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.

1.
J. G.
Kooney
, 2007, “
Estimating Total Power Consumption by Servers in the US and the World
,” Lawrence Berkeley National Laboratory, http://enterprise.amd.com/Downloads/svrpwrusecompletefinal.pdfhttp://enterprise.amd.com/Downloads/svrpwrusecompletefinal.pdf.
2.
Green Grid Industry Consortium
, 2007, “
Green Grid Metrics–Describing Data Center Power Efficiency
,” Technical Committee White Paper, http://www.thegreengrid.org/~/media/WhitePapers/Green_Grid_Metrics_WP.ashx?lang=enhttp://www.thegreengrid.org/~/media/WhitePapers/Green_Grid_Metrics_WP.ashx?lang=en.
3.
2006, “
HP Unveils Automated Cooling System for Data Centers
,” Information Week, Nov. 29.
4.
ASHRAE Publication, 2005, “
Datacom Equipment Power Trends and Cooling Applications
.”
5.
Schmidt
,
R.
, 2004, “
Thermal Profile of a High Density Data Center—Methodology to Thermally Characterize a Data Center
,”
ASHRAE Summer Meeting, Symposium NA-04
, Nashville, TN, Jun., Paper No. NA-04-4-2.
6.
Schmidt
,
R.
,
Iyengar
,
M.
,
Beaty
,
D.
, and
Shrivastava
,
S.
, 2005, “
Thermal Profile of a High Density Data Center—Hot Spot Heat Fluxes of 512 W/ft2
,”
Proceedings of the ASHRAE Annual Meeting, Symposium DE-05-11
, Denver, CO, Jun. 25–29.
7.
Schmidt
,
R.
,
Iyengar
,
M.
, and
Mayhugh
,
S.
, 2006, “
Thermal Profile of World's 3rd Fastest Supercomputer-IBM’s ASCI Purple Cluster-
,”
Proceedings of the ASHRAE Summer Meeting, Symposium DE-05-11
, Quebec City, Canada, Jun., Paper No. QC-03-019.
8.
Tschudi
,
W.
, 2006, “
Best Practices Identified Through Benchmarking Data Centers
,”
Presentation at the ASHRAE Summer Conference
, Quebec City, Canada, Jun.
9.
Pacific Gas and Electric Company Report, 2006, “
High Performance Data Centers—A Design Guidelines Sourcebook
,” Developed by Rumsey Engineers and Lawrence Berkeley National Laboratory, http://hightech.lbl.gov/documents/DATA_CENTERS/06_DataCenters-PGE.pdfhttp://hightech.lbl.gov/documents/DATA_CENTERS/06_DataCenters-PGE.pdf.
10.
Gordon
,
J. M.
, and
Ng
,
K. C.
, 1995, “
Predictive and Diagnostic Aspect of a Universal Thermodynamic Model for Chillers
,”
Int. J. Heat Mass Transfer
0017-9310,
38
(
5
), pp.
807
818
.
11.
Jiang
,
W.
, and
Reddy
,
T. A.
, 2003, “
Reevaluation of the Gordon-Ng Performance Models for Water-Cooled Chillers
,”
Proceedings of the ASHRAE Annual Meeting
, Vol.
109
, Part 2, Kansas City, MO, pp.
272
287
.
12.
Bourdouxhe
,
J.
,
Grodeni
,
M.
,
Lebrun
,
J. J.
,
Saavedra
,
C.
, and
Silva
,
K.
, 1994, “
A Toolkit for Primary HVAC System Energy Calculations—Part2: Reciprocating Chiller Models
,”
Proceedings of the ASHRAE Annual Meeting
, Vol.
100
, Orlando, FL, Paper No. OR-94-9-2 (RP-665), pp.
774
786
.
13.
Sreedharan
,
P.
, 2001, “
Evaluation of Chiller Modeling Approaches And Their Usability For Fault Detection
,” Masters Project at the University of California at Berkeley, Department of Mechanical Engineering, http://repositories.cdlib.org/lbnl/LBNL-48856/http://repositories.cdlib.org/lbnl/LBNL-48856/.
14.
Stout
,
M. R.
, Jr.
, 2002, “
Cooling Tower Fan Control for Energy Efficiency
,”
Energ. Eng.
0199-8595,
99
(
1
), pp.
7
31
.
15.
Incropera
,
F. P.
, and
DeWitt
,
D. P.
,1990,
Introduction to Heat Transfer
,
2nd ed.
,
Wiley
,
New York
.
16.
Iyengar
,
M.
, and
Schmidt
,
R.
, 2006, “
Analytical Modeling for Prediction of Hot Spot Chip Junction Temperature for Electronics Cooling Applications
,”
Proceedings of the Inter Society Conference on Thermal Phenomena (ITherm)
, San Diego, May–Jun.
17.
Schmidt
,
R.
,
Iyengar
,
M.
, and
Chu
,
R.
, 2005, “
Data Centers—Meeting Data Center Temperature Requirements
,”
ASHRAE J.
0001-2491,
47
(
4
), pp.
44
49
.
18.
Schmidt
,
R.
,
Cruz
,
E.
, and
Iyengar
,
M.
, 2005, “
Challenges of Data Center Thermal Management
,”
IBM J. Res. Dev.
0018-8646,
49
(
4/5
), pp.
709
723
.
19.
Schmidt
,
R.
, and
Iyengar
,
M.
, 2006, “
Comparison Between Under Floor Supply and Overhead Supply Data Center Ventilation Designs for High Density Clusters
,”
Proceedings of the ASHRAE Winter Meeting, Symposium DA-07
, Chicago, IL, Paper No. DA-07-013.
20.
Schmidt
,
R.
, and
Iyengar
,
M.
, 2005, “
Effect of Data Center Layouts on Rack Inlet Temperatures
,”
Proceedings of the Pacific Rim/ASME International Electronic Packaging Technical Conference (InterPack)
, San Francisco, CA, Jul. 17–22, Paper No. IPACK2005-73385.
You do not currently have access to this content.