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The effect of wind and solar power forecasts on day-ahead and intraday electricity prices in Germany

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  • Gürtler, Marc
  • Paulsen, Thomas

Abstract

This study analyzes the effects of wind and solar power generation forecasts on electricity prices. Converse to the existing empirical literature in this area, we apply a panel data analysis to control for endogeneity due to unobserved heterogeneity. We use a dataset with 24 daily observations of day-ahead and intraday prices from 2010 to 2016, and we apply a fixed effects regression under consideration of robust Driscoll-Kraay standard errors. A noteworthy element of the regression model is the simulation-based design of a variable indicating the power generation technology that is price-determining at a certain point in time. In this context, we differentiate between the fuel types coal, gas, and others, to model the nonlinear price behavior for a varying demand. For 2016, we find price dampening effects of both wind and solar power of approximately 0.6 €/MWh per additional GWh of feed-in. Along with the rapidly increasing shares of wind and solar power of the total power generation during the last years, their price dampening effect has declined since 2013, due to a drop in fuel prices. Another finding is that a reduction in forecasting errors on the power generation from wind and solar, and smoothing of the cyclical demand would lead to a decreased price volatility.

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  • Gürtler, Marc & Paulsen, Thomas, 2018. "The effect of wind and solar power forecasts on day-ahead and intraday electricity prices in Germany," Energy Economics, Elsevier, vol. 75(C), pages 150-162.
  • Handle: RePEc:eee:eneeco:v:75:y:2018:i:c:p:150-162
    DOI: 10.1016/j.eneco.2018.07.006
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    2. Yasir Alsaedi & Gurudeo Anand Tularam & Victor Wong, 2020. "Assessing the Effects of Solar and Wind Prices on the Australia Electricity Spot and Options Markets Using a Vector Autoregression Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 10(1), pages 120-133.
    3. Meus, Jelle & De Vits, Sarah & S'heeren, Nele & Delarue, Erik & Proost, Stef, 2021. "Renewable electricity support in perfect markets: Economic incentives under diverse subsidy instruments," Energy Economics, Elsevier, vol. 94(C).
    4. Marcel Kremer & Rüdiger Kiesel & Florentina Paraschiv, 2020. "Intraday Electricity Pricing of Night Contracts," Energies, MDPI, vol. 13(17), pages 1-14, September.
    5. Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Day-Ahead vs. Intraday—Forecasting the Price Spread to Maximize Economic Benefits," Energies, MDPI, vol. 12(4), pages 1-15, February.
    6. Macedo, Daniela Pereira & Marques, António Cardoso & Damette, Olivier, 2020. "The impact of the integration of renewable energy sources in the electricity price formation: is the Merit-Order Effect occurring in Portugal?," Utilities Policy, Elsevier, vol. 66(C).
    7. Sergei Kulakov & Florian Ziel, 2019. "The Impact of Renewable Energy Forecasts on Intraday Electricity Prices," Papers 1903.09641, arXiv.org, revised Nov 2019.
    8. Ilkay Oksuz & Umut Ugurlu, 2019. "Neural Network Based Model Comparison for Intraday Electricity Price Forecasting," Energies, MDPI, vol. 12(23), pages 1-14, November.
    9. Maciejowska, Katarzyna & Nitka, Weronika & Weron, Tomasz, 2021. "Enhancing load, wind and solar generation for day-ahead forecasting of electricity prices," Energy Economics, Elsevier, vol. 99(C).
    10. Kolb, Sebastian & Dillig, Marius & Plankenbühler, Thomas & Karl, Jürgen, 2020. "The impact of renewables on electricity prices in Germany - An update for the years 2014–2018," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    11. Micha{l} Narajewski & Florian Ziel, 2020. "Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories," Papers 2005.01365, arXiv.org, revised Aug 2020.
    12. Katarzyna Maciejowska & Weronika Nitka & Tomasz Weron, 2019. "Enhancing load, wind and solar generation forecasts in day-ahead forecasting of spot and intraday electricity prices," HSC Research Reports HSC/19/08, Hugo Steinhaus Center, Wroclaw University of Technology.
    13. Sam Wilkinson & Michele John & Gregory M. Morrison, 2021. "Rooftop PV and the Renewable Energy Transition; a Review of Driving Forces and Analytical Frameworks," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    14. Narajewski, Michał & Ziel, Florian, 2020. "Ensemble forecasting for intraday electricity prices: Simulating trajectories," Applied Energy, Elsevier, vol. 279(C).

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    More about this item

    Keywords

    Merit-order effect; Renewable energy sources; Wind; Solar; Ramping costs; Forecasting errors;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C59 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Other
    • Q20 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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