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

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.