Ultra-short-term wind power prediction method based on composite data source autoregression model
An autoregressive model, ultra-short-term forecasting technology, applied in forecasting, data processing applications, instruments, etc., can solve the problems of wind power, photovoltaic power generation fluctuations, and transmission network charging power fluctuations.
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[0048] The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.
[0049] A super-short-term prediction method of wind power based on composite data derived from regression model, including input data to obtain autoregressive model parameters,
[0050] And inputting the input data required for wind power prediction into the autoregressive model determined according to the parameters of the above-mentioned autoregressive model to obtain the prediction result; wherein the input data to obtain the autoregressive model parameters specifically includes step 101, inputting the basic data for model training,
[0051] Step 102, using the residual variance map method to determine the order of the autoregressive model AR(p),
[0052] Step 10...
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