Ultra-short-term wind power prediction method based on autoregression moving average model
An autoregressive sliding, ultra-short-term forecasting technology, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as power transmission network charging power fluctuations, wind power, photovoltaic power generation output fluctuations, etc.
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[0055] 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.
[0056] An ultra-short-term prediction method for wind power based on an autoregressive moving average model, including inputting data to obtain autoregressive moving average model parameters;
[0057] The input data required for wind power prediction is input into the autoregressive moving average model determined according to the parameters of the above-mentioned autoregressive moving average model to obtain the prediction result.
[0058] The operation of power systems including large-scale wind power depends on huge and accurate data sets, and if wind power forecasting can effectively integrate and utilize these data, the prediction accuracy can be effectively imp...
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