APPLICATION OF A KALMAN FILTER FOR IMPROVING WIND AND SOLAR IRRADIANCE FORECASTS FOR THE RENEWABLE INDUSTRY
MeteoGroup has developed a Kalman filter for correcting the type of systematic errors described above. Kalman filtering as a means for post-processing numerical weather prediction model output has been around for several decades. Traditionally, Kalman filters have been mainly applied on weather parameters that have errors that are normally distributed. However, the current work will show that this filtering technique is also successful in removing systematic errors in wind and solar irradiance forecasts.
A recursive Kalman filter does not require the storage of large training data sets. The system is ‘self-learning' and will adjust automatically if NWP models are upgraded or local conditions at the site of interest change.