Pinto, R., Brockway, P.E. orcid.org/0000-0001-6925-8040, Domingos, T. et al. (1 more author) (2026) Long-run electricity consumption in computing: Exponential growth followed by stabilization due to efficiency gains. iScience, 29 (3). 114876. ISSN: 2589-0042
Abstract
Published projections suggest that information and communication technologies could account for up to 20% of global electricity use by 2030, yet these estimates are often based on short (<5 years) historical periods. Here, we present the first global long-run (1975-2022) analysis that jointly estimates electricity consumption, processed information, and efficiency. We find that these increased by 4, 11, and 7 orders of magnitude, respectively. However, after an initial exponential growth, the share of computing devices in world electricity consumption peaked at 2.5% in 2013, then decreased and stabilized at 1.8% since 2018. The stabilisation was due to the massive increases in information processing being offset by efficiency gains associated with the growing amount of computation in large datacenters and the shift from desktop computers to laptops and, more recently, to smartphones. These results indicate that concerns about the future electricity demand of computing may be overstated.
Metadata
| Item Type: | Article |
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| Authors/Creators: |
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| Copyright, Publisher and Additional Information: | © 2026 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | electricity; energy management; information and communication technologies |
| Dates: |
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| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) |
| Date Deposited: | 12 May 2026 10:59 |
| Last Modified: | 12 May 2026 10:59 |
| Status: | Published |
| Publisher: | Elsevier |
| Identification Number: | 10.1016/j.isci.2026.114876 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:240748 |

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