Research Papers

Thermal Control Strategies for Reliable and Energy-Efficient Data Centers

[+] Author and Article Information
Rehan Khalid

Department of Mechanical Engineering,
Villanova University,
800 Lancaster Avenue,
Villanova, PA 19085
e-mail: rkhalid@villanova.edu

Aaron P. Wemhoff

Department of Mechanical Engineering,
Villanova University,
800 Lancaster Avenue,
Villanova, PA 19085

1Corresponding author.

Contributed by the Electronic and Photonic Packaging Division of ASME for publication in the JOURNAL OF ELECTRONIC PACKAGING. Manuscript received July 13, 2018; final manuscript received June 18, 2019; published online July 12, 2019. Assoc. Editor: Baris Dogruoz.

J. Electron. Packag 141(4), 041004 (Jul 12, 2019) (12 pages) Paper No: EP-18-1058; doi: 10.1115/1.4044129 History: Received July 13, 2018; Revised June 18, 2019

Two self-developed control schemes, ON/OFF and supervisory control and data acquisition (SCADA), were applied on a hybrid evaporative and direct expansion (DX)-based model data center cooling system to assess the impact of controls on reliability and energy efficiency. These control schemes can be applied independently or collectively, thereby saving the energy spent on mechanical refrigeration by using airside economization and/or evaporative cooling. Various combinations of system-level controls and component-level controls are compared to a baseline no-controls case. The results show that reliability is consistently met by employing only sophisticated component-level controls. However, the recommended conditions are met approximately 50% of the simulated time by employing system-level controls only (i.e., SCADA) but with a reduction in data center cooling system power usage effectiveness (PUE) values from 3.76 to 1.42. Moreover, the recommended conditions are met at all averaged times with an even lower cooling system PUE of 1.13 by combining system-level controls only (SCADA and ON/OFF controls). Thus, the study introduces a simple method to compare control schemes for reliable and energy-efficient data center operation. The work also highlights a potential source of capital expenses and operating expenses savings for data center owners by switching from expensive built-in component-based controls to inexpensive, yet effective, system-based controls that can easily be imbedded into existing data center infrastructure systems management.

