An Hour Ahead Wind Speed Prediction by Kalman Filter

This paper proposes a trustworthy and practical approach to predict wind speed, which could be used as input to predict wind power generation. In the prediction model, we applied the variable speed wind as input of this model. Then the Gaussian noise is added to the input due to existing of noise in measuring of wind speed. Kalman filtering is used as the prediction method in this study. The parameters of shaping filter are calculated using power spectral analysis and Gauss-Markov theory. Results under different time horizon of prediction are compared with actual data and the comparison shows that the results obtained using Kalman filter is reliable. The proposed method works well for an hour ahead prediction and for short-time prediction works even better. The application of Kalman filter on wind speed prediction is implemented in MATLAB software and results are provided in this paper.