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Energy

Recalibrating global data center energy-use estimates

Growth in energy use has slowed owing to efficiency gains that smart policies can help maintain in the near term
Science
28 Feb 2020
Vol 367, Issue 6481
pp. 984-986

Abstract

Data centers represent the information backbone of an increasingly digitalized world. Demand for their services has been rising rapidly (1), and data-intensive technologies such as artificial intelligence, smart and connected energy systems, distributed manufacturing systems, and autonomous vehicles promise to increase demand further (2). Given that data centers are energy-intensive enterprises, estimated to account for around 1% of worldwide electricity use, these trends have clear implications for global energy demand and must be analyzed rigorously. Several oft-cited yet simplistic analyses claim that the energy used by the world's data centers has doubled over the past decade and that their energy use will triple or even quadruple within the next decade (35). Such estimates contribute to a conventional wisdom (5, 6) that as demand for data center services rises rapidly, so too must their global energy use. But such extrapolations based on recent service demand growth indicators overlook strong countervailing energy efficiency trends that have occurred in parallel (see the first figure). Here, we integrate new data from different sources that have emerged recently and suggest more modest growth in global data center energy use (see the second figure). This provides policy-makers and energy analysts a recalibrated understanding of global data center energy use, its drivers, and near-term efficiency potential.

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References and Notes

1
Cisco, “Cisco Global Cloud Index: Forecast and methodology, 2016–2021 white paper” (Cisco, document 1513879861264127, 2018).
2
International Energy Agency (IEA), Digitalization & Energy (IEA, 2017).
3
L. Belkhir, A. Elmeligi, J. Clean. Prod. 177, 448 (2018).
4
A.S.G. Andrae, T. Edler, Challenges 6, 117 (2015).
5
T. Bawdy, “Global warming: Data centres to consume three times as much energy in next decade, experts warn,” The Independent, 23 January 2016.
6
N. Jones, Nature 561, 163 (2018).
7
E. Masanet, R. E. Brown, A. Shehabi, J. G. Koomey, B. Nordman, Proc. IEEE 99, 1440 (2011).
8
A. Shehabi et al., “United States data center energy usage report” (Lawrence Berkeley National Laboratory, LBNL-1005775, 2016).
9
J. G. Koomey, “Growth in data center electricity use 2005 to 2010” (Analytics Press for the New York Times, 2011).
10
B. Wagner, “Intergenerational energy efficiency of Dell EMC PowerEdge servers” (Dell, DellEMC white paper, 2018).
11
A. Shehabi, S. J. Smith, E. Masanet, J. Koomey, Environ. Res. Lett. 13, 124030 (2018).
12
IEA, “Tracking clean energy progress” (IEA, 2019); www.iea.org/tcep/.
13
H. Fuchs et al., Energy Effic. 10.1007/s12053-019-09809-8 (2019).
14
M. Avgerinou, P. Bertoldi, L. Castellazzi, Energies 10, 1470 (2017).
15
E. Masanet, A. Shehabi, J. G. Koomey, Nat. Clim. Chang. 3, 627 (2013).

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Science
Volume 367 | Issue 6481
28 February 2020

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Published in print: 28 February 2020

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Acknowledgments

This material includes work conducted by Lawrence Berkeley National Laboratory (LBNL) with support from the U.S. Department of Energy (DOE) Advanced Manufacturing Office. LBNL is supported by the Office of Science of the DOE and operated under contract grant No. DE-AC02-05CH11231. E.M. and N.L. are grateful for financial support provided by Leslie and Mac McQuown. The global data center analysis modeling file with all data inputs, results, methodological notes, figures, discussion of uncertainties, and sources is available on GitHub (doi: 10.5281/zenodo.3668743 ).

Authors

Affiliations

Eric Masanet
McCormick School of Engineering and Applied Science, Northwestern University, Evanston, IL, USA.
Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, USA.
Arman Shehabi
Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Nuoa Lei
McCormick School of Engineering and Applied Science, Northwestern University, Evanston, IL, USA.
Sarah Smith
Energy Technologies Area, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Jonathan Koomey
Koomey Analytics, Burlingame, CA, USA.

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