Big multi-step wind speed forecasting model based on secondary decomposition, ensemble method and error correction algorithm

2018 ◽  
Vol 156 ◽  
pp. 525-541 ◽  
Author(s):  
Hui Liu ◽  
Zhu Duan ◽  
Feng-ze Han ◽  
Yan-fei Li
Keyword(s):  
Wind Speed ◽  
Error Correction ◽  
Ensemble Method ◽  
Forecasting Model ◽  
Correction Algorithm ◽  
Wind Speed Forecasting ◽  
Model Based ◽  
Error Correction Algorithm

An ultra-short-term wind speed forecasting model based on time scale recognition and dynamic adaptive modeling

2022 ◽  
Vol 135 ◽  
pp. 107502
Author(s):  
Zhao Zhen ◽  
Gang Qiu ◽  
Shengwei Mei ◽  
Fei Wang ◽  
Xuemin Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Time Scale ◽  
Forecasting Model ◽  
Short Term ◽  
Adaptive Modeling ◽  
Wind Speed Forecasting ◽  
Model Based

scholarly journals Artificial Combined Model Based on Hybrid Nonlinear Neural Network Models and Statistics Linear Models—Research and Application for Wind Speed Forecasting

2018 ◽  
Vol 10 (12) ◽  
pp. 4601 ◽  
Author(s):  
Yuewei Liu ◽  
Shenghui Zhang ◽  
Xuejun Chen ◽  
Jianzhou Wang
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Wind Speed ◽  
Wind Farm ◽  
Linear Models ◽  
Search Algorithm ◽  
Forecasting Model ◽  
Neural Network Models ◽  
Wind Speed Forecasting ◽  
Model Based

The use of wind power is rapidly increasing as an important part of power systems, but because of the intermittent and random nature of wind speed, system operators and researchers urgently need to find more reliable methods to forecast wind speed. Through research, it is found that the time series of wind speed demonstrate not only linear features but also nonlinear features. Hence, a combined forecasting model based on an improved cuckoo search algorithm optimizes weight, and several single models—linear model, hybrid nonlinear neural network, and fuzzy forecasting model—are developed in this paper to provide more trend change for time series of wind speed forecasting besides improving the forecasting accuracy. Furthermore, the effectiveness of the proposed model is proved by wind speed data from four wind farm sites and the results are more reliable and accurate than comparison models.

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