Support vector regression machine wind speed combination forecast method with interpolation being smoothed and optimized

The invention discloses a support vector regression machine wind speed combination forecast method with interpolation being smoothed and optimized. The method comprises the following steps of: step I, preprocessing obtained initial data of wind speed at height of a hub of a fan in a wind power station, analyzing sample data, and selecting a time domain for smoothing and optimizing the interpolation; step II, carrying out interpolation smoothing and optimizing on a wind speed time sequence in the selected time domain; step III, carrying out phase space reconstruction on the wind speed sequence which is subjected to interpolation smoothing and optimizing so as to form a sample set required by modeling; and step IV, establishing a corresponding support vector regression machine wind speed combination forecast model with the interpolation being smoothed and optimized by utilizing the sample set obtained from the step III. According to the method, higher forecast accuracy can be obtained compared with a general counting method under the same data condition, the knowability and the controllability of wind power are increased, the grid-connected development of large-scale wind power is favored, and the benefits of the wind power station and a power dispatch department are guaranteed.