Wind speed prediction method and system for wind farm based on wavelet analysis

Abstract

The invention relates to a wind power station wind speed prediction method based on wavelet analysis and a system thereof. The method comprises the following steps: according to a specific prediction time interval, determining an input and an output variable of a prediction model; reading a historical wind speed value and correcting an incomplete point in the historical wind speed value so as to acquire a training sample value sequence of a wind speed prediction model; carrying out rapid wavelet decomposition to the training sample value sequence so as to acquire an approximation detail component value sequence; establishing the wind speed prediction model according to the approximation detail component value sequence so as to carry out the wind speed prediction. According to the wind power station wind speed prediction method based on the wavelet analysis and the system of the invention, through the wavelet decomposition, the training sample value sequence is decomposed into different layers according to a scale so that a trend term, a period term and a random term are separated. Each layer is individually analyzed and predicted and finally the corresponding prediction value can be obtained through reconstruction. By using the method, any prediction interval can be selected according to different demands. The wind speed prediction which is many steps ahead and has high precision can be performed.

Description

technical field [0001] The present invention relates to a wind speed prediction method and system for a wind farm, and more specifically, to a wind speed prediction method and system for a wind farm based on wavelet analysis. Background technique [0002] Wind power, as one of the most competitive power generation methods in the short term, has the advantages of being renewable, pollution-free, occupying less land, short construction period, flexible investment, high level of automation, and fewer management personnel. However, wind does not exist all the time, it mainly depends on the change of air flow, so wind energy is a random energy source with low density. The amount of energy generated by it is unstable, severely restricted by geographical location, and the conversion efficiency is low. [0003] my country has a vast territory, a long coastline, and abundant wind energy resources. With the continuous development of my country's wind power industry, the total instal...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved by the present invention is that the prediction of wind speed in the prior art mainly depends on the physical prediction model, which has a large amount of calculation, a high error accumulation rate, and requires professional maintenance, which cannot meet the needs of wind power companies for short-term wind energy forecasting. In order to provide a method and system for forecasting wind speed in wind farms based on wavelet analysis.

Images