IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i9p2347-d355472.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/9/2347/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/9/2347/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mahler, Valentin & Girard, Robin & Kariniotakis, Georges, 2022. "Data-driven structural modeling of electricity price dynamics," Energy Economics, Elsevier, vol. 107(C).
    2. Jahns, Christopher & Podewski, Caroline & Weber, Christoph, 2020. "Supply curves for hydro reservoirs – Estimation and usage in large-scale electricity market models," Energy Economics, Elsevier, vol. 87(C).
    3. 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).
    4. Christopher Jahns & Caroline Podewski & Christoph Weber, "undated". "Supply Curves for Hydro Reservoirs - Estimation and Usage in Large-Scale Electricity Market Models," EWL Working Papers 1901, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    5. Seljom, Pernille & Tomasgard, Asgeir, 2017. "The impact of policy actions and future energy prices on the cost-optimal development of the energy system in Norway and Sweden," Energy Policy, Elsevier, vol. 106(C), pages 85-102.
    6. 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.
    7. Valentin Mahler & Robin Girard & Georges Kariniotakis, 2021. "Data-driven Structural Modeling of Electricity Price Dynamics," Working Papers hal-03445396, HAL.
    8. Rintamäki, Tuomas & Siddiqui, Afzal S. & Salo, Ahti, 2020. "Strategic offering of a flexible producer in day-ahead and intraday power markets," European Journal of Operational Research, Elsevier, vol. 284(3), pages 1136-1153.
    9. Christopher Kath & Florian Ziel, 2018. "The value of forecasts: Quantifying the economic gains of accurate quarter-hourly electricity price forecasts," Papers 1811.08604, arXiv.org.
    10. Erik Heilmann & Janosch Henze & Heike Wetzel, 2021. "Machine learning in energy forecasts with an application to high frequency electricity consumption data," MAGKS Papers on Economics 202135, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    11. William Paul Bell & John Foster, 2017. "Using solar PV feed-in tariff policy history to inform a sustainable flexible pricing regime to enhance the diffusion of energy storage and electric vehicles," Journal of Bioeconomics, Springer, vol. 19(1), pages 127-145, April.
    12. Mwampashi, Muthe Mathias & Nikitopoulos, Christina Sklibosios & Konstandatos, Otto & Rai, Alan, 2021. "Wind generation and the dynamics of electricity prices in Australia," Energy Economics, Elsevier, vol. 103(C).
    13. Graabak, Ingeborg & Wu, Qiuwei & Warland, Leif & Liu, Zhaoxi, 2016. "Optimal planning of the Nordic transmission system with 100% electric vehicle penetration of passenger cars by 2050," Energy, Elsevier, vol. 107(C), pages 648-660.
    14. Stefanos Tampakakis & Dimitrios Zafirakis, 2023. "On the Value of Emerging, Day-Ahead Market Related Wind-Storage Narratives in Greece: An Early Empirical Analysis," Energies, MDPI, vol. 16(8), pages 1-19, April.
    15. Bianco, Vincenzo & Scarpa, Federico, 2018. "Impact of the phase out of French nuclear reactors on the Italian power sector," Energy, Elsevier, vol. 150(C), pages 722-734.
    16. Farahmand, H. & Doorman, G.L., 2012. "Balancing market integration in the Northern European continent," Applied Energy, Elsevier, vol. 96(C), pages 316-326.
    17. Bouwmeester, Maaike C. & Scholtens, Bert, 2017. "Cross-border investment expenditure spillovers in European gas infrastructure," Energy Policy, Elsevier, vol. 107(C), pages 371-380.
    18. Bouwmeester, Maaike & Scholtens, Bert, 2014. "Cross-border spillovers from European gas infrastructure investment," Research Report 14028-EEF, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    19. Bell, William Paul & Wild, Phillip & Foster, John & Hewson, Michael, 2017. "Revitalising the wind power induced merit order effect to reduce wholesale and retail electricity prices in Australia," Energy Economics, Elsevier, vol. 67(C), pages 224-241.
    20. Katarzyna Maciejowska, 2022. "A portfolio management of a small RES utility with a Structural Vector Autoregressive model of German electricity markets," Papers 2205.00975, arXiv.org.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2347-:d:355472. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.