The purpose of this thesis is to examine possible waste heat recovery methods in data
centers. Predictions indicate that in the next decade data center racks may dissipate 70kW of
heat, up from the current levels of 10-15kW. Due to this increase, solutions must be found to
increase the efficiency of data center cooling. This thesis will examine possible waste heat
recovery technologies which will improve energy efficiency. Possible approaches include phase
change materials, thermoelectrics, thermomagnetics, vapor compression cycles, absorbtion and
adsorbtion systems. After a thorough evaluation of the possible waste heat engines, the use of an
ejector heat pump was evaluated in detail. The principle behind an ejector heat pump is very
similar to a vapor compression cycle. However, the compressor is replaced with a pump, boiler
and an ejector. These three components require less moving parts and are more cost effective
then a comparable compressor, despite a lower efficiency. This system will be examined under
general operating conditions in a data center. The heat load is around 15-20kW and air
temperatures near 85°C. A parametric study is conducted to determine the viability and cost
effectiveness of this system in the data center. Included will be various environmentally friendly
working fluids that satisfy the low temperature ranges found in a data center. It is determined
that Ammonia presents the best option as a working fluid for this application. Using this system
a Coefficient Of Performance of 1.538 at 50°C can be realized. This will result in an estimated
373,000 kW-hr saved over a year and a $36,425 reduction in annual cost. Finally,
recommendations for implementation are considered to allow for future design and testing of this
viable waste heat recovery device.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/26594 |
Date | 24 November 2008 |
Creators | Harman, Thomas David, V |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Detected Language | English |
Type | Thesis |
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