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Applying a Model of Technology Diffusion to Quantify the Potential Benefit of Improved Energy Efficiency in Data Centres

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  • Bryan Coyne

    (Department of Economics, Trinity College Dublin, D02 PN40 Dublin 2, Ireland
    Department of Business, Institute of Technology Sligo, Co., F91 YW50 Sligo, Ireland)

  • Eleanor Denny

    (Department of Economics, Trinity College Dublin, D02 PN40 Dublin 2, Ireland)

Abstract

Data centres are a key infrastructure for the global digital economy, helping enable the EU “Digital Decade” by 2030. In 2015, data centres were estimated to consume 2.5% of EU electricity demand. In Ireland, the concentrated presence of data centres could consume 37% of national electricity demand by 2028. The uncertainty of data centre facility-level energy efficiency paired with the need to achieve a low-carbon economy pose significant challenge for generation and transmission network planning. This is the first paper to apply a model of technology diffusion with a national forecast of changes in Irish data centre electricity demand through more efficient liquid cooling. The methodology serves as a technology-agnostic resource for practitioners performing forecasts under uncertainty with limited information. Results suggest that technology adoption could lower national electricity demand by 0.81% if adopted by new plant from 2019 to 2028. Savings rise to 3.16% over the same period if adopted by new and existing data centres. Adoption would also lower related emissions by 4.70% and 23.04% over the same period across both scenarios, respectively. Results highlight substantial potential electricity and associated emissions savings available in the sector and suggest policy options to support a transition towards a low-carbon economy.

Suggested Citation

  • Bryan Coyne & Eleanor Denny, 2021. "Applying a Model of Technology Diffusion to Quantify the Potential Benefit of Improved Energy Efficiency in Data Centres," Energies, MDPI, vol. 14(22), pages 1-18, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:22:p:7699-:d:681248
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    References listed on IDEAS

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    2. Zhao, Haoran & Guo, Sen, 2023. "Analysis of the non-linear impact of digital economy development on energy intensity: Empirical research based on the PSTR model," Energy, Elsevier, vol. 282(C).

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