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Optimal design of data center cooling systems concerning multi-chiller system configuration and component selection for energy-efficient operation and maximized free-cooling

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  • Cheung, Howard
  • Wang, Shengwei

Abstract

The large data center electricity consumption is a growing global concern. To be environment-friendly and to enhance energy efficiency in operation, data center cooling systems adopt a variety of advanced cooling and renewable energy technologies such as free cooling. However, these free cooling systems are not optimally designed in field practices, and their energy efficiencies are much lower than that of the ideal case. In this study, optimal designs in water piping, pumps and equipment sequencing control are introduced to maximize the cooling efficiency of free cooling systems. It finds that the use of distribution headers around cooling towers and pumps, the maximization of the number of operating cooling towers, the minimization of the number of operating pumps and the mixed use of large and small single-speed pumps can reduce the system's power consumption by 60% under certain operating conditions. The results also show that the designs can reduce the annual energy consumption by 3–15% depending on the climate conditions.

Suggested Citation

  • Cheung, Howard & Wang, Shengwei, 2019. "Optimal design of data center cooling systems concerning multi-chiller system configuration and component selection for energy-efficient operation and maximized free-cooling," Renewable Energy, Elsevier, vol. 143(C), pages 1717-1731.
    • Handle: RePEc:eee:renene:v:143:y:2019:i:c:p:1717-1731
    DOI: 10.1016/j.renene.2019.05.127
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    References listed on IDEAS

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    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. Li, Hangxin & Wang, Shengwei, 2017. "Probabilistic optimal design concerning uncertainties and on-site adaptive commissioning of air-conditioning water pump systems in buildings," Applied Energy, Elsevier, vol. 202(C), pages 53-65.
    3. 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.
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    Cited by:

    1. Borkowski, Mateusz & Piłat, Adam Krzysztof, 2022. "Customized data center cooling system operating at significant outdoor temperature fluctuations," Applied Energy, Elsevier, vol. 306(PB).
    2. Fan, Chengliang & Hinkelman, Kathryn & Fu, Yangyang & Zuo, Wangda & Huang, Sen & Shi, Chengnan & Mamaghani, Nasim & Faulkner, Cary & Zhou, Xiaoqing, 2021. "Open-source Modelica models for the control performance simulation of chiller plants with water-side economizer," Applied Energy, Elsevier, vol. 299(C).
    3. Han, Ouzhu & Ding, Tao & Zhang, Xiaosheng & Mu, Chenggang & He, Xinran & Zhang, Hongji & Jia, Wenhao & Ma, Zhoujun, 2023. "A shared energy storage business model for data center clusters considering renewable energy uncertainties," Renewable Energy, Elsevier, vol. 202(C), pages 1273-1290.

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