three solutions meet ASHRAE's recommended IT operating environment through CFD analysis. The research reveals energy efficiency improvements, with PUEcooling decreasing from 1.33 for room-based cooling to 1.28 for rack-based cooling. These improvements are attributed to reduced fan power by CRAC/H type and decreased primary plant energy consumption by increasing COP through the supply chilled water temperature. The findings offer valuable insights for designing cooling solutions tailored to ITE power density and considering factors such as space requirements, thermal performance, energy efficiency, and cost for new hyperscale data centers. Overall, this research constitutes a significant academic contribution in the field of data center cooling solutions.

Suggested Citation

  • Cho, Jinkyun & Lim, Seung-beom, 2023. "Balanced comparative assessment of thermal performance and energy efficiency for three cooling solutions in data centers," Energy, Elsevier, vol. 285(C).
    • Handle: RePEc:eee:energy:v:285:y:2023:i:c:s0360544223027640
    DOI: 10.1016/j.energy.2023.129370
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223027640
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.129370?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. Jinkyun Cho & Beungyong Park & Yongdae Jeong, 2019. "Thermal Performance Evaluation of a Data Center Cooling System under Fault Conditions," Energies, MDPI, vol. 12(15), pages 1-16, August.
    2. Moazamigoodarzi, Hosein & Gupta, Rohit & Pal, Souvik & Tsai, Peiying Jennifer & Ghosh, Suvojit & Puri, Ishwar K., 2020. "Modeling temperature distribution and power consumption in IT server enclosures with row-based cooling architectures," Applied Energy, Elsevier, vol. 261(C).
    3. Tradat, Mohammad I. & Manaserh, Yaman “Mohammad Ali” & Sammakia, Bahgat G. & Hoang, Cong Hiep & Alissa, Husam A., 2021. "An experimental and numerical investigation of novel solution for energy management enhancement in data centers using underfloor plenum porous obstructions," Applied Energy, Elsevier, vol. 289(C).
    4. Güğül, Gül Nihal & Gökçül, Furkan & Eicker, Ursula, 2023. "Sustainability analysis of zero energy consumption data centers with free cooling, waste heat reuse and renewable energy systems: A feasibility study," Energy, Elsevier, vol. 262(PB).
    5. Sun, Xiaoqing & Zhang, Ce & Han, Zongwei & Dong, Jiaxiang & Zhang, Yiqi & Li, Mengyi & Li, Xiuming & Wang, Qinghai & Wen, Zhenwu & Zheng, Baoli, 2023. "Experimental study on a novel pump-driven heat pipe/vapor compression system for rack-level cooling of data centers," Energy, Elsevier, vol. 274(C).
    6. 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).
    7. Cho, Jinkyun & Park, Beungyong & Jang, Seungmin, 2022. "Development of an independent modular air containment system for high-density data centers: Experimental investigation of row-based cooling performance and PUE," Energy, Elsevier, vol. 258(C).
    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. Cho, Jinkyun, 2024. "Optimal supply air temperature with respect to data center operational stability and energy efficiency in a row-based cooling system under fault conditions," Energy, Elsevier, vol. 288(C).
    2. Yifan Li & Congzhe Zhu & Xiuming Li & Bin Yang, 2025. "A Review of Non-Uniform Load Distribution and Solutions in Data Centers: Micro-Scale Liquid Cooling and Large-Scale Air Cooling," Energies, MDPI, vol. 18(1), pages 1-22, January.
    3. Kong, Rui & Zhang, Hainan & Tang, Mingsheng & Zou, Huiming & Tian, Changqing & Ding, Tao, 2024. "Enhancing data center cooling efficiency and ability: A comprehensive review of direct liquid cooling technologies," Energy, Elsevier, vol. 308(C).
    4. Zhang, Ce & Hou, Beiran & Li, Minxia & Dang, Chaobin & Chen, Xun & Li, Xiuming & Han, Zongwei, 2025. "Feasibility analysis of multi-mode data center liquid cooling system integrated with Carnot battery energy storage module," Energy, Elsevier, vol. 320(C).
    5. Tian, Bo & Wang, Ningbo & Huang, Congqi & Liu, Lu & Wei, Zuyuan & Guo, Yanhua & Shao, Shuangquan, 2025. "Absorption refrigeration heating pump system for year-round waste heat recovery in liquid-cooled data centers," Energy, Elsevier, vol. 338(C).

