While current models for wind energy forecasting are often tailored to individual wind turbines (WTs), excluding smaller or planned installations, the new application follows a unified and scalable approach. Using a machine learning model, forecasts are generated for all European WTs according to the same principle, regardless of whether real production data are available or parameters have been custom-defined. This enables, for the first time, a flexible and cross-turbine assessment of wind energy potential.
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