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Energy
Article . 2020 . Peer-reviewed
License: Elsevier TDM
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The role of data centres in the future Danish energy system

Authors: Stefan Petrović; Alessandro Colangelo; Olexandr Balyk; Chiara Delmastro; Maurizio Gargiulo; Mikkel Bosack Simonsen; Kenneth Karlsson;

The role of data centres in the future Danish energy system

Abstract

Abstract Data centres (DCs) are expected to satisfy the rising demand for internet services. Denmark alone is expected to host several large-scale DCs, whose demand for electricity in 2040 may reach 33% of 2017 national electricity consumption. Understanding the operation and interactions of DCs with energy systems is key to understanding their impacts on installed capacities, costs and emissions. The present paper makes three contributions in this regard. First, we introduce a thermodynamic model that relates the power consumption of DCs to their production of excess heat (EH). Second, the results are scaled up to represent DCs in a national energy-system model for the analysis of different scenarios. Third, scenarios are generated and analysed to quantify the impact of DCs on the Danish energy system until 2050. The results show that DCs might have significant impacts on Denmark’s power and district heating (DH) sectors. First, the power demand from DCs translates into an additional 3–6 GW of offshore wind capacity. Second, EH from DCs is beneficial to the whole energy system, the entire quantity of EH being utilized in four out of five scenarios. EH recovery from DCs is economically beneficial, providing from 4% to 27% of Denmark’s DH after 2040.

Countries
Denmark, Italy
Keywords

/dk/atira/pure/sustainabledevelopmentgoals/affordable_and_clean_energy; name=SDG 7 - Affordable and Clean Energy, Carbon budget; District heating; Energy systems analysis; Excess heat; Power demand; TIMES-DK

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    29
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Top 10%
Top 10%
Top 10%
Green
bronze