Wind speed ultra-short term prediction algorithm based on empirical mode decomposition and random forest
An empirical mode decomposition and ultra-short-term forecasting technology, applied in the field of power systems, can solve problems such as difficult acquisition of modeling data, low prediction accuracy, and difficulty in meeting actual production needs with traditional algorithms, and achieve insensitivity to abnormal data and generalization capabilities strong effect
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[0023] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.
[0024] An ultra-short-term wind speed prediction algorithm based on empirical mode decomposition and random forest of the present invention obtains components of different time scales by decomposing historical real wind speed data to train the prediction model. The wind speed data at the moment predicts the wind speed at the next moment, and the prediction result of the wind speed at the next moment is obtained; the specific implementation steps of the method are as follows:
[0025] Step S1: Obtain the historical wind speed data of the wind power plant, and the wind speed sampling frequency is once every 10 minutes to form a wind speed time series;
[0026] Step S2: Use the law to screen the bad data in the historical wind speed data and remove them, the formula is as follows:
[0027]
[0028] In the formula, X b is the bth wind sp...
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