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Prediction Studies of Electricity Use of Global Computing in 2030

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International Journal of Science and Engineering Investigations (IJSEI), Vol. 8, Issue 86, pp. 27-33, 2019, http://www.ijsei.com/papers/ijsei-88619-04.pdf, peer-reviewed article, The electricity use of the information technology (IT) sector - consisting of demand from computing, transmission and production - is of large interest. Here a theoretical framework describing how the total global electricity demand - associated with the computing instructions done in servers and computers - is used to estimate the electricity use in 2030. The proposed theoretical framework is based on the following parameters: instructions per second, joules per transistor, and transistors per instruction as well as a distinction between general and special purpose computing. The potential predictions - made possible with the proposed equations - include the electricity used by the data centres based on utilization of the processors therein and estimations of the electricity use of the processors used in fixed and mobile networks and end-user devices. Predictions for computing 2030 vary a lot depending on which transistor technology will be dominant handling the instructions. Two other prediction techniques - based on instructions per joule and joules per operation - give similar results.
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... Figure 2 shows the range of estimates of global data center energy for the years 2010, 2020, and 2030. The difference between the min and max values is an order of magnitude, excluding estimates greater than 2,000 TWh for effective scaling of the visualizations (5 estimates in total, 2 from Andrae and Edler, 11 1 from Andrae, 31 1 from The Shift Project, 13 and 1 from Andrae. 32 If included, the max value for 2030 11 All estimates can be found in Table S2. ...
... Several of these were self-published via ResearchGate 33,34 and only included in this review because they were cited in a formally published article. 31 Sources without a publication year (classed as ''N/A,'' 17%) were common, highlighting that much of the data within is being captured by databases and other means of dissemination, versus through official publications. This lack of information makes methods challenging to reproduce because the original source data cannot be pinpointed. ...
... An alternative approach to bottom-up calculations from shipment and installed base statistics was developed in Andrae. 31,[33][34][35] Here, estimates for the energy per individual CPU instruction are suggested and then extrapolated to an estimated total number of annual, global number of CPU instructions. Although future efficiency improvements can be included in the calculations, the tech industry has shown it is repeatedly able to introduce unexpected innovations. ...
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... Datacenters are nonetheless part of an extended sociotechnical system with an increasing environmental impact. Internet and online services account for about 10% of global electricity demand [2,3], and take a similar proportion of electricity in most countries. The growth in energy powering the online services and data that society relies upon shows no sign of slowing, with about 20% annual growth in network traffic. ...
... Our literature review materials were sourced from scholarly databases like Scopus, online sites like Google and government websites. We utilized these sources because [1]: research on datacenter (especially in the Arctic or Nordic region) is not yet mature [2], scholarly articles in standard sources like Scopus were fairly limited as a sole source of data and [3], of our need to understand the unique roles and perspectives of different governments towards incentivizing the datacenter industry in their countries. ...
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... 100-175 g Table 2 shows the carbon footprint of internet activities per hour by watching hours based on four different methods based on [1,11,[25][26][27][28]. The main differences were the time spent on the actions and the data size of the video. ...
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... Clearly, the main determinant of energy consumption in ICT networks is the volume of data traffic. However, energy demand associated with the computing instructions performed in servers and computers can also be used to estimate the energy consumption (Andrae, 2019b). Meanwhile, bandwidth growth and a further slow-down in efficiency improvements may cause that the Internet becomes the ultimate energy-consuming machine globally (Grobe and Jansen, 2020). ...
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... Due to this intensive use of software, ICT energy consumption had already increased by 2018 to 1895 TW h, representing about 9% of total global energy consumption [2]. And by 2025, this could exceed 20 % of total energy and emit up to 5.5 % of the world's carbon emissions [3,4]. ...
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... Scientific debate over ICT's emissions has intensified in the last 5 years. We therefore focus on research since 2015-especially studies by three main research groups led by Andrae, [3][4][5][6] Belkhir, 7 and Malmodin. 8,9 Andrae and Edler 3 estimate ICT's emissions for every year 2010-2030, Belkhir and Elmeligi 7 for 2007-2040 and Malmodin and Lundé n 8,9 for 2015. ...
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