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Future wind and solar power market values in Germany — Evidence of spatial and technological dependencies?

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  • Eising, Manuel
  • Hobbie, Hannes
  • Möst, Dominik

Abstract

Achieving ambitious climate targets entails an extensive utilisation of renewable energy sources. However, due to weather-dependent fluctuations, generation from variable renewable energy (VRE) sources is characterised by significantly lower market values in comparison to conventional technologies, reinforced by a decline in electricity prices. This development poses interesting questions as to its drivers and to what extent market values of wind and solar power can be influenced by the design of electricity markets. Against this background, a scenario-based analysis is conducted to trace the future development of market values using endogenously derived electricity prices considering different regional and technological VRE diversification strategies and investments into VRE technologies on a myopic basis. The results show a continued decline in market values with increasing regional discrepancies indicating a growing importance of interregional interdependencies for assessing the profitability of VRE. Furthermore, from a system point of view, a more distributed allocation of onshore wind capacities to contend with declining market values does not always prove to stabilise market values by facilitating a more constant feed-in pattern, contrary to expectation. Finally, replacing onshore with offshore wind energy appears to be beneficial as it can lead to an overall increase in the market values of offshore, onshore as well as PV generation technologies compared to other mitigation strategies. This result raise interesting questions about the systemic economic value of offshore wind despite its higher LCOE in the context of market integration of VRE.

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  • Eising, Manuel & Hobbie, Hannes & Möst, Dominik, 2020. "Future wind and solar power market values in Germany — Evidence of spatial and technological dependencies?," Energy Economics, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:eneeco:v:86:y:2020:i:c:s0140988319304359
    DOI: 10.1016/j.eneco.2019.104638
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    4. Klie, Leo & Madlener, Reinhard, 2022. "Optimal configuration and diversification of wind turbines: A hybrid approach to improve the penetration of wind power," Energy Economics, Elsevier, vol. 105(C).
    5. Dujardin, Jérôme & Schillinger, Moritz & Kahl, Annelen & Savelsberg, Jonas & Schlecht, Ingmar & Lordan-Perret, Rebecca, 2022. "Optimized market value of alpine solar photovoltaic installations," Renewable Energy, Elsevier, vol. 186(C), pages 878-888.
    6. Simshauser, Paul, 2021. "Renewable Energy Zones in Australia's National Electricity Market," Energy Economics, Elsevier, vol. 101(C).
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    10. Simshauser, P., 2021. "Renewable Energy Zones in Australia’s National Electricity Market," Cambridge Working Papers in Economics 2119, Faculty of Economics, University of Cambridge.
    11. Patrick Rausch & Michał Suchanek, 2021. "Socioeconomic Factors Influencing the Prosumer’s Investment Decision on Solar Power," Energies, MDPI, vol. 14(21), pages 1-10, November.
    12. Thomas Mobius & Mira Watermeyer & Oliver Grothe & Felix Musgens, 2023. "Enhancing Energy System Models Using Better Load Forecasts," Papers 2302.11017, arXiv.org.
    13. Petersen, Claire & Reguant, Mar & Segura, Lola, 2024. "Measuring the impact of wind power and intermittency," Energy Economics, Elsevier, vol. 129(C).
    14. Lynch, Muireann & Longoria, Genaro & Curtis, John, 2021. "Market design options for electricity markets with high variable renewable generation," Utilities Policy, Elsevier, vol. 73(C).
    15. Misconel, S. & Leisen, R. & Mikurda, J. & Zimmermann, F. & Fraunholz, C. & Fichtner, W. & Möst, D. & Weber, C., 2022. "Systematic comparison of high-resolution electricity system modeling approaches focusing on investment, dispatch and generation adequacy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
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    More about this item

    Keywords

    Market value; Market integration of renewables; Technological diversification; Geographical diversification; Spatial value factor distribution;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • D40 - Microeconomics - - Market Structure, Pricing, and Design - - - General

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