Power prediction method based on wind-solar hybrid model
A power forecasting and wind-solar hybrid technology, which is applied in photovoltaic modules, photovoltaic power generation, wind power generation, etc., can solve the problems of low accuracy and achieve the effects of improving prediction accuracy, wide engineering application value, and simplifying prediction methods
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[0016] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0017] First, establish an accurate BP neural network model for wind-solar hybrid power prediction. In this embodiment, a three-layer feed-forward network is used as an example to illustrate, as shown in figure 1 shown. Select the measured historical meteorological data of more than one month, the output power of wind farms and photovoltaic power stations as the data for network training, and preprocess them (such as checking the rationality and completeness of the selected data, Supplement and correction with abnormal data, and perform normalization processing), establish a database for training the BP network model, and then input the data in the database into the established BP neural network structure for training, and verify the prediction model And correction, finally get the trained BP neural network model.
[0018] Then comprehensively consider vari...
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