Influence of cooling architecture on data center power consumption

Hosein Moazamigoodarzi, Peiying Jennifer Tsai, Souvik Pal, Suvojit Ghosh and Ishwar K. Puri

Energy, 2019, vol. 183, issue C, 525-535

Abstract: Almost thirty percent of the power consumed by data centers (DCs) is attributable to the cooling of IT equipment (ITE). There are opportunities to reduce a DC's energy budget by considering alternatives to traditional cooling methods, which experience inherent airflow deficiencies due to hot air recirculation and cold air bypass. Minimizing these two air distribution problems results in more effective cooling, but the two effects are manifest differently in the three conventional DC cooling architectures, i.e., (a) room-based, (b) row-based, and (c) rack-based cooling. Despite the intuitive logic that predicts improved cooling air distribution within row- and rack-based architectures that include shorter airflow pathlengths compared to room-based systems that have longer paths, the mechanism through which improvements translate into energy savings is not well understood. Therefore, we present methodologies that resolve the characteristic airflow and temperature distributions for three cooling architectures using computational fluid dynamics. These results inform thermodynamics models of the power consumptions that are required to cool these three architectures. The analysis reveals that row- and rack-based architectures reduce cooling power by much as 29% over a room-based architecture. Adding an enclosure within row- and rack-based architectures to separate the hot and cold airflows provides further 18% reduction in cooling power. This analysis facilitates better DC design from a cooling power consumption perspective.

Keywords: Data center; Distributed cooling; Power consumption; Row-based; Rack-based (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:183:y:2019:i:c:p:525-535

DOI: 10.1016/j.energy.2019.06.140

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