Method for predicting wind speed of wind power plant at short term

Abstract

The invention discloses a method for predicting the wind speed of a wind power plant at a short term. The method includes the following steps that wind speed data in a period of time are acquired and reduced into a time sequence for analytical prediction; a carpet traversal search method is adopted, and based on a dynamic cubic exponential smoothing prediction method, dynamic smoothing coefficients are determined according to the criterion of the minimum error sum of squares; the determined dynamic smoothing coefficients and the dynamic cubic exponential smoothing method are utilized to conduct one-step or multi-step prediction; the rest is conducted in the same way, new historical data are acquired, the smoothing coefficients are updated, and the later wind speed prediction continues to be conducted. According to the method for predicting the wind speed of the wind power plant at the short term, the characteristics of local historical wind speed are comprehensively considered, and the prediction effect is good.

Description

technical field [0001] The invention relates to the technical field of wind power generation, in particular to a short-term wind speed prediction method for a wind farm based on an adaptive dynamic cubic exponential smoothing prediction model. Background technique [0002] Judging from the development of distributed power in recent years, wind power has undoubtedly become the most promising new energy due to the maturity of its technology and the reduction of power generation costs. The output of wind turbines has strong randomness, which is determined by the randomness of wind speed. Therefore, the forecasting research on wind speed has become an indispensable part of studying the output of wind power generation system. [0003] At present, some experts and scholars at home and abroad have proposed many wind speed prediction methods, such as artificial neural network method, Kalman filter method, wavelet transform method, autoregressive moving average (ARMA) modeling metho...

AI Technical Summary

Problems solved by technology

These methods have good applications in some specific fields, but they do not consider the influence of historical data in different time periods on the prediction results.

[0004] The existing wind speed prediction methods for wind farms can have an error of 25%-40%. The accuracy of wind speed prediction is affected by the violent fluctuation of wind speed and sends a relatively large error. It is impossible to accurately predict the wind speed, which affects the accuracy of wind speed prediction, especially in different places. , even if the same method is used to predict, the prediction accuracy is not the same

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