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Improving energy efficiency of dedicated cooling system and its contribution towards meeting an energy-optimized data center

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  • Cho, Jinkyun
  • Kim, Yundeok

Abstract

Data centers are approximately 50 times more energy-intensive than general buildings. The rapidly increasing energy demand for data center operation has motivated efforts to better understand data center electricity use and to identify strategies that reduce the environmental impact. This research is presented analytical approach to the energy efficiency optimization of high density data center, in a synergy with relevant performance analysis of corresponding case study. This paper builds on data center energy modeling efforts by characterizing climate and cooling system differences among data centers and then evaluating their consequences for building energy use. Representative climate conditions for four regions are applied to data center energy models for several different prototypical cooling types. This includes cooling system, supplemental cooling solutions, design conditions and controlling the environment of ICT equipment were generally used for each climate zone, how these affect energy efficiency, and how the prioritization of system selection is derived. Based on the climate classification and the required operating environmental conditions for data centers suggested by the ASHRAE TC 9.9, a dedicated data center energy evaluation tool was taken to examine the potential energy savings of the cooling technology. Incorporating economizer use into the cooling systems would increase the variation in energy efficiency among geographic regions, indicating that as data centers become more energy efficient, their locations will have an increasing effect on overall energy demand. The proposal for the most energy-optimized data center is given by each climate zone.

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  • Cho, Jinkyun & Kim, Yundeok, 2016. "Improving energy efficiency of dedicated cooling system and its contribution towards meeting an energy-optimized data center," Applied Energy, Elsevier, vol. 165(C), pages 967-982.
    • Handle: RePEc:eee:appene:v:165:y:2016:i:c:p:967-982
    DOI: 10.1016/j.apenergy.2015.12.099
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    21. Wang, Wei & Abdolrashidi, Amirali & Yu, Nanpeng & Wong, Daniel, 2019. "Frequency regulation service provision in data center with computational flexibility," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
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