Wind power day-ahead prediction with cluster analysis of NWP.

The selection of training data for establishing a model directly affects the prediction precision. Wind power has the characteristic of daily similarity. The corresponding meteorological data also has the characteristic of daily similarity. This paper proposes a new model with cluster analysis of the numerical weather prediction information. The similar day with the predicted day is searched as training sample to a generalized regression neural network model. The numerical weather prediction data and actual wind power data from a wind farm are used in this study to test the model. The prediction results show that correct cluster analysis method is a useful tool in day-ahead wind power prediction. [ABSTRACT FROM AUTHOR]