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| A Novel Combined Model for Wind Power Forecasting Based on Maximum Entropy Principle |
| Xia Dong, Wu Junyong, He Dian, Song Honglei, Ji Luyu |
| Beijing Jiaotong University Beijing 100044 China |
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Abstract On the basis of individual forecasting models, a novel combined short time forecasting model based on the maximum entropy principle is proposed. Taking the forecasting values and the historical forecasting error distributions produced by all the adopted individual power forecasting models as constraints, the new combined model calculates the weight coefficient of adopted models based on maximum entropy principle, and then the wind power forecasting results could be obtained. The wind power forecasting results of different wind turbines in different times show that the integrated model forecasting is better than individual and combined models’, and wind speed forecasting errors range between 15% and 20%, the wind power forecasting errors range between 25% and 30% and the proposed method is practical.
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Received: 11 October 2010
Published: 07 March 2014
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2011, Vol. 26 
