Title :
Wind power forecasting considering wind turbine condition
Author :
Pei Yan;Qian Zheng;Chen Niya
Author_Institution :
School of Instrument Science and Opto-electronics Engineering, Beihang University, Beijing, China
Abstract :
In recent years, rapid growth of the wind power all around the world highlights the requirement of developing accurate wind power forecasting method. Since the wind power generation mainly relies on wind speed and wind turbine condition, a novel wind power forecasting strategy considering wind turbine condition is proposed in this paper. The proposed strategy which can predict several-hours-ahead wind power is based on wavelet method and Support Vector Machine method. Real-world dataset is adopted to evaluate the efficiency of the proposed method. Simulation results show that the proposed method can improve wind power forecasting accuracy compared with traditional forecasting strategy.
Keywords :
"Wind speed","Wind power generation","Forecasting","Wind turbines","Predictive models","Support vector machines","Wind forecasting"
Conference_Titel :
Smart Grid Technologies - Asia (ISGT ASIA), 2015 IEEE Innovative
Electronic_ISBN :
2378-8542
DOI :
10.1109/ISGT-Asia.2015.7387115