We analyse the drivers of European Power Exchange (EPEX) retail electricity prices between 2012 and early 2022 using machine learning. The agnostic random forest approach that we use is able to reduce in-sample root mean square errors (RMSEs) by around 50% when compared to a standard linear...

We use Monte Carlo analysis to examine the potential of increased renewable generation to provide a hedge against variability in energy prices and costs. Fuel costs, electricity demand and wind generation are allowed to vary and a unit commitment and economic dispatch algorithm is employed to...

With greater penetration of renewable generation, the uncertainty faced in electricity markets has increased substantially. Conventionally, generators are assigned a pre-dispatch quantity in advance of real time, based on estimates of uncertain quantities. Expensive real time adjustments then...

Renewable energy such as wind or solar power currently contributes a large share to the total German electricity supply as a result of the German energy transition. This paper presents an empirical analysis of how power shocks resulting from intermittent renewable supply affect forward premiums...