Wind Power Prediction with Machine Learning

@inproceedings{Treiber2016WindPP,
  title={Wind Power Prediction with Machine Learning},
  author={Nils Andr{\'e} Treiber and Justin Heinermann and Oliver Kramer},
  booktitle={Computational Sustainability},
  year={2016}
}
Better predictionmodels for the upcoming supply of renewable energy are important to decrease the need of controlling energy provided by conventional power plants. Especially for successful power grid integration of the highly volatile wind power production, a reliable forecast is crucial. In this chapter, we focus on shortterm wind power prediction and employ data from the National Renewable Energy Laboratory (NREL), which are designed for a wind integration study in the western part of the… CONTINUE READING

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