Impact of wind and solar production on electricity prices: Quantile regression approach

Linh Phuong Catherine Do, Štefan Lyócsa and Peter Molnár

Journal of the Operational Research Society, 2019, vol. 70, issue 10, 1752-1768

Abstract: We study the impact of fuel prices, emission allowances, demand, past prices, wind and solar production on hourly day-ahead electricity prices in Germany over the period from January 2015 until June 2018. Working within a linear regression, ARX-EGARCH and quantile regression framework we compare how different pricing factors influence the mean and quantiles of the electricity prices. Contrary to the existing literature, we find that short-term price fluctuations on the fuel markets and emission allowances have little effect on the electricity prices. We also find that day-of-the-week as well as monthly effects have significant impact on the electricity prices in Germany and should not be ignored in model specifications. Three main factors are found to drive extreme prices: price persistence, expected demand and expected wind production. Our findings contribute to understanding of extreme price movements, which can be used in pricing models and hedging strategies.

Date: 2019
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DOI: 10.1080/01605682.2019.1634783

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