Photovoltaic generation power prediction method based on self-learning composite data source autoregression model
A photovoltaic power generation, autoregressive model technology, applied in forecasting, data processing applications, instruments, etc., can solve problems such as photovoltaic power generation uncertainty, uncontrollable power grid security, stability and economic operation
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[0050] 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.
[0051] A method for forecasting photovoltaic power generation based on self-learning composite data derived from a regression model, including inputting data to obtain autoregressive model parameters,
[0052] And input the input data required for photovoltaic power generation prediction into the autoregressive model determined according to the parameters of the above autoregressive model to obtain the prediction result; perform post-evaluation on the prediction result, that is, analyze the error between the predicted value and the measured value, such as the prediction error Greater than the maximum error allowed, then re-carry out the autoregressive model AR (p) or...
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