IT Aire data center cooling system evaluation & Results

Energy Efficiency Center & Industrial Sustainability LaboratorySchool of Mechanical, Industrial, and Manufacturing Engineering

IT AIRE DATA CENTER COOLING SYSTEM EVALUATION &RESULTS

Babak Lajevardi, Ph.D. CandidateJoseph F. Junker, P.E.Karl R. Haapala, Ph.D.

Project Milestone MeetingCity of Gresham, OregonMay 30, 2014


Project Objective and Timeline

Objective: To compare the energy efficiency and performance of City of Gresham data center before and post installation of IT Aire cooling system.

Timeline Summer 2013: Monitoring system

implementation Fall 2013-Spring 2014: Monitoring of cooling

systems Winter 2014-Spring 2014: Analysis of results Spring 2014: Technical article and white paper

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3

Data Center Energy Consumption

Worldwide data center energy use [EPA, 2010] About 240 billion kWh annually Roughly 1.3% of the world total

U.S. data center energy use [EPA, 2010] About 80 billion kWh annually Roughly 2% of the U.S. total


Data Center Energy Consumption4

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

0

50

100

150

200

250

300US Datacenters

Wordwide Dat-acenters

Year

Tota

l ene

rgy

use

(kW

h)


Strategies for Data Center Energy Reduction

Technology development and implementation Optimized rack layout Hot aisle-cold aisle containment New cooling system equipment solutions

Energy and thermal measurement and monitoring Allows evaluation of energy efficiency

performance Gives insight to thermal management

inefficiencies Gives insight into strategic investment for

cost reduction

5


Data Center Air Flow6

Q, T, RH (intake)

Q, T, RH (supply)

Q, T, RH (return)

Cold AisleHot Aisle

IT Rack

Partition

Q, T, RH (exit)


7

Data Center Monitoring

Gresham City Hall wireless monitoring network Dry bulb temperature Relative humidity (RH) Current transducers

Data loggers Record with interval

of one minute Save a copy to an OSU

FTP address every 24 hours

Return air

Supply air/Rack intake air

Hot aisle

Cold aisle

Rack exit air

Rack powerRack power

Data room

Roof

AC unitRack

Node

AC unit powerOutdoor air

Receiver


Outdoor Temperature8

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

202530354045505560

Out

door

Tem

pera

ture

(°F)

IT Aire System Week avg. 42.07°F

Week st. dev. 4.61°F

Old SystemWeek avg. 41.55°F

Week st. dev. 3.86°F


Outdoor Relative Humidity9

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

020406080

100

Out

door

Rel

ativ

e H

umid

ity

(%)

IT Aires System Week avg. 77.58%

Week st. dev. 8.45%

Old SystemWeek avg. 78.21%

Week st. dev. 7.42%


Current Data Center Efficiency Metrics

Power Usage Effectiveness (PUE) [The Green Grid, 2007]

10

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

1

1.5

2

2.5

3Uptime Institute

EPA

Digital Reality Trust

Lawrence Berkeley National Laboratory

PUE

Trendline


Power Use Effectiveness (PUE)11

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

1

1.1

1.2

1.3

1.4

1.5

1.26

1.25

1.24

1.24

1.251.26

1.26

1.011.02 1.05

1.06

1.07 1.07

1.06

PU

E

Old SystemWeek avg. 1.25Week st. dev. 0.06

IT Aire SystemWeek avg. 1.05Week st. dev. 0.03


PUE as a Function of Wet Bulb Temperature12

31-35 36-40 41-45 46-50 51-55 56-60 61-65 66-701.00

1.10

1.20

1.30

1.40

1.50

1.25 1.26 1.25 1.241.29

1.33 1.341.39

1.05 1.05 1.05 1.011.08

1.14 1.17 1.19

Old systemITAire

Wet Bulb Temperature (°F)

PU

E



Dry Bulb Temperature °F

Wet

Bulb Te

mperat

ure °F

Hum

idity

Rat

io (P

ound

s of

m

oist

ure/

Pou

nds

of d

ry a

ir)

IT Aire: 1.0-1.1Old System: 1.2-1.3


ASHRAE Envelope


14


Rack Cooling Index (RCI) [M. K. Herrlin, 2005]

ASHRAE Guideline [ASHRAE, 2011] Recommended: 64°F < Tintake< 77°F Allowable: 59°F < Tintake< 90°F


Rack Cooling Index (ASHRAE Guideline)15

0 2000 4000 6000 8000 1000040

50

60

70

80

90

100 ITAire System

Rack Intake Number

Inta

ke T

empe

ratu

re (°

F)

Recommended

Allowable

Old SystemRCIHI=100%RCILO=92.5%

IT AireRCIHI=100%RCILO=100%


Data Center Air Flow16

Q, T, RH (intake)

Q, T, RH (supply)

Q, T, RH (return)

Cold AisleHot Aisle

Q, T, RH (exit)

Air bypass

Air recirculation


17


Return Temperature Index (RTI) [Herrlin, 2007]

Supply and Return Heat Indices (SHI, RHI) [Sharma and Bash, 2002]


Return Temperature Index (RTI)18

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

80%

90%

100%

110%

120%

RTI

Old SystemWeek avg. dev. 63%

IT Aire SystemWeek avg. dev. 35%


Supply Heat Index (SHI)19

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

0

0.2

0.4

0.6

0.8

1Old System IT Aire

SH

I

Lower SHI, Less recirculation


Return Heat Index (RHI)20

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

0

0.2

0.4

0.6

0.8

1

Old System IT AireRH

I

Higher RHI, Less by pass air


Cooling Energy (IT Aire vs. Old System)21

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

0

20

40

60

80

100

22.3 18.6 20.6 22.923.6 23.220.0

91.586.6 85.485.2 87.892.0 93.3

IT Aire Old

Ene

rgy

(kW

h)

