Date post: | 28-Dec-2015 |
Category: |
Documents |
Upload: | junior-hunter |
View: | 221 times |
Download: | 0 times |
A Sustainable Data Center with Heat-Activated Cooling
Thermodynamic Feasibility
1Anna Haywood, Jon Sherbeck, Patrick Phelan, Georgios Varsamopoulos, Sandeep K. S. Gupta
INTRODUCTIONThermal architecture side: II-EN: BlueTool:
Infrastructure for Innovative Cyberphysical Data Center Management Research
NSF funded award #0855277
In response to an acknowledged problemIncreasing amount of data center energy use,Currently at 3% of all US energy consumption~50% of which is used for cooling the data
center2
The BlueTool project
Design and on-site assessment services
BlueWeb: On-line data and simulation services
Online services:• Measurement archive• Profile archive• Model archive• Energy Calculator
authorized userBackend data andservice access
Research:• Model development• Scheduling testing• Design methodology development• Alternative, eco-friendly cooling technologies
Researchers at ASU
Consulting services:• Energy and efficiency
assessment• Design and online
solutions• Expert advising
BlueCenter:Experimental testbed
BlueSense: on-site monitoring
http://impact.asu.edu/BlueTool/
3
ObjectiveThe overall objective of thermal project is to
reduce the grid power consumption of the cooling system for data centers.
4
HOW?use heat-driven, LiBr absorption chiller to
reduce the cooling load on a typical Computer Room AC (CRAC)
heat to drive the chiller will be originated from the data center itself.
Challenges1. generating enough high-temperature heat
from the blade components inside the data center,
Target heat source = CPUs
2. and then capturing and transporting that heat effectively and efficiently to a Li-Br heat-activated absorption unit.
dynamic/fluctuating heat output of CPUs
5
Overall Concept: Capture 90% of CPU heat and send to chiller
6
CPUs dissipate most heat on the board high heat fraction (HHF)
a capture fraction (CF) of 0.90.
Low loss
LiBr heat-activated chiller
SHiTQ ,
CRACQ T budget =70-95oC
High Heat Fraction
7
42U
chassisIT blade server
CPUs
Figure 1. IT server equipment.
Dell DataCenter Capacity Planner Tool: 103W/CPU, 294W/blade and 19.78kW/rack
HHF: CPU heat /blade heat = 0.7(206W/294W)
10blades/chassis
5 chassis/rack
7U
Target Heat SourceDell PE 1855Intel® Xeon®
Nocona Processors 3.20 GHz
2 CPUs/server blade103W/CPU =
206W/bladeTDP @ 72oC
8
How much heat required from CPUs to run chiller for best performance?
Cooling Capacity: 10 ton =35.2 kW and COPC = 0.7
*Goal: 50.3 kW*Translates into 269 server blades of the Dell PE 1855 with dual Xeon Nocona CPUs.
gQ
eQCOP
inHeat
outCoolingOP CC
orC
Apply Steady-State System AnalysisData center + cooling system layout
System equations applied to PUEApply equations to gauge system performance
Analyze power effectiveness of data centerPUE metric: Power Usage EffectivenessRatio of power delivered to the facility divided
by power used exclusively for the IT equipment
10
System diagram: work and heat flow paths
11Contributors: Dr. Phelan, Anna Haywood, Jon Sherbeck, Phani Domalapally
PUE is traditionally defined assuming conventional electric supply configurations
For non-conventional configurations,using alternative sourcesor reusing heat,
12
PowerElectricIT
PowerElectricTotalPUE
.
PUE Level of Efficiency
3.0 Very Inefficient
2.5 Inefficient
2.0 Average
1.5 Efficient
1.2 Very Efficient
Industry benchmarked PUE values (GreenGrid 2009)
PUE may fall below 1.0
PUE applied to our system diagram
13
IT
LossLightsCPCRACIT
IT
TOT
W
WWWWW
W
WPUE
CoolW
CRAC
CRACCRAC COP
QW
IT
CPLossLightsCRAC
SHiTEVAPTOTIT
W
WWWCOP
QQQW
PUE
,
Relates electric power for compressor to the heat load on the CRAC
CPU heat load removal
Equations relating PUE to HHF, CF, QEXT
14
total heat flow from data center as a load on the cooling equipment
SHiTEVAPTOT QQQ ,
ITCPLightsLoss
CRAC
ITEXTITCLightsLossIT
IT
W/}WWWCOP
WCFHHF)QWCF(HHFCOPWWW
W{PUE
SHiTQ ,
EVAPQ
TOTQ
chiller’s cooling capacity reduces heat load on CRAC
heat extraction from the CPUs to the storage
Portion of rack heat driving chiller
15
Rearranging terms and simplifying
IT
CP
IT
Lights
IT
Loss
IT
EXTC
IT
Lights
IT
Loss
CRAC
W
W
W
W
W
W
CFHHF)W
QCF(HHFCOP
W
W
W
W1
COP
1
1PUE
PUE can become less than one. This cooling portion (heat removal) is divided by COPCRAC to represent electric power.
CRAC
IT
EXTC
COP
)WQ
CF(HHFCOP
Term suggests that external heating can generate excess cooling that can be “exported,” i.e., used to cool adjacent rooms or facilities, -- (pwr out)
CoolW
Win = QL/COPCRAC
Calculated values for our data center with 6 racks
16
HHF 0.70
(6 racks) 118.70 kWe
(CPUs) 74.77 kWth
0.55 kWe
0.50 kWe
0.21 kWe
-1.88 kWe
Coefficients of performance
COPCRAC 3.9 *typical COPR
COPC 0.7 optimum
Capture Fraction (CF) 0.90 Expected
PUE 0.99
CRAC
CP
Lights
Loss
HiT
IT
WW
WWQW
Heat pwr
Elec pwr
ITWCFHHF
0 10 20 30 40 50 60 70 80 90 100
0 20 40 60 80 100 120
0.97
1.02
1.07
1.12
1.17
1.22
1.27
0.97
1.02
1.07
1.12
1.17
1.22
1.27
High-Temperature Capture Fraction (%)
COPC = 0.7
COPC = 0.6
COPC = 0.5
PUE “very efficient” for our Data Center
17
PUE=0.99
PU
E
PUE even better with Solar Source Added
18
PUE=0.81
0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 10.80
0.85
0.90
0.95
1.00
1.05
COPC = 0.7
COPC = 0.5
COPC= 0.6
PU
E
ConclusionThe potential exists to utilize some of the waste heat
generated by data centers to drive absorption chillers, which would then relieve some of the cooling load on the conventional computer room air conditioner (CRAC).
By reusing data center waste heat and supplementing the high-temperature heat captured from the CPUs with an external source of heating, such as from solar energy, it is theoretically possible to generate a PUE (Power Usage Effectiveness) ratio of less than one.
19
Extra material
20
Example using reused heatTake an initial PUE of 1.283% of that goes to servers
If can utilize 30% of dissipated heat, then PUE drops to 0.9
21
9.04.15MW
1.24MW-5MWPUE
4.15MW
5MWPUE