A hybrid wind power forecasting model based on data mining and wavelets analysis

2016 ◽  
Vol 127 ◽  
pp. 208-225 ◽  
Author(s):  
R. Azimi ◽  
M. Ghofrani ◽  
M. Ghayekhloo
Keyword(s):  
Data Mining ◽  
Wind Power ◽  
Forecasting Model ◽  
Wind Power Forecasting ◽  
Model Based ◽  
Wavelets Analysis ◽  
Power Forecasting

An improved wind power forecasting model based on eliminating outliers

2016 ◽  
Vol 40 (1) ◽  
pp. 50-58 ◽  
Author(s):  
Jingxin Guo ◽  
Xiao-Yu Zhang ◽  
Wenling Jang ◽  
Hongqing Wang
Keyword(s):  
Wind Power ◽  
Forecasting Model ◽  
Wind Power Forecasting ◽  
Model Based ◽  
Power Forecasting

scholarly journals Short-Term Wind Power Forecasting Model based on ICA-BP Neural Network

2014 ◽  
Vol 8 (1) ◽  
Author(s):  
Zi-Cheng Lan ◽  
Yuan-Biao Zhang ◽  
Jing Zhang ◽  
Xin-Guang Lv
Keyword(s):  
Neural Network ◽  
Wind Power ◽  
Bp Neural Network ◽  
Forecasting Model ◽  
Short Term ◽  
Wind Power Forecasting ◽  
Model Based ◽  
Power Forecasting

Wind Power Forecasting Model Based on Extreme Learning Machine and Time series

2021 ◽  
Author(s):  
Ibtissame Mansoury ◽  
Dounia El Bourakadi ◽  
Ali Yahyaouy ◽  
Jaouad Boumhidi
Keyword(s):  
Time Series ◽  
Wind Power ◽  
Extreme Learning Machine ◽  
Forecasting Model ◽  
Wind Power Forecasting ◽  
Model Based ◽  
Learning Machine ◽  
Power Forecasting

Wind Power Combination Forecasting Model Based on Drift

2014 ◽  
Vol 953-954 ◽  
pp. 522-528 ◽  
Author(s):  
Quan Cheng Lyu ◽  
Wen Ying Liu ◽  
Dan Dan Zhu ◽  
Wei Zhou Wang ◽  
Xu Shan Han ◽  
...  
Keyword(s):  
Wind Power ◽  
Forecasting Model ◽  
Wind Power Forecasting ◽  
Model Based ◽  
Forecasting Methods ◽  
Forecast Precision ◽  
Combination Forecasting ◽  
Wind Power Forecast ◽  
Combination Forecasting Model ◽  
Power Forecasting

As different wind power forecasting methods provide different information and differ in forecast precision, the combined wind power forecasting model is employed to better forecast wind power. Wind power combination forecasting model based on drift and complementarity of different single wind power forecasting models is proposed in this paper. The combination forecasting model provides a new solution to wind power forecast. Finally a practical example is given to show that wind power combination forecasting model based on drift can improve forecasting precision and is effective in practice.

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