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Control-oriented modeling and optimization for the temperature and airflow management in an air-cooled data-center

  • S.I.: Computational Intelligence-based Control and Estimation in Mechatronic Systems
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Abstract

This paper presents a method for minimizing the power consumption of a data-center cooling system by optimizing the airflow pattern and the supplied cold air temperature simultaneously. To discover the potential benefits of reorganizing the rack flow rates, a gray-box fast-temperature evaluation model is proposed for the first time, which reflects the thermal relationship among the components of the data center and has low computational complexity. Next, a model-based constrained nonlinear optimization problem is formulated with the aim of minimizing the power consumption of both cooling fans and air conditioners. Meanwhile, the safety thermal guidelines are considered as the main constraints. At last, the optimal settings of rack airflow rates and supplied cold air temperature are obtained by solving the optimization problems. The simulation results show that the proposed method can yield an effective thermal management tool and reduce significant cooling power for air-cooled data centers.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China under Grant No. 61903134 and by the Natural Science Foundation of Hunan Province 2020JJ5086.

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Authors and Affiliations

  1. National Engineering Laboratory for Robot Visual Perception and Control Technology, Hunan University, Changsha, 410082, People’s Republic of China

    Qiu Fang, Jiakang Zhou, Shi Wang & Yaonan Wang

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  1. Qiu Fang
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  2. Jiakang Zhou
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  3. Shi Wang
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  4. Yaonan Wang
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Correspondence to Shi Wang.

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Fang, Q., Zhou, J., Wang, S. et al. Control-oriented modeling and optimization for the temperature and airflow management in an air-cooled data-center. Neural Comput & Applic 34, 5225–5240 (2022). https://doi.org/10.1007/s00521-021-06385-w

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