Page 24 - European Energy Innovation - autumn 2019 publication
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24                          Autumn 2019 European Energy Innovation

                            DIGITALIZATION

Final energy demand (EU28) for all sectors in the three scenarios and the variant (Worst Case).
The graph shows also the contribution of the four large Trend Clusters in the case of the New
Trends Efficient Scenario

Final Energy Demand [Mtoe]  1800                                                  Digitalization
                            1600                                                  New Social and Economic
                            1400                                                  Models
                            1200                                                  Industrial Transformation
                            1000                                                  Quality of Life
                             800                                                  Worst Case
                             600                                                  Baseline (Primes 2016)
                             400                                                  New Trends Inefficient
                             200                                                  Removing Market Barriers
                                                                                  New Trends Efficient
                                 0
                                 2000 2010 2020 2030 2040 2050

Key findings:                                 the case when digital processes         demand could be up to 67% lower
• If the techno-economic potentials           become more and more efficient,         in 2050. This scenario is only
                                              but also drastically increase in        achievable if the trends unfold in a
    - including the ones arising              volume, therefore leading to an         way that puts a decreasing energy
    through digitalization - are              increased energy demand (as             demand first (supported by the
    realized (in the Removing Market          compared to the Removing Market         respective legislation).
    Barriers Scenario), final energy          Barriers Scenario).
    demand in Europe could decrease                                               The work conducted for the “Study
    substantially by up to 51% (relative  • If, in addition, the techno-          on Energy Savings Scenario 2050”
    to the reference scenario).               economic potentials are not         summarizes existing knowledge on
                                              realized, for example due to a      the correlation between societal
• If there is no focus on reducing            hesitant energy efficiency policy   trends and energy demand in a
    energy demand when developing             (worst case variant), then final    pioneering study. It clearly reveals the
    societal trends (New Trends               energy demand could increase        strong influence that new trends can
    Inefficient Scenario), this will          substantially by 42%.               have on energy demand. The “Study
    counteract reductions achieved                                                on Energy Savings Scenario 2050”
    due to the techno-economic            • If, in contrast, new societal trends  was published in January 2019 and
    potentials. This means, the               are supported by a strong focus     forms the prelude to more intensive
    scenario only achieves a 32%              on energy demand reduction (New     research on the impact of new
    reduction of European energy              Trends Efficient Scenario), energy  societal trends on energy demand. l
    demand. This is for example

Brugger, H.; Eichhammer, W.; Dönitz, E. (2019): Study on Energy Savings Scenarios 2050.
https://www.isi.fraunhofer.de/content/dam/isi/dokumente/ccx/2019/Summary_Energy-Savings-Scenarios-2050.pdf

Wadud, Z., MacKenzie, D., Leiby, P., 2016. Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles.
Transportation Research Part A: Policy and Practice 86, 1–18.https://doi.org/10.1016/j.tra.2015.12.001

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