Wind Power Prediction Model Based on ARMA and Improved BP-ANN
2014 ◽
Vol 1008-1009
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pp. 183-187
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In order to improve the prediction accuracy of wind power, this research is based on time series and improved BP-ANN algorithm. The basic idea is described as follows: wind speed forecasting model is established by using time series method; wind speed-wind power model is built by utilising improved BP-ANN algorithm; wind speed data from time series forecasting is used as input of neural network model, and the prediction results for wind power are obtained. In order to analyse the availability of wind power prediction model, the mean absolute error and correlation coefficient are compared to analyse the predictions results. The results show that the prediction model can effectively improve the forecasting accuracy of wind power.
2013 ◽
Vol 392
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pp. 622-627
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2021 ◽
Vol 838
(1)
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pp. 012001
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2015 ◽
Vol 733
◽
pp. 893-897
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