On Global Electricity Usage of Communication Technology: Trends to 2030

Overview

The work estimates the global electricity usage that can be ascribed to communication technology (CT) between 2010 and 2030. The scope is three scenarios for use and production of consumer devices, communication networks and data centres: best, expected and worst, with annual numbers of sold devices, data traffic and electricity intensities/efficiencies. The most significant trend, regardless of scenario, is that the proportion of use-stage electricity by consumer devices will decrease and be transferred to the networks and data centres.

Data-centre electricity is computed from global data-centre IP traffic and an intensity of 0.135, 0.14 and 0.142 TWh/EB in 2010 (best/expected/worst), with annual efficiency improvement of 15%, 10% and 5% respectively (5% for all scenarios from 2022). Data centres are projected to use around 3-13% of global electricity in 2030 compared with 1% in 2010, against a 25% annual growth in data-centre IP traffic. To hold fixed-access wired and data-centre electricity at the 2015 level, a 17-times improvement in TWh/EB between 2015 and 2030 would be needed, while four times is foreseen.

In the worst-case scenario communication technology could use as much as 51% of global electricity in 2030 and contribute up to 23% of global GHG emissions, which would happen if not enough improvement in electricity efficiency of wireless access networks and fixed access networks/data centres is possible. Generated renewable electricity in 2030 (11,000 TWh) is likely to exceed the electricity demand of all networks and data centres (2200 to 23,100 TWh across scenarios).

Limits: results range very widely and the worst case is very high; the traffic-based extrapolation method was later criticised for overestimating demand, so the paper is useful mainly as a method and upper-bound reference. Scenario parameters are assumptions.

Key points

1. In the worst-case scenario communication technology could use as much as 51% of global electricity in 2030 and contribute up to 23% of global GHG emissions.
2. Data-centre electricity is computed from global data-centre IP traffic and an intensity of 0.135, 0.14 and 0.142 TWh/EB in 2010 (best/expected/worst), with annual efficiency improvement of 15%, 10% and 5% (5% for all scenarios from 2022).
3. Data centres are projected to use around 3-13% of global electricity in 2030 compared with 1% in 2010, against a 25% annual growth in data-centre IP traffic.
4. To hold fixed-access wired and data-centre electricity at the 2015 level, a 17-times improvement in TWh/EB between 2015 and 2030 would be needed, while four times is foreseen.
5. Generated renewable electricity in 2030 (11,000 TWh) is likely to exceed the electricity demand of all networks and data centres (2200 to 23,100 TWh across scenarios).

Using it in design

• In data-centre electricity-demand projections use traffic-based extrapolation (traffic × annually improving energy intensity) as an upper-bound reference; the worst case is very high and the method was later criticised for overestimating demand.
• Make the energy-intensity improvement assumption (5-15% a year) an explicit input and report the uncertainty by showing the range across scenarios (data centres 3-13% in 2030).
• In power and energy planning present projections as a best/expected/worst range rather than a single value.

Who should read it

Analysts and policy specialists assessing the method and upper bounds of data-centre electricity-demand projections.

Document contents

1. 1. Introduction
2. 2. Materials and Methods—Approach
3. 3. Consumer Devices Use Stage—Results (3.1 Desktops, Monitors, Laptops, 3.2 Smartphones, Tablets, ..., 3.3 TVs, 3.4 TV peripherals)
4. 4. Networks Use Stage—Results (4.1 Fixed Access Wired and Wi-Fi Networks, 4.2 Wireless Access Networks: mobile data traffic)
5. 5. Data Centers Use Stage—Results
6. 6. Production Electricity for Consumer Devices, Networks and Data Centers—Results
7. 7. Global Electricity Usage
8. 8. Renewable Electricity
9. 9. Overall Results
10. 10. Discussion (10.3 Improvement of Electricity Efficiency for Electricity Usage and GHG Reduction, 10.4 Renewable Electricity Capacity for Greenhouse Gas Emission Reduction)
11. 11. Conclusions
12. 12. Next Steps

Read the document

Publication details

Authors

Anders Andrae; Tomas Edler

Publisher

Challenges (MDPI AG)

Year

2015

Volume

6

Issue

1

Pages

117-157

Document language

English

Source type

Scientific

Access

Open licence — downloadable

DOI

10.3390/challe6010117

Licence

CC BY 4.0 — share with attribution

Licence evidence

www.mdpi.com

Citation