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

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 mod...

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Bibliographic Details
Published in:Neural computing & applications 2022-04, Vol.34 (7), p.5225-5240
Main Authors: Fang, Qiu, Zhou, Jiakang, Wang, Shi, Wang, Yaonan
Format: Article
Language:English
Subjects:
Air conditioners
Air flow
Air temperature
Artificial Intelligence
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Constraints
Cooling
Cooling systems
Data centers
Data Mining and Knowledge Discovery
Flow velocity
Image Processing and Computer Vision
Optimization
Power consumption
Probability and Statistics in Computer Science
S.I.: Computational Intelligence-based Control and Estimation in Mechatronic Systems
Special Issue on Computational Intelligence-based Control and Estimation in Mechatronic Systems
Thermal management
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Summary: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.
ISSN:0941-0643
1433-3058
DOI:10.1007/s00521-021-06385-w