DocumentCode
313570
Title
Neural network for wind power generation with compressing function
Author
Li, Shuhui ; Wunsch, Don C. ; O´Hair, Edgar ; Giesselmann, Michael G.
Author_Institution
Dept. of Electr. Eng., Texas Tech. Univ., Lubbock, TX, USA
Volume
1
fYear
1997
fDate
9-12 Jun 1997
Firstpage
115
Abstract
The power generated by electric wind turbines changes rapidly because of the continuous fluctuation of wind speed and direction. It is important for the power industry to have the capability to estimate this changing power. In this paper, the characteristics of wind power generation are studied and a neural network is used to estimate it. We use real wind farm data to demonstrate a neural network solution for this problem, and show that the network can estimate power even in changing wind conditions
Keywords
backpropagation; feedforward neural nets; parameter estimation; power engineering computing; wind power plants; wind turbines; backpropagation; compressing function; electric wind turbines; forecasting; multilayer neural networks; power estimation; wind power generation; Meteorology; Neural networks; Poles and towers; Power generation; Power measurement; Wind energy generation; Wind farms; Wind power generation; Wind speed; Wind turbines;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks,1997., International Conference on
Conference_Location
Houston, TX
Print_ISBN
0-7803-4122-8
Type
conf
DOI
10.1109/ICNN.1997.611648
Filename
611648
Link To Document