Short-term wind speed prediction method based on SSA-HMD-CNNSVM model

Abstract

The invention relates to the field of short-term wind speed prediction, and discloses a short-term wind speed prediction method based on SSA-HMD-CNNSVM model. The method includes: firstly, utilizing singular spectrum analysis (SSA) to reduce noise and extract trend information of original wind speed data; and then, carrying out deep decomposition on the wind speed data by using mixed mode decomposition, then, predicting each wind speed sub-layer by using a convolutional support vector machine, and finally, carrying out superposition on prediction results of all components, thereby obtaining afinal wind speed prediction result. Compared with a common signal preprocessing mode, noise reduction and deep decomposition processing on the wind speed time sequence can effectively reduce the influence of random fluctuation of the wind speed time sequence on a prediction result, and the accuracy and precision of wind speed prediction are greatly improved. Meanwhile, the CNNSVM can combine the advantages of a single model convolutional neural network and a support vector machine, so that the wind speed prediction method has strong generalization capability and robustness, and can be appliedto wind power plant wind speed prediction on a large scale.

Description

technical field [0001] The invention relates to a short-term wind speed prediction method based on an SSA-HMD-CNNSVM ​​model, and belongs to the technical field of ultra-short-term wind speed prediction. Background technique [0002] With the increasingly serious destruction of the global ecological environment and climate warming, countries around the world have begun to continuously develop new energy technologies to solve this problem. As a renewable and clean energy, wind power has received more and more attention worldwide. . However, the wind speed generated in nature will greatly affect the wind power generation of wind farms, and the change of wind speed is often highly uncontrollable and random. In order to reduce the impact of wind energy generated by wind farms on the operation of the power grid and ensure the power supply quality of the power grid, how to implement reliable and accurate prediction of wind speed in wind farms becomes very important, and it is als...

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Problems solved by technology

[0006] The technical problem to be solved by the present invention is: how to eliminate the interference of random fluctuating noise of wind speed time series, and further improve the accuracy and precision of wind speed prediction

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