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Exploiting thermal energy storage to reduce data center capital and operating expenses

Authors: Wenli Zheng; Kai Ma; Xiaorui Wang;

Exploiting thermal energy storage to reduce data center capital and operating expenses

Abstract

Power shaving has recently been proposed to dynamically shave the power peaks of a data center with energy storage devices (ESD), such that more servers can be safely hosted. In addition to the reduction of capital investment (cap-ex), power shaving also helps cut the electricity bills (op-ex) of a data center by reducing the high utility tariffs related to peak power. However, existing work on power shaving focuses exclusively on electrical ESDs (e.g., UPS batteries) to shave the server-side power demand. In this paper, we propose TE-Shave, a generalized power shaving framework that exploits both UPS batteries and a new knob, thermal energy storage (TES) tanks equipped in many data centers. Specifically, TE-Shave utilizes stored cold water or ice to manipulate the cooling power, which accounts for 30–40% of the total power cost of a data center. Our extensive evaluation with real-world workload traces shows that TE-Shave saves cap-ex and op-ex up to $2,668/day and $825/day, respectively, for a data center with 17,920 servers. Even for future data centers that are projected to have more efficient cooling and thus a smaller portion of cooling power, e.g., a quarter of today's level, TE-Shave still leads to 28% more savings than existing work that focuses only on the server-side power. TE-Shave is also coordinated with traditional TES solutions for further reduced op-ex.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
35
Top 10%
Top 10%
Top 10%
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