Neural Network for Wind Power Generation with Compressing Function
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.
S. Li et al., "Neural Network for Wind Power Generation with Compressing Function," Neural Networks, 1997. International Conference on Neural Networks, vol. 1, pp. 115-120, Institute of Electrical and Electronics Engineers (IEEE), Jan 1997.
The definitive version is available at https://doi.org/10.1109/ICNN.1997.611648
IEEE International Conference on Neural Networks (1997: Jun. 9-12, Houston, TX)
Electrical and Computer Engineering
International Standard Book Number (ISBN)
Article - Conference proceedings
© 1997 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
01 Jan 1997