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The Numerical Simulation of the Airflow Distribution and Energy Efficiency in Data Centers with Three Types of Aisle Layout

Author

Listed:
  • Jing Ni

    (Department of Information Management and Information System, Beijing Institute of Petrochemical Technology, Beijing 102617, China)

  • Bowen Jin

    (College of Liberal Arts, University of Minnesota Twin Cities, Minneapolis, MN 55455, USA
    College of Science, Univerisity of Idaho, Moscow, ID 83844, USA)

  • Shanglei Ning

    (Beijing Key Laboratory of Fuels Cleaning and Advanced Catalytic Emission Reduction Technology, College of Chemical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China)

  • Xiaowei Wang

    (Department of Information Management and Information System, Beijing Institute of Petrochemical Technology, Beijing 102617, China)

Abstract

The energy consumption of fast-growing data centers is drawing attentions from not only energy organizations and institutions all over the world, but also charity groups, such as Greenpeace, and research shows that the power consumption of air conditioning makes up a large proportion of the electricity cost in data centers. Therefore, more detailed investigations of air conditioning power consumption are warranted. Three types of airflow distributions with different aisle layouts (the open aisle, the closed cold aisle, and the closed hot aisle) were investigated with Computational Fluid Dynamics (CFD) methods in a typical data center of four rows of racks in this study. To evaluate the results of thermal and bypass phenomenon, the temperature increase index (β) and the energy utilization index (η r ) were used. The simulations show that there is a better trend of the β index and η r index both closed cold aisle and closed hot aisle compared with free open aisle. Especially with high air flow rate, the β index decreases and the η r index increases considerably. Moreover, the results prove the closed aisles (both closed cold aisle and closed hot aisle) can not only significantly improve the airflow distribution, but also reduce the mixture of cold and heat flow, and therefore improve energy efficiency. In addition, it proves the design of the closed aisles can meet the increasing density of installations and our simulation method could evaluate the cooling capacity easily.

Suggested Citation

  • Jing Ni & Bowen Jin & Shanglei Ning & Xiaowei Wang, 2019. "The Numerical Simulation of the Airflow Distribution and Energy Efficiency in Data Centers with Three Types of Aisle Layout," Sustainability, MDPI, vol. 11(18), pages 1-13, September.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:18:p:4937-:d:265837
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    References listed on IDEAS

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    1. Rong, Huigui & Zhang, Haomin & Xiao, Sheng & Li, Canbing & Hu, Chunhua, 2016. "Optimizing energy consumption for data centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 674-691.
    2. Ni, Jiacheng & Bai, Xuelian, 2017. "A review of air conditioning energy performance in data centers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 625-640.
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