A turbine hub height wind speed consensus forecasting system

Accurate forecasts of hub height wind speed are critical for the prediction of power produced by any particular turbine. Much of the research in the area has focused on the generation of a wind speed forecast using one Numerical Weather Prediction model and the refinements to that model to improve forecasts within the boundary layer. This paper describes a consensus forecast system that acts as a post-processing system to an ensemble of input forecasts. The system ingests and processes meteorological data (observations, models, statistical data, climatology data, etc.) and produces optimized meteorological forecasts at user-defined forecast sites (e.g., wind turbines) and forecast lead times. In order to achieve this goal, the system generates independent forecasts from each of the data sources using a variety of statistical forecasting techniques. A single consensus forecast from the set of individual forecasts is generated at each user-defined site based on a processing method that takes into account the recent skill of each forecast module.

This consensus system provides a forecast that reduces the average error of any input forecast and leads to a more accurate power forecast. This consensus forecast system is a critical part of the wind energy forecast system developed for Xcel Energy by the National Center for Atmospheric Research (NCAR).