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Shehabi, A. , Smith, S. , Sartor, D. , Brown, R. , Herrlin, M. , Koomey, J. , Masanet, E. , Horner, N. , Azevedo, I. , and Lintner, W. , 2016, “ United States Data Center Energy Usage Report,” Lawrence Berkeley National Laboratory, Berkeley, CA, Report No. LBNL-1005775. https://eta.lbl.gov/publications/united-states-data-center-energy
Alissa, H. A. , 2015, “ Innovative Approaches of Experimentally Guided CFD Modeling for Data Centers,” 31st Thermal Measurement, Modeling & Management Symposium (SEMI-THERM), San Jose, CA, Mar. 15–19, pp. 176–184.
Iyengar, M. , Schmidt, R. R. , Hamann, H. , and VanGilder, J. , 2007, “ Comparison Between Numerical and Experimental Temperature Distributions in a Small Data Center Test Cell,” ASME Paper No. IPACK2007-33508.
Iyengar, M. , and Schmidt, R. R. , 2009, “ Analytical Modeling for Thermodynamic Characterization of Data Center Cooling Systems,” ASME, J. Electron. Packag., 131(2), p. 021009. [CrossRef]
Tsuda, A. , Mino, Y. , and Nishimura, S. , 2017, “ Comparison of ICT Equipment Air-Intake Temperatures Between Cold Aisle Containment and Hot Aisle Containment in Datacenters,” IEEE International Telecommunications Energy Conference (INTELEC), Broadbeach, QLD, Australia, Oct. 22–26, pp. 59–65.
ASHRAE, 2010, “Save Energy Now Presentation Series,” ASHRAE Technical Committee 9.9, Dallas, TX.
Durand-Estabe, B. , Le Bot, C. , Mancos, J. N. , and Arquis, E. , 2014, “ Simulation of a Temperature Adaptive Control Strategy for an IWSE Economizer in a Data Center,” Appl. Energy, 134, pp. 45–56. [CrossRef]
Jonge, D. B. , 2017, “ Trial and Application of Direct Evaporative Cooling at Telstra's Information and Communication Technology Centers,” IEEE International Telecommunications Energy Conference (INTELEC), Broadbeach, QLD, Australia, Oct. 22–26, pp. 66–70.
Parolini, L. , Sinopoli, B. , Krogh, B. H. , and Wang, Z. , 2012, “ A Cyber-Physical Systems Approach to Data Center Modeling and Control for Energy Efficiency,” Proc. IEEE, 100(1), pp. 254–268. [CrossRef]
Xu, H. G. , He, J. P. , and Li, Y. Q. , 2012, “ Energy Management and Control Strategy for DC Micro-Grid in Data Center,” IEEE Fifth International Conference on Electricity Distribution, Shanghai, China, Sept. 5–6, pp. 1–6.
Fulpagre, Y. , and Bhargav, A. , 2015, “ Advances in Data Center Thermal Management,” Renewable Sustainable Energy Rev., 43, pp. 981–996. [CrossRef]
Boucher, T. D. , Auslander, D. M. , Bash, C. E. , Federspiel, C. C. , and Patel, C. D. , 2006, “ Viability of Dynamic Cooling Control in a Data Center Environment,” ASME J. Electron. Packag., 128(2), pp. 137–144. [CrossRef]
Lin, M. , Shao, S. , Zhang, X. , VanGilder, J. W. , Avelar, V. , and Hu, X. , 2014, “ Strategies for Data Center Temperature Control During a Cooling System Outage,” Energy Build., 73, pp. 146–152. [CrossRef]
Chen, J. , Tan, R. , Xing, G. , and Wang, X. , 2014, “ PTEC: A System for Predictive Thermal and Energy Control in Data Centers,” IEEE Real-Time Systems Symposium, Rome, Italy, Dec. 2–5, pp. 218–227.
Walsh, E. J. , Breen, T. J. , Punch, J. , Shah, A. J. , and Bash, C. E. , 2011, “ From Chip to Cooling Tower Data Center Modeling: Influence of Chip Temperature Control Philosophy,” ASME J. Electron. Packag., 133(3), p. 031008. [CrossRef]
Shah, A. J. , Carey, V. P. , Bash, C. E. , and Patel, C. D. , 2004, “ An Exergy-Based Control Strategy for Computer Room Air-Conditioning Units in Data Centers,” ASME Paper No. IMECE2004-61384.
Mohsenian, G. , Khalili, S. , and Sammakia, B. , 2019, “ A Design Methodology for Controlling Local Airflow Delivery in Data Centers Using Air Dampers,” IEEE ITherm Conference, Las Vegas, NV, May 28–31, p. 431.
VanGilder, J. , Zhang, Y. , Linder, S. , and Condor, M. , 2019, “ Balancing Cooling and IT Airflow With Dampers in Ceiling-Ducted Hot-Aisle Containment in Data Centers,” IEEE ITherm Conference, Las Vegas, NV, May 28–31, p. 142.
Baxendale, M. , Athavale, J. , Robertson, S. , and Joshi, Y. , 2019, “ Data Center Temperature Control Using PI System and MATLAB,” IEEE ITherm Conference, Las Vegas, NV, May 28–31, Paper No. 397.
Wemhoff, A. P. , del Valle, M. , Abbasi, K. , and Ortega, A. , 2013, “ Thermodynamic Modeling of Data Center Cooling Systems,” ASME Paper No. IPACK2013-73116.
Steinbrecher, R. A. , and Schmidt, R. , 2011, “ Data Center Environments ASHRAE's Evolving Thermal Guidelines,” ASHRAE J., 53(12), pp. 42–49.
