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The development of the German energy market until 2030--A critical survey of selected scenarios

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  • Keles, Dogan
  • Möst, Dominik
  • Fichtner, Wolf

Abstract

Many scenarios have been generated in the last years analysing the international energy market. The variety of these scenarios is manifold, as they are generated by different institutions using different methodological approaches and different framework assumptions. However, these scenarios can roughly be classified into three main groups: "moderate", "climate protection" and "resource scarcity and high fossil fuel prices". Analysing the German energy market makes a fourth scenario group necessary, which considers the possible revision of the decided nuclear energy phase out. Most of the existing scenarios developed by different institutions can be allocated into one of these groups. A representative scenario for each group has been selected to illustrate the development of the energy sector until 2030. Contrary to the worldwide primary energy demand (PED), the German PED decreases in each scenario, even though the drop differs strongly throughout the scenarios. On the other hand the structure of the PED in 2030 varies strongly for each scenario, especially regarding the share of fossil energy sources. However, a common robust result can be observed throughout all scenarios, namely the high increase in the share of the renewable energy resources, although the scenario generation processes are not always robust.

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  • Keles, Dogan & Möst, Dominik & Fichtner, Wolf, 2011. "The development of the German energy market until 2030--A critical survey of selected scenarios," Energy Policy, Elsevier, vol. 39(2), pages 812-825, February.
  • Handle: RePEc:eee:enepol:v:39:y:2011:i:2:p:812-825
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    3. Karel Janda & Jan Malek & Lukas Recka, 2017. "Influence of Renewable Energy Sources on Electricity Transmission Networks in Central Europe," Working Papers IES 2017/05, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Feb 2017.
    4. Hafezi, Reza & Akhavan, AmirNaser & Pakseresht, Saeed & Wood, David A., 2019. "A Layered Uncertainties Scenario Synthesizing (LUSS) model applied to evaluate multiple potential long-run outcomes for Iran's natural gas exports," Energy, Elsevier, vol. 169(C), pages 646-659.
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    6. Westner, Günther & Madlener, Reinhard, 2012. "Investment in new power generation under uncertainty: Benefits of CHP vs. condensing plants in a copula-based analysis," Energy Economics, Elsevier, vol. 34(1), pages 31-44.
    7. Alipour, M. & Hafezi, R. & Amer, M. & Akhavan, A.N., 2017. "A new hybrid fuzzy cognitive map-based scenario planning approach for Iran's oil production pathways in the post–sanction period," Energy, Elsevier, vol. 135(C), pages 851-864.
    8. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
    9. Prina, Matteo Giacomo & Nastasi, Benedetto & Groppi, Daniele & Misconel, Steffi & Garcia, Davide Astiaso & Sparber, Wolfram, 2022. "Comparison methods of energy system frameworks, models and scenario results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    10. Paraschiv, Florentina & Fleten, Stein-Erik & Schürle, Michael, 2015. "A spot-forward model for electricity prices with regime shifts," Energy Economics, Elsevier, vol. 47(C), pages 142-153.
    11. Fichtner, Stephan & Meyr, Herbert, 2019. "Biogas plant optimization by increasing its exibility considering uncertain revenues," Hohenheim Discussion Papers in Business, Economics and Social Sciences 07-2019, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    12. Yolanda Lechón & Cristina De La Rúa & Helena Cabal, 2018. "Impacts of Decarbonisation on the Water-Energy-Land (WEL) Nexus: A Case Study of the Spanish Electricity Sector," Energies, MDPI, vol. 11(5), pages 1-24, May.
    13. Keles, Dogan & Scelle, Jonathan & Paraschiv, Florentina & Fichtner, Wolf, 2016. "Extended forecast methods for day-ahead electricity spot prices applying artificial neural networks," Applied Energy, Elsevier, vol. 162(C), pages 218-230.
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    15. Nagl, Stephan & Fürsch, Michaela & Paulus, Moritz & Richter, Jan & Trüby, Johannes & Lindenberger, Dietmar, 2011. "Energy policy scenarios to reach challenging climate protection targets in the German electricity sector until 2050," Utilities Policy, Elsevier, vol. 19(3), pages 185-192.

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    Energy scenarios Energy demand CO2-emissions;

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