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

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  • 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.

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  • 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
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    References listed on IDEAS

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    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. 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).
    5. 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).
    6. 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).
    7. 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).
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    Cited by:

    1. 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.
    2. 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).
    3. 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).

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