Week avg. 41.55°FWeek stdev. 4.63°F

Average energy saving of 67.2 kWh


Cooling Energy Reduction (IT Aire vs. Old System)22

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

Sunday

Monday

Tuesday

Wednesday

Thursday

Friday

Saturday

0%

20%

40%

60%

80%

100%

75.6%

78.6%

75.9%73.1%

73.3%

74.8%

78.6%

Coo

ling

Sys

tem

Ene

rgy

Red

uctio

n Week avg. 41.55°FWeek stdev. 4.63°F

Average energy reduction of 75.7%


Next Steps

Continued system monitoring (Until Spring 15) Elucidate seasonal variation effects Large data repository for higher resolution of PUE

prediction Enables statistical models for efficiency improvements Provides in-depth insights into performance

Upcoming milestones Presentation at IIE ISERC, May 31-June 4, 2014 Presentation at SME NAMRC, June 9-13, 2014 Whitepaper, June 30, 2014 (draft mid-June for review)

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Dry Bulb Temperature °F

Wet

Bulb Te

mperat

ure °F

Hum

idity

Rat

io (P

ound

s of

m

oist

ure/

Pou

nds

of d

ry a

ir)



ASHRAE Envelope

We gratefully acknowledge the funding support of this project from Portland Development Commission (PDC), Oregon Best, and Energy Trust through Oregon Best Commercialization Program. We wish to express our appreciation from the assistance we received from the City of Gresham and IT Aire.

Acknowledgments25


References

R. Sharma, C. Bash, and C. Patel, “Dimensionless Parameters for Evaluation of Thermal Design and Performance of Large-scale Data Centers,” in 8th AIAA/ASME Joint Thermophysics and Heat Transfer Conference, 2002, pp. 1–11.

R. Brown, “United States Environmental Protection Agency Energy Star Program, Report to congress on server and data center energy efficiency, public law, 109-431,” 2008.

Y. Joshi and P. Kumar, Energy efficient thermal management of data centers. Springer, 2012. “The green grids opportunity: decreasing data center and other IT energy usage patterns,” The Green

Grids, Technical Report, 2007. L. Stahl and C. Belady, “Designing an alternative to conventional room cooling,” presented at the IEE

conference publication, 2001, pp. 109–115. B. Kenneth, “Heat Density Trends in Data Processing, Computer Systems, and Telecommunications

Equipment,” UpTime Institute, White paper, 2005. C. Bash, C. D. Patel, and R. K. Sharma, “Dynamic thermal management of air cooled data centers,”

presented at the Thermal and Thermomechanical Phenomena in Electronics Systems, 2006, pp. 445–452.

G. Koutitas and P. Demestichas, “Challenges for Energy Efficiency in Local and Regional Data Centers,” Journal of Green Engineering, vol. 1, p. 32.

W. Tschudi, E. Mills, S. Greenberg, and P. Rumsey, “Measuring and Managing-Data Center Energy Use,” Ernest Orlando Lawrence Berkeley NationalLaboratory, Berkeley, CA (US), 2005.

S. Law, “Gresham startup says it can slash energy costs at power-thirsty server farms,” Portland Tribune, 2013.

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References

V. Avelar, Azevedo, and A. French, “PUETM: A comprehensive examination of the metric,” The Green Grid, White paper 49, 2012.

J. Bruschi, P. Rumsey, R. Anliker, L. Chu, and S. Gregson, “Best practices guide for energy-efficient data center design,” U.S. Department of Energy, Energy Efficiency & Renewable Energy, Federal Energy Management Program, [Washington, DC], 2010.

M. K. Herrlin, “Rack cooling effectiveness in data centers and telecom central offices: The rack cooling index (RCI),” Transactions-American Society of Heating Refrigerating and Air conditioning Engineers, vol. 111, p. 725, 2005.

T. ASHRAE, “9.9 (2011) Thermal guidelines for data processing environments–expanded data center classes and usage guidance,” Whitepaper prepared by ASHRAE technical committee (TC), vol. 9, 2011.

M. K. Herrlin, “Improved data center energy efficiency and thermal performance by advanced airflow analysis,” presented at the Digital Power Forum, 2007, pp. 10–12.

M. K. Herrlin, “Airflow and cooling performance of data centers: two performance metrics,” ASHRAE transactions, vol. 114, no. Part 2, 2008.

M. K. Patterson, “Energy efficiency metrics,” in Energy Efficient Thermal Management of Data Centers, Springer, 2012, pp. 237–271.

A. Vijayaraghavan and D. Dornfeld, “Automated energy monitoring of machine tools,” CIRP Annals-Manufacturing Technology, vol. 59, no. 1, pp. 21–24, 2010.

J. W. Gardner and V. K. Varadan, Microsensors, MEMS and smart devices. John Wiley & Sons, Inc., 2001. C.-Y. Chong and S. P. Kumar, “Sensor networks: evolution, opportunities, and challenges,” Proceedings of

the IEEE, vol. 91, no. 8, pp. 1247–1256, 2003. J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Computer networks, vol. 52, no.

12, pp. 2292–2330, 2008.

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IT Aire data center cooling system evaluation & Results

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