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Data center growth in the United States: Decoupling the demand for services from electricity use

Journal Article · · Environmental Research Letters
 [1];  [1];  [2];  [3]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Energy Analysis & Environmental Impacts Division
  2. Northwestern Univ., Evanston, IL (United States). McCormick School of Engineering
  3. Koomey Analytics, Burlingame, CA (United States)
Data centers are energy intensive buildings that have grown in size and number to meet the increasing demands of a digital economy. This paper presents a bottom-up model to estimate data center electricity demand in the United States over a 20 year period and examines observed and projected electricity use trends in the context of changing data center operations. Results indicate a rapidly increasing electricity demand at the turn of the century that has significantly subsided to a nearly steady annual electricity use of about 70 billion kWh in recent years. While data center workloads continue to grow exponentially, comparable increases in electricity demand have been avoided through the adoption of key energy efficiency measures and a shift towards large cloud-based service providers. Alternative projections from the model illustrate the wide range in potential electricity that could be consumed to support data centers, with the US data center workload demand estimated for 2020 requiring a total electricity use that varies by about 135 billion kWh, depending on the adoption rate of efficiency measures during this decade. While recent improvements in data center energy efficiency have been a success, the growth of data center electricity use beyond 2020 is uncertain, as modeled trends indicate that the efficiency measures of the past may not be enough for the data center workloads of the future. The results show that successful stabilization of data center electricity will require new innovations in data center efficiency to further decouple electricity demand from the ever-growing demand for data center services.
Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1494097
Alternate ID(s):
OSTI ID: 22882025
Journal Information:
Environmental Research Letters, Journal Name: Environmental Research Letters Journal Issue: 12 Vol. 13; ISSN 1748-9326
Publisher:
IOP PublishingCopyright Statement
Country of Publication:
United States
Language:
English

References (14)

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Greening Multi-Tenant Data Center Demand Response preprint January 2015

Cited By (1)

Energy-Aware Online Non-Clairvoyant Scheduling Using Speed Scaling with Arbitrary Power Function journal April 2019

Figures / Tables (4)


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