DATA CENTER COOLING EFFICIENCY

The efficient control of cooling for data centers is an issue of broad economic importance due to the significant energy consumption of data centers. Many solutions attempt to optimize the control of the cooling equipment with temperature, pressure, or airflow sensors. We propose a simulation-based approach to optimize the cooling energy consumption and show how this approach can be implemented with simple power-consumption models. We also provide a real-life case study to demonstrate how energy saving cooling setpoints can be found using calibrated simulations and smooth metamodels of the system.

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Failure Resistant Data Center Cooling Control Through Model-Based Thermal Zone Mapping

Volume 2: Heat Transfer Enhancement for Practical Applications; Fire and Combustion; Multi-Phase Systems; Heat Transfer in Electronic Equipment; Low Temperature Heat Transfer; Computational Heat Transfer ◽

10.1115/ht2012-58403 ◽

2012 ◽

Cited By ~ 6

Author(s):

Rongliang Zhou ◽

Zhikui Wang ◽

Cullen E. Bash ◽

Tahir Cader ◽

Alan McReynolds

Keyword(s):

Data Center ◽

Data Centers ◽

Cooling System ◽

Cooling Power ◽

Cooling Efficiency ◽

Model Based ◽

Thermal Zone ◽

Cooling Control ◽

Data Center Cooling ◽

Thermal Status

Due to the tremendous cooling costs, data center cooling efficiency improvement has been actively pursued for years. In addition to cooling efficiency, the reliability of the cooling system is also essential for guaranteed uptime. In traditional data center cooling system design with N+1 or higher redundancy, all the computer room air conditioning (CRAC) units are either constantly online or cycled according to a predefined schedule. Both cooling system configurations, however, have their respective drawbacks. Data centers are usually over provisioned when all CRAC units are online all the time, and hence the cooling efficiency is low. On the other hand, although cooling efficiency can be improved by cycling CRAC units and turning off the backups, it is difficult to schedule the cycling such that sufficient cooling provisioning is guaranteed and gross over provisioning is avoided. In this paper, we aim to maintain the data center cooling redundancy while achieving high cooling efficiency. Using model-based thermal zone mapping, we first partition data centers to achieve the desired level of cooling influence redundancy. We then design a distributed controller for each of the CRAC units to regulate the thermal status within its zone of influence. The distributed controllers coordinate with each other to achieve the desired data center thermal status using the least cooling power. When CRAC units or their associated controllers fail, racks in the affected thermal zones are still within the control “radius” of other decentralized cooling controllers through predefined thermal zone overlap, and hence their thermal status is properly managed by the active CRAC units and controllers. Using this failure resistant data center cooling control approach, both cooling efficiency and robustness are achieved simultaneously. A higher flexibility in cooling system maintenance is also expected, since the distributed control system can automatically adapt to the new cooling facility configuration incurred by maintenance.

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