Neural Network for Wind Power Generation with Compressing Function

Author

Shuhui Li
Donald C. Wunsch, Missouri University of Science and TechnologyFollow
Edgar O'Hair
Michael G. Giesselmann

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.

Recommended Citation

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

Meeting Name

IEEE International Conference on Neural Networks (1997: Jun. 9-12, Houston, TX)

Department(s)

Electrical and Computer Engineering

International Standard Book Number (ISBN)

0000780341228

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 1997 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jan 1997