Neas Energy trades power on behalf of asset owners (e.g. wind and solar farms) and large scale consumers. As the liberalization of the power markets only started approximately 15 years ago the academic research in the field is all fairly new and a lot of issues is left to be solved. Simultaneously, the large inflow of renewable energy, combined with changes in the infrastructure of the market, makes the data environment ever changing.
This presentation will describe how statistics is applied at Neas Energy to solve issues at the frontier of power analytics. This ranges from purely descriptive setups to spot trends, over forecasting of fundamentals to forecasting of power prices and system imbalances (where the demand and supply are not equal). Lastly an in-depth example will be discussed, focusing on my current research topic: simulating German day-ahead prices applying Lasso methods.