Synthetic Photovoltaic and Wind Power Forecasting Data

@article{Vogt2022SyntheticPA,
  title={Synthetic Photovoltaic and Wind Power Forecasting Data},
  author={Stephan Vogt and Jens Schreiber and Bernhard Sick},
  journal={ArXiv},
  year={2022},
  volume={abs/2204.00411}
}
Photovoltaic and wind power forecasts in power systems with a high share of renewable energy are essential in several applications. These include stable grid operation, profitable power trading, and forward-looking system planning. However, there is a lack of publicly available datasets for research on machine learning-based prediction methods. This paper provides an openly accessible time series dataset with realistic synthetic power data. Other publicly and non-publicly available datasets… 

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