Comparison of Deep Reinforcement Learning Algorithms in Data Center Cooling Management: A Case Study

The increasingly ubiquitous nature of computer and internet usage in our society, has driven advances in semiconductor technology, server packaging, and cluster level optimizations, in the IT industry. Not surprisingly this has an impact on our societal infrastructure with respect to providing the requisite energy to fuel these power hungry machines. Cooling has been found to contribute to about a third of the total data center energy consumption, and is the focus of this study. In this paper we develop and present physics based models to allow the prediction of the energy consumption and heat transfer phenomenon in a data center. These models allow the estimation of the microprocessor junction and server inlet air temperatures for different flow and temperature conditions at various parts of the data center cooling infrastructure. For a case study example considered, the chiller energy use was the biggest fraction of about 41% and also the most inefficient. The room air conditioning was the second largest energy component and also the second most inefficient. A sensitivity analysis of plant and chiller energy efficiency with chiller set point temperature and outdoor air conditions is also presented.

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Refrigeration Heat Exchanger Systems for Server Rack Cooling in Data Centers

ASME 2009 InterPACK Conference, Volume 2 ◽

10.1115/interpack2009-89258 ◽

2009 ◽

Cited By ~ 5

Author(s):

Takeshi Tsukamoto ◽

Jyunji Takayoshi ◽

Roger R. Schmidt ◽

Madhusudan K. Iyengar

Keyword(s):

Heat Exchanger ◽

Data Center ◽

Heat Exchangers ◽

Energy Savings ◽

Vapor Compression ◽

Data Center Cooling ◽

Thermal Data ◽

Coolant Loop ◽

Vapor Compression System

In 2005, IBM released a water cooled heat exchanger product that significantly enhanced data center cooling capability while also demonstrating substantial energy savings. In 2008, IBM released an enhanced water less solution to cool the electronic racks via a R410A refrigerant based vapor compression system, which is the focus of this paper. The paper provides a detailed description of device and coolant loop construction, the experimental thermal data collected, as well as a discussion of its’ cooling energy efficiency relative to both typical air cooled facilities and water cooled heat exchangers, respectively. A data center level case study was performed with experimental measurements collected and discussed herein. Significant energy savings were realized even when the heat exchanger devices were implemented on a small part of the data center. Based on the test data and the experimental data center study, the CRAC units based loops have a COP of 1.95, while the refrigerant refrigerant heat exchanger loop has a COP of 5.0.

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Analytical Modeling for Thermodynamic Characterization of Data Center Cooling Systems

Journal of Electronic Packaging ◽

10.1115/1.3103952 ◽

2009 ◽

Vol 131 (2) ◽

Cited By ~ 33

Author(s):

Madhusudan Iyengar ◽

Roger Schmidt

Keyword(s):

Energy Consumption ◽

Data Center ◽

Energy Use ◽

It Industry ◽

Air Temperatures ◽

Data Center Cooling ◽

Total Data ◽

Heat Transfer Phenomenon

The increasingly ubiquitous nature of computer and internet usage in our society has driven advances in semiconductor technology, server packaging, and cluster level optimizations in the IT industry. Not surprisingly this has an impact on our societal infrastructure with respect to providing the requisite energy to fuel these power hungry machines. Cooling has been found to contribute about a third of the total data center energy consumption and is the focus of this study. In this paper we develop and present physics based models to allow the prediction of the energy consumption and heat transfer phenomenon in a data center. These models allow the estimation of the microprocessor junction and server inlet air temperatures for different flows and temperature conditions at various parts of the data center cooling infrastructure. For the case study example considered, the chiller energy use was the biggest fraction of about 41% and was also the most inefficient. The room air conditioning was the second largest energy component and was also the second most inefficient. A sensitivity analysis of plant and chiller energy efficiencies with chiller set point temperature and outdoor air conditions is also presented.

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Data Center Cooling Efficiency With Simulation-Based Optimization

Volume 1: Thermal Management ◽

10.1115/ipack2015-48425 ◽

2015 ◽

Cited By ~ 1

Author(s):

Laurent M. Billet ◽

Christopher M. Healey ◽

James W. VanGilder ◽

Zachary M. Pardey

Keyword(s):

Energy Consumption ◽

Data Center ◽

Data Centers ◽

Real Life ◽

Economic Importance ◽

Cooling Efficiency ◽

Simulation Based ◽

Data Center Cooling ◽

Efficient Control

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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