    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. Cho, Jinkyun, 2024. "Optimal supply air temperature with respect to data center operational stability and energy efficiency in a row-based cooling system under fault conditions," Energy, Elsevier, vol. 288(C).
    2. Liu, Qingqing & Wang, Ningbo & Guo, Yujie & Shao, Shuangquan, 2025. "Experimental investigation of a dual-evaporator pump-driven loop heat pipe composite system for data centers cooling," Energy, Elsevier, vol. 341(C).
    3. Sun, Xiaoqing & Zhang, Ce & Han, Zongwei & Dong, Jiaxiang & Zhang, Yiqi & Li, Mengyi & Li, Xiuming & Wang, Qinghai & Wen, Zhenwu & Zheng, Baoli, 2023. "Experimental study on a novel pump-driven heat pipe/vapor compression system for rack-level cooling of data centers," Energy, Elsevier, vol. 274(C).
    4. 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.
    5. Wang, Ningbo & Guo, Yanhua & Huang, Congqi & Tian, Bo & Shao, Shuangquan, 2025. "Multi-scale collaborative modeling and deep learning-based thermal prediction for air-cooled data centers: An innovative insight for thermal management," Applied Energy, Elsevier, vol. 377(PB).
    6. Zhou, Jing & Kanbur, Baris Burak & Le, Duc Van & Tan, Rui & Duan, Fei, 2023. "Multi-criteria assessments of increasing supply air temperature in tropical data center," Energy, Elsevier, vol. 271(C).
    7. Hu, Zhi-Hua & Zheng, Yu-Xin & Wang, You-Gan, 2022. "Packing computing servers into the vessel of an underwater data center considering cooling efficiency," Applied Energy, Elsevier, vol. 314(C).
    8. Huang, Xiaofei & Yan, Junwei & Zhou, Xuan & Yang, Zhixian & Huang, Xiaofeng, 2025. "Energy-efficient optimization method for air conditioning terminal systems in IDC based on genetic algorithm," Energy, Elsevier, vol. 333(C).
    9. Manaserh, Yaman M. & Tradat, Mohammad I. & Bani-Hani, Dana & Alfallah, Aseel & Sammakia, Bahgat G. & Nemati, Kourosh & Seymour, Mark J., 2022. "Machine learning assisted development of IT equipment compact models for data centers energy planning," Applied Energy, Elsevier, vol. 305(C).
    10. Yifan Li & Congzhe Zhu & Xiuming Li & Bin Yang, 2025. "A Review of Non-Uniform Load Distribution and Solutions in Data Centers: Micro-Scale Liquid Cooling and Large-Scale Air Cooling," Energies, MDPI, vol. 18(1), pages 1-22, January.
    11. Cho, Jinkyun & Park, Beungyong & Jang, Seungmin, 2022. "Development of an independent modular air containment system for high-density data centers: Experimental investigation of row-based cooling performance and PUE," Energy, Elsevier, vol. 258(C).
    12. Han, Yibo & Han, Kai & Wang, Yongzhen & Lin, Jiayu & Han, Juntao & Song, Kuo & Tang, Hao & Han, Te, 2025. "Bi-level optimization and sustainability assessment of data center integrated energy system based on emergy theory," Energy, Elsevier, vol. 334(C).
    13. Zhang, Qiaoxin & Tu, Rang & Yang, Xu, 2024. "Optimization operation of data Center's distributed air conditioning system based on supply-demand matching," Energy, Elsevier, vol. 306(C).
    14. Gao, Jiacheng & Lv, Yanlong & Feng, Lejun & Sui, Jun & Jin, Hongguang, 2025. "Model predictive control incorporating data correction for LHTES power controlling: Deployment and case study in data center," Applied Energy, Elsevier, vol. 401(PA).
    15. Wang, Songjie & Xiang, Duo & Zhong, Wei & Lin, Xiaojie & Chen, Shuqin, 2025. "A multi-objective bilevel planning for data center integrated energy systems with waste heat utilization," Energy, Elsevier, vol. 335(C).
    16. Wang, Ningbo & Tian, Bo & Wei, Zuyuan & Guo, Yanhua & Dong, Zijun & Ding, Dekun & Shao, Shuangquan, 2025. "Experimental study of a dual-loop cooling system for data centers: A combined active and passive cooling approach," Energy, Elsevier, vol. 333(C).
    17. Zhang, Ce & Hou, Beiran & Li, Minxia & Dang, Chaobin & Chen, Xun & Li, Xiuming & Han, Zongwei, 2025. "Feasibility analysis of multi-mode data center liquid cooling system integrated with Carnot battery energy storage module," Energy, Elsevier, vol. 320(C).
    18. Xue, Lin & Wang, Jianxue & Li, Haotian & Yong, Weizhen & Zhang, Yao, 2025. "Online energy conservation scheduling for geo-distributed data centers with hybrid data-driven and knowledge-driven approach," Energy, Elsevier, vol. 322(C).
    19. Han, Ouzhu & Ding, Tao & Yang, Miao & Jia, Wenhao & He, Xinran & Ma, Zhoujun, 2024. "A novel 4-level joint optimal dispatch for demand response of data centers with district autonomy realization," Applied Energy, Elsevier, vol. 358(C).
    20. Kong, Rui & Zhang, Hainan & Tang, Mingsheng & Zou, Huiming & Tian, Changqing & Ding, Tao, 2024. "Enhancing data center cooling efficiency and ability: A comprehensive review of direct liquid cooling technologies," Energy, Elsevier, vol. 308(C).

    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:285:y:2023:i:c:s0360544223027640. 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.