Ultrashort combined predicting method for wind speed of wind power plant

Abstract

The invention relates to an ultrashort combined predicting method for wind speed of a wind power plant. Firstly, wind speed time series of the wind power plant is acquired, and data pretreatment is carried out on the series to obtain input data of a prediction system; the input data is predicted respectively by a continuous prediction model, an ARMA (Auto Regressive Moving Average) prediction model and a wavelet-neural network prediction model, and three groups of prediction values are obtained through computation; and finally the three groups of prediction values are adopted to obtain the prediction value of the wind speed in the future 0-1 hour by a combined prediction method, and the last two groups of prediction values are adopted to obtain the prediction value of the wind speed in the future 1-4 hours by the combined prediction method. The combined prediction method is adopted, useful information of each single prediction method is fully utilized, the prediction precision of the wind speed in the future 4 hours of the wind power plant is improved, and a reference is provided for reasonably scheduling a power grid.

Description

technical field [0001] The invention relates to an ultra-short-term wind speed prediction method of a wind farm in a wind power generation system, in particular to an ultra-short-term combined wind speed prediction method of a wind farm using a continuation method, an ARMA method and a wavelet-neural network method. Background technique [0002] With the large-scale integration of wind power into the grid, it has a certain impact on the safe and stable operation of the power system. Prediction of wind power or wind speed can enable the power grid dispatching department to reasonably arrange power generation plans and countermeasures, reduce system spinning reserve capacity and operating costs, and improve wind power penetration power limit and market competitiveness. [0003] Due to the influence of numerical weather forecast prediction accuracy and the lack of high-quality historical database of wind farms, medium and long-term or even 24 hours in advance wind power or wind...

AI Technical Summary

Problems solved by technology

[0012] The purpose of the present invention is to overcome the shortcomings of the prior art, aiming at the current situation that the prediction accuracy of wind speed prediction methods for wind farms in my country is relatively low, and propose a super short-term combination prediction method for wind speed in wind farms

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