A short-term wind power prediction method based on wind speed correction and spatial data enhancement is proposed. Firstly, considering the discrepancy between the wind speed data in the numerical weather prediction (NWP) and the measured wind speed, a wind speed correction strategy is developed to correct the wind speed. Secondly, the empirical orthogonal function decomposition (EOF) and hierarchical clustering methods are used to divide the wind farms into subregions and select representative wind turbines using the correlation coefficients. Finally, the wind speed information of the representative turbines is integrated to complete the spatial data enhancement session.
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