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Performance Analysis of Lake Water Cooling Coupled with a Waste Heat Recovery System in the Data Center

Author

Listed:
  • Peng Yin

    (Jiangsu Communications Services Co., Ltd., Nanjing 210006, China)

  • Yang Guo

    (School of Energy Science and Engineering, Central South University, Changsha 410083, China)

  • Man Zhang

    (School of Energy Science and Engineering, Central South University, Changsha 410083, China)

  • Jiaqiang Wang

    (School of Energy Science and Engineering, Central South University, Changsha 410083, China)

  • Linfeng Zhang

    (School of Transportation, Southeast University, Nanjing 211189, China)

  • Da Feng

    (China Telecom Corporation Limited Suzhou Branch, Suzhou 215025, China)

  • Weike Ding

    (China Information Consulting & Designing Institute Co., Ltd., Nanjing 210019, China)

Abstract

Data centers (DCs) require continuous cooling throughout the year and produce a large amount of low-grade waste heat. Free cooling and waste heat recovery techniques are promising approaches to reduce DC energy consumption. Although previous studies have explored diverse waste heat utilization strategies, there is a significant gap in combining waste heat recovery with lake water cooling in DCs. Therefore, this study proposed a system integrating lake water cooling with waste heat recovery for DCs. To evaluate the energy-saving performance of the suggested system, the influence of waste heat recovery locations and volumes has been investigated. An analysis of the improvement in system parameters is also conducted. The study’s findings highlight that targeted recovery of waste heat from sources like chilled water or air in server rooms can significantly reduce the cooling energy demand of the system. The results show that recovering heat from the return air of IT equipment can yield a remarkable power usage effectiveness (PUE) and coefficient of performance (COP) of 1.19 and 10.17, and the energy consumption of the cooling system is reduced to 10.06%. Moreover, the outcomes reveal the potential for substantial energy savings of up to 26.05% within the proposed system by setting the chilled water and air supply temperatures to 16 and 20 °C, respectively.

Suggested Citation

  • Peng Yin & Yang Guo & Man Zhang & Jiaqiang Wang & Linfeng Zhang & Da Feng & Weike Ding, 2024. "Performance Analysis of Lake Water Cooling Coupled with a Waste Heat Recovery System in the Data Center," Sustainability, MDPI, vol. 16(15), pages 1-21, July.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:15:p:6542-:d:1446666
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    References listed on IDEAS

    as
    1. 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).
    2. Huang, Pei & Copertaro, Benedetta & Zhang, Xingxing & Shen, Jingchun & Löfgren, Isabelle & Rönnelid, Mats & Fahlen, Jan & Andersson, Dan & Svanfeldt, Mikael, 2020. "A review of data centers as prosumers in district energy systems: Renewable energy integration and waste heat reuse for district heating," Applied Energy, Elsevier, vol. 258(C).
    3. Wahlroos, Mikko & Pärssinen, Matti & Manner, Jukka & Syri, Sanna, 2017. "Utilizing data center waste heat in district heating – Impacts on energy efficiency and prospects for low-temperature district heating networks," Energy, Elsevier, vol. 140(P1), pages 1228-1238.
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