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Impact of Long-Term Water Inflow Uncertainty on Wholesale Electricity Prices in Markets with High Shares of Renewable Energies and Storages

Author

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  • Heike Scheben

    (Institute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, Heßbrühlstraße 49a, 70565 Stuttgart, Germany
    Current address: Heßbrühlstraße 49a, 70565 Stuttgart, Germany.)

  • Nikolai Klempp

    (Institute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, Heßbrühlstraße 49a, 70565 Stuttgart, Germany)

  • Kai Hufendiek

    (Institute of Energy Economics and Rational Energy Use (IER), University of Stuttgart, Heßbrühlstraße 49a, 70565 Stuttgart, Germany)

Abstract

Renewable energy shares in electricity markets are increasing and therefore also require an increase in flexibility options. Conventional electricity price modelling with optimisation models in thermally dominated markets is not appropriate in markets with high shares of renewable energies and storages because price structures are not adequately represented. Previous research has already identified the impact of uncertainty in renewable energy feed-in on investment and dispatch decisions. However, we are not aware of any work that investigates the influence of uncertainties on price structures by means of optimisation models. Appropriate modelling of electricity price structures is important for investment and policy decisions. We have investigated the influence of uncertainty concerning water inflow by applying a second stage stochastic dual dynamic programming approach in a linear optimisation model using Norway as an example. We found that the influence of uncertainty concerning water inflow combined with high shares of storages has a strong impact on the electricity price structures. The identified structures are highly influenced by seasonal water inflow, electricity demand, wind, and export profiles. Additionally, they are reinforced by seasonal primary energy source prices and import prices. Incorporating uncertainties in linear optimisation models improves the price modelling and provides, to a large extent, an explanation for the seasonal patterns of Norwegian electricity market prices. The paper explains the basic pricing mechanisms in markets with high shares of storages and renewable energies which are subject to uncertainty. To identify these fundamental mechanisms, we focused on uncertainty regarding water inflow, but the basic results hold true for uncertainties regarding other renewable energies as well.

Suggested Citation

  • Heike Scheben & Nikolai Klempp & Kai Hufendiek, 2020. "Impact of Long-Term Water Inflow Uncertainty on Wholesale Electricity Prices in Markets with High Shares of Renewable Energies and Storages," Energies, MDPI, vol. 13(9), pages 1-21, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2347-:d:355472
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    References listed on IDEAS

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    1. Ward, K.R. & Green, R. & Staffell, I., 2019. "Getting prices right in structural electricity market models," Energy Policy, Elsevier, vol. 129(C), pages 1190-1206.
    2. Wolfgang, Ove & Haugstad, Arne & Mo, Birger & Gjelsvik, Anders & Wangensteen, Ivar & Doorman, Gerard, 2009. "Hydro reservoir handling in Norway before and after deregulation," Energy, Elsevier, vol. 34(10), pages 1642-1651.
    3. Spiecker, Stephan & Vogel, Philip & Weber, Christoph, 2013. "Evaluating interconnector investments in the north European electricity system considering fluctuating wind power penetration," Energy Economics, Elsevier, vol. 37(C), pages 114-127.
    4. Pape, Christian & Hagemann, Simon & Weber, Christoph, 2016. "Are fundamentals enough? Explaining price variations in the German day-ahead and intraday power market," Energy Economics, Elsevier, vol. 54(C), pages 376-387.
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    Cited by:

    1. Laura Torralba-Díaz & Christoph Schimeczek & Matthias Reeg & Georgios Savvidis & Marc Deissenroth-Uhrig & Felix Guthoff & Benjamin Fleischer & Kai Hufendiek, 2020. "Identification of the Efficiency Gap by Coupling a Fundamental Electricity Market Model and an Agent-Based Simulation Model," Energies, MDPI, vol. 13(15), pages 1-19, July.
    2. Scheben, Heike & Hufendiek, Kai, 2023. "Modelling power prices in markets with high shares of renewable energies and storages—The Norwegian example," Energy, Elsevier, vol. 267(C).
    3. Annika Gillich & Kai Hufendiek, 2022. "Asset Profitability in the Electricity Sector: An Iterative Approach in a Linear Optimization Model," Energies, MDPI, vol. 15(12), pages 1-31, June.
    4. Umut Burak Geyikci & Serkan Çınar & Fatih Mehmet Sancak, 2022. "Analysis of the Relationships among Financial Development, Economic Growth, Energy Use, and Carbon Emissions by Co-Integration with Multiple Structural Breaks," Sustainability, MDPI, vol. 14(10), pages 1-11, May.

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