Warke, D. A. , and Deshmukh, S. J. , 2017, “ Experimental Analysis of Cellulose Cooling Pads Used in Evaporative Coolers,” Int. J. Energy Sci. Eng., 3(4), pp. 37–43. http://files.aiscience.org/journal/article/pdf/70180051.pdf
Joshi, Y. , and Kumar, P. , 2012, Energy Efficient Thermal Management of Data Centers, 1st ed., Springer, New York, p. 111.
Incropera, F. P. , DeWitt, D. , Bergman, T. , and Lavine, A. , 2007, Fundamentals of Heat and Mass Transfer, 6th ed., Wiley, Hoboken, NJ, p. 689.
Bhalerao, A. , Fouladi, K. , Silva-Llanca, L. , and Wemhoff, A. P. , 2016, “ Rapid Predictions of Exergy Destruction in Data Centers Due to Airflow Mixing,” Numer. Heat Transfer, Part A: Appl., 70(1), pp. 48–63. [CrossRef]
Grote, K.-H. , and Antonsson, E. , 2009, “ Damper Applications Guide,” Handbook of Mechanical Engineering Part B: Applications, Springer, Berlin.
Engineered Software Inc., 2017, “Modeling a Damper,” Modeling Piping System Devices, Engineered Software Inc., accessed July 5, 2019, http://kb.eng-software.com/display/ESKB/Modeling+a+Damper
Crane Co. Staff, 2009, Flow of Fluids Through Valves, Fittings and Pipe [Paper No. 410], Crane Company, Stamford, CT, Chap. 6.
Wilcox, S., 2007, “Typical Meteorological Year Weather Database,” National Renewable Energy Laboratory, Division of Department of Energy, Golden, CO, Sponsored Under Contract No. DE-AC36-08GO28308, accessed July 5, 2019, http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2005/tmy3/
Brown, K. , Torell, W. , and Avelar, V. , 2014, “ Choosing the Optimal Data Center Power Density,” Schneider White, Boston, MA, p. 2.
Ibrahim, M. , Shrivastava, S. , Sammakia, B. , and Ghose, K. , 2012, “ Thermal Mass Characterization of a Server at Different Fan Speeds,” 13th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITHERM), San Diego, CA, May 30–June 1, pp. 457–455.
Pardey, Z. M. , Demetriou, D. W. , Erden, H. S. , VanGilder, J. W. , Khalifa, H. E. , and Schmidt, R. R. , 2015, “ Proposal for Standard Compact Server Model for Transient Data Center Simulations,” ASHRAE Trans., 121(1), pp. 413–421. https://experts.syr.edu/en/publications/proposal-for-standard-compact-server-model-for-transient-data-cen
Belady, C. , Kelkar, K. M. , and Patankar, S. V. , 1995, “ Improved Productivity With Use of Flow Network Modeling (FNM) in Electronic Packaging,” Electron. Cooling, 5(1), pp. 36–40. http://inresllc.com/assets/files/macroflow/MF01-Elec-Cooling-Paper.pdf
Wemhoff, A. P. , and Frank, A. , 2010, “ Predictions of Energy Savings in HVAC Systems by Lumped Models,” J. Energy Build., 42(10), pp. 1807–1814. [CrossRef]
Fried, E. , and Idelchik, I. E. , 1989, Flow Resistance: A Design Guide for Engineers, 1st ed., Taylor & Francis, New York.
Faul, A. C. , 2016, A Concise Introduction to Numerical Analysis, CRC Press, Boca Raton, FL.
White, F. , 2001, Fluid Mechanics, 7th ed., McGraw-Hill, New York, p. 769.


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Fig. 1

Schematic of chosen data center cooling system. Adapted from Ref. [23].

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Fig. 2

Virtual controls test bed used in this study

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Fig. 3

Psychrometric chart showing working methodology for both CRAC models

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Fig. 4

(a) VTAS controller architecture in steady-state mode and (b) VTAS controller architecture in transient mode

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Fig. 5

Flowchart for SCADA database creation

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Fig. 6

ON/OFF controller logic. “db” represents controller deadband.

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Fig. 7

Variation of external temperature and relative humidity for July 23rd in Dallas–Fort Worth

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Fig. 8

Comparison of time spent in each ASHRAE range for each control scheme

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Fig. 9

Comparison of average cooling system PUE for each control scheme

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Fig. 10

Panduit test bed for VTAS validation

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Fig. 11

Optimization of all three variables using regression and random sampling for external conditions of 20 °C and 40% relative humidity



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