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

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.

Keywords:

• Price modelling
• wind
• solar
• renewables
• quantile regression

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 A brief conference paper of Hagfors et al. (2016c) is more closely related to our study, but our analysis is much more detailed in terms of models specifications, models employed, discussion and we utilize new data which have no overlap with their dataset.

2 The pairwise correlation between exceedance of prices below the 5th percentile (1 if yes, 0 otherwise) and the share of energy produced from renewable sources is at 0.40. The corresponding correlation for the exceedance of prices above the 95^th percentile (1 if yes, 0 otherwise) is -0.21.

3 The residuals from ARX(7,0)-EGARCH(1,1) show no traces of serial dependence and all the parameters of this model are significant.

4 The overall number of observations in not even due to the day-light saving times and occasional missing observation.

5 An exception was found for three price series, where the Canova and Hansen’s (1995) test indicated a seasonal-unit root, but the remaining tests no.

Additional information

Funding

Peter Molnár acknowledges the support provided by the Czech Grant Agency under Grant No. 19-26812X.