Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering

Petroula Louka (1) , Georges Galanis (1) , Nils Siebert (2) , Georges Kariniotakis (2) , Petros Katsafados (1) , George Kallos (1) , Iaonnis Pytharoulis (1)

1 Division of Applied Physics, Atmospheric Modelling and Weather Forecasting Group
2 CEP - Centre Énergétique et Procédés

This paper studies the application of Kalman filtering as a post-processing method in numerical predictions of wind speed. Two limited-area atmospheric models have been employed, with different options/capabilities of horizontal resolution, to provide wind speed forecasts. The application of Kalman filter to these data leads to the elimination of any possible systematic errors, even in the lower resolution cases, contributing further to the significant reduction of the required CPU time. The potential of this method in wind power applications is also exploited. In particular, in the case of wind power prediction, the results obtained showed a remarkable improvement in the model forecasting skill.

Mots clés: Wind speed forecasting; Kalman filtering; Wind power forecasting

Domaines: Sciences de l'ingénieur [physics]; Energétique

Petroula Louka, Georges Galanis, Nils Siebert, Georges Kariniotakis, Petros Katsafados, et al.. Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering. Journal of Wind Engineering and Industrial Aerodynamics, 2008, 96 (12), pp.Pages 2348-2362. ⟨10.1016/j.jweia.2008.03.013⟩. ⟨hal-00505993⟩