Optimal power cost management using stored energy in data centers

Rahul Urgaonkar, Bhuvan Urgaonkar, Michael J. Neely, Anand Sivasubramanian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

190 Citations (Scopus)

Abstract

Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, reducing this has become important. We investigate cost reduction opportunities that arise by the use of uninterrupted power supply (UPS) units as energy storage devices. This represents a deviation from the usual use of these devices as mere transitional fail-over mechanisms between utility and captive sources such as diesel generators. We consider the problem of opportunistically using these devices to reduce the time average electric utility bill in a data center. Using the technique of Lyapunov optimization, we develop an online control algorithm that can optimally exploit these devices to minimize the time average cost. This algorithm operates without any knowledge of the statistics of the work-load or electricity cost processes, making it attractive in the presence of workload and pricing uncertainties. An interesting feature of our algorithm is that its deviation from optimality reduces as the storage capacity is increased. Our work opens up a new area in data center power management.

Original languageEnglish (US)
Title of host publicationSIGMETRICS'11 - Proceedings of the 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems
Pages221-232
Number of pages12
Edition1 SPEC. ISSUE
DOIs
StatePublished - Jul 15 2011
Event2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS'11 - San Jose, CA, United States
Duration: Jun 7 2011Jun 11 2011

Publication series

NamePerformance Evaluation Review
Number1 SPEC. ISSUE
Volume39
ISSN (Print)0163-5999

Other

Other2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS'11
CountryUnited States
CitySan Jose, CA
Period6/7/116/11/11

Fingerprint

Costs
Electricity
Electric utilities
Cost reduction
Energy storage
Statistics
Uncertainty
Power management

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

Urgaonkar, R., Urgaonkar, B., Neely, M. J., & Sivasubramanian, A. (2011). Optimal power cost management using stored energy in data centers. In SIGMETRICS'11 - Proceedings of the 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (1 SPEC. ISSUE ed., pp. 221-232). (Performance Evaluation Review; Vol. 39, No. 1 SPEC. ISSUE). https://doi.org/10.1145/1993744.1993766
Urgaonkar, Rahul ; Urgaonkar, Bhuvan ; Neely, Michael J. ; Sivasubramanian, Anand. / Optimal power cost management using stored energy in data centers. SIGMETRICS'11 - Proceedings of the 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems. 1 SPEC. ISSUE. ed. 2011. pp. 221-232 (Performance Evaluation Review; 1 SPEC. ISSUE).
@inproceedings{94cbcf9cf18b4bf799899c34b58801ff,
title = "Optimal power cost management using stored energy in data centers",
abstract = "Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, reducing this has become important. We investigate cost reduction opportunities that arise by the use of uninterrupted power supply (UPS) units as energy storage devices. This represents a deviation from the usual use of these devices as mere transitional fail-over mechanisms between utility and captive sources such as diesel generators. We consider the problem of opportunistically using these devices to reduce the time average electric utility bill in a data center. Using the technique of Lyapunov optimization, we develop an online control algorithm that can optimally exploit these devices to minimize the time average cost. This algorithm operates without any knowledge of the statistics of the work-load or electricity cost processes, making it attractive in the presence of workload and pricing uncertainties. An interesting feature of our algorithm is that its deviation from optimality reduces as the storage capacity is increased. Our work opens up a new area in data center power management.",
author = "Rahul Urgaonkar and Bhuvan Urgaonkar and Neely, {Michael J.} and Anand Sivasubramanian",
year = "2011",
month = "7",
day = "15",
doi = "10.1145/1993744.1993766",
language = "English (US)",
isbn = "9781450302623",
series = "Performance Evaluation Review",
number = "1 SPEC. ISSUE",
pages = "221--232",
booktitle = "SIGMETRICS'11 - Proceedings of the 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems",
edition = "1 SPEC. ISSUE",

}

Urgaonkar, R, Urgaonkar, B, Neely, MJ & Sivasubramanian, A 2011, Optimal power cost management using stored energy in data centers. in SIGMETRICS'11 - Proceedings of the 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems. 1 SPEC. ISSUE edn, Performance Evaluation Review, no. 1 SPEC. ISSUE, vol. 39, pp. 221-232, 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, SIGMETRICS'11, San Jose, CA, United States, 6/7/11. https://doi.org/10.1145/1993744.1993766

Optimal power cost management using stored energy in data centers. / Urgaonkar, Rahul; Urgaonkar, Bhuvan; Neely, Michael J.; Sivasubramanian, Anand.

SIGMETRICS'11 - Proceedings of the 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems. 1 SPEC. ISSUE. ed. 2011. p. 221-232 (Performance Evaluation Review; Vol. 39, No. 1 SPEC. ISSUE).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Optimal power cost management using stored energy in data centers

AU - Urgaonkar, Rahul

AU - Urgaonkar, Bhuvan

AU - Neely, Michael J.

AU - Sivasubramanian, Anand

PY - 2011/7/15

Y1 - 2011/7/15

N2 - Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, reducing this has become important. We investigate cost reduction opportunities that arise by the use of uninterrupted power supply (UPS) units as energy storage devices. This represents a deviation from the usual use of these devices as mere transitional fail-over mechanisms between utility and captive sources such as diesel generators. We consider the problem of opportunistically using these devices to reduce the time average electric utility bill in a data center. Using the technique of Lyapunov optimization, we develop an online control algorithm that can optimally exploit these devices to minimize the time average cost. This algorithm operates without any knowledge of the statistics of the work-load or electricity cost processes, making it attractive in the presence of workload and pricing uncertainties. An interesting feature of our algorithm is that its deviation from optimality reduces as the storage capacity is increased. Our work opens up a new area in data center power management.

AB - Since the electricity bill of a data center constitutes a significant portion of its overall operational costs, reducing this has become important. We investigate cost reduction opportunities that arise by the use of uninterrupted power supply (UPS) units as energy storage devices. This represents a deviation from the usual use of these devices as mere transitional fail-over mechanisms between utility and captive sources such as diesel generators. We consider the problem of opportunistically using these devices to reduce the time average electric utility bill in a data center. Using the technique of Lyapunov optimization, we develop an online control algorithm that can optimally exploit these devices to minimize the time average cost. This algorithm operates without any knowledge of the statistics of the work-load or electricity cost processes, making it attractive in the presence of workload and pricing uncertainties. An interesting feature of our algorithm is that its deviation from optimality reduces as the storage capacity is increased. Our work opens up a new area in data center power management.

UR - http://www.scopus.com/inward/record.url?scp=79960180251&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=79960180251&partnerID=8YFLogxK

U2 - 10.1145/1993744.1993766

DO - 10.1145/1993744.1993766

M3 - Conference contribution

AN - SCOPUS:79960180251

SN - 9781450302623

T3 - Performance Evaluation Review

SP - 221

EP - 232

BT - SIGMETRICS'11 - Proceedings of the 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems

ER -

Urgaonkar R, Urgaonkar B, Neely MJ, Sivasubramanian A. Optimal power cost management using stored energy in data centers. In SIGMETRICS'11 - Proceedings of the 2011 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems. 1 SPEC. ISSUE ed. 2011. p. 221-232. (Performance Evaluation Review; 1 SPEC. ISSUE). https://doi.org/10.1145/1993744.1993766