DocumentCode :
634794
Title :
Distributed battery control for peak power shaving in datacenters
Author :
Aksanli, Baris ; Rosing, Tajana ; Pettis, Eddie
Author_Institution :
Comput. Sci. & Eng. Dept., UC San Diego, San Diego, CA, USA
fYear :
2013
fDate :
27-29 June 2013
Firstpage :
1
Lastpage :
8
Abstract :
Datacenters are large cyber-physical systems with continuous performance and power measurements, and real-time control decisions related to workload placement, cooling and power subsystems etc. In our work we focus on the non-ideal UPS system used to shave peak power demands. Our novel distributed battery control design has no performance impact, reduces the peak power needs, and accurately estimates and maximizes the battery lifetime. We demonstrate that models which do not take into account physical characteristics of batteries overestimate their lifetime by 2.4x. In contrast, our design is within 3.3% of the centralized battery control in terms of battery lifetime with 10x reduction in the communication costs, while shaving 23MWhrs/week of energy in a 10MW datacenter, equivalent to adding 8760 more servers at no additional power cost.
Keywords :
computer centres; distributed control; power measurement; real-time systems; secondary cells; uninterruptible power supplies; battery lifetime; communication costs; continuous performance; cooling; datacenters; distributed battery control; large cyber-physical systems; nonideal UPS system; peak power demands; peak power shaving; power 10 MW; power measurements; power subsystems; real-time control decisions; workload placement; Batteries; Discharges (electric); Power demand; Power measurement; Servers; US Department of Defense; Uninterruptible power systems; batteries; datacenters; distributed control; peak power shaving;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Green Computing Conference (IGCC), 2013 International
Conference_Location :
Arlington, VA
Type :
conf
DOI :
10.1109/IGCC.2013.6604477
Filename :
6604477
Link To Document :
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