Title :
Research on wind power forecasting method using phase space reconstruction and artificial neural network
Author :
Minghao, Zhao ; Dongxiang, Jiang ; Chao, Liu
Author_Institution :
Dept. of Thermal Eng., Tsinghua Univ., Beijing, China
Abstract :
In this paper, wind speed and the power generated are predicted using phase space reconstruction and artificial neural network (ANN) method. First of all, data of wind speed is preprocessed with theory of phase space reconstruction to obtain the optimal length of time series for forecasting. And then, RBF artificial neural network is used to forecast the wind speed. Finally, the output power of a wind turbine is forecasted and a relatively effective model is obtained.
Keywords :
power engineering computing; radial basis function networks; time series; wind power plants; wind turbines; RBF ANN method; artificial neural network; phase space reconstruction; power generation; time series; wind power forecasting method; wind speed forecast; wind turbine; Artificial neural networks; Chaos; Delay effects; Power engineering and energy; Predictive models; Thermal engineering; Weather forecasting; Wind energy; Wind forecasting; Wind speed; artificial neural network; phase space reconstruction; wind power forecasting;
Conference_Titel :
Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4934-7
DOI :
10.1109/SUPERGEN.2009.5348196
