Extracting relevant features to explain electricity price variations

This paper proposes to explain the variations of energy price, namely the electricity on the German market. Such price variations are described by a set of characteristics which are not totally relevant to explain the variations. We first propose to find explanations by using visual tools in order to draw some preliminary conclusions. Analysing such kind of data is usually done thanks to visual comparison by plotting the curves chronologically. In a second time, we propose to build a statistical model from data. The aim of such approach is to detail the characteristic that get involved in the solution, so that we can automatically extract the most pertinent characteristics. We apply this approach on a set of historical data (2007–2010). Obtained results show that methodology is very interesting, since the conclusion from the statistical modelling enforce the visual analysis and also add details about the explanation.