A dataset provided for the "Machine Learning Wind Turbine Power Curve Prediction" challenge. See https://hack.opendata.ch/project/471
The accurate prediction of the power production of a wind turbine at a particular site is important in both the planning and operation phases, but the standard power curve binning method is not specific to the atmospheric conditions at the site and can therefore be inaccurate. The goal of this challenge is to develop a machine learning algorithm in order to improve site-specific power curve prediction accuracy. For this, you will be provided with a dataset of 8'000 simulated powers of the NREL 5MW reference wind turbine from the simulation tool ASHES at a range of different atmospheric conditions. This new algorithm could be developed into a tool for wind farm operators in a future innovation project.