Neural network for wind power generation with compressing function

Shuhui Li; Don C. Wunsch; Edgar O'Hair; Michael G. Giesselmann

doi:10.1109/ICNN.1997.611648

Neural network for wind power generation with compressing function

Shuhui Li, Don C. Wunsch, Edgar O'Hair, Michael G. Giesselmann

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

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.

Original language	English
Title of host publication	1997 IEEE International Conference on Neural Networks, ICNN 1997
Pages	115-120
Number of pages	6
DOIs	https://doi.org/10.1109/ICNN.1997.611648
State	Published - 1997
Event	1997 IEEE International Conference on Neural Networks, ICNN 1997 - Houston, TX, United States Duration: Jun 9 1997 → Jun 12 1997

Publication series

Name	IEEE International Conference on Neural Networks - Conference Proceedings
Volume	1
ISSN (Print)	1098-7576

Conference

Conference	1997 IEEE International Conference on Neural Networks, ICNN 1997
Country	United States
City	Houston, TX
Period	06/9/97 → 06/12/97

Access to Document

10.1109/ICNN.1997.611648

Link to publication in Scopus

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Cite this

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title = "Neural network for wind power generation with compressing function",

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.",

author = "Shuhui Li and Wunsch, {Don C.} and Edgar O'Hair and Giesselmann, {Michael G.}",

year = "1997",

doi = "10.1109/ICNN.1997.611648",

language = "English",

isbn = "0780341228",

series = "IEEE International Conference on Neural Networks - Conference Proceedings",

pages = "115--120",

booktitle = "1997 IEEE International Conference on Neural Networks, ICNN 1997",

}

Li, S, Wunsch, DC, O'Hair, E & Giesselmann, MG 1997, Neural network for wind power generation with compressing function. in 1997 IEEE International Conference on Neural Networks, ICNN 1997., 611648, IEEE International Conference on Neural Networks - Conference Proceedings, vol. 1, pp. 115-120, 1997 IEEE International Conference on Neural Networks, ICNN 1997, Houston, TX, United States, 06/9/97. https://doi.org/10.1109/ICNN.1997.611648

Neural network for wind power generation with compressing function. / Li, Shuhui; Wunsch, Don C.; O'Hair, Edgar; Giesselmann, Michael G.

1997 IEEE International Conference on Neural Networks, ICNN 1997. 1997. p. 115-120 611648 (IEEE International Conference on Neural Networks - Conference Proceedings; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Wunsch, Don C.

AU - O'Hair, Edgar

AU - Giesselmann, Michael G.

PY - 1997

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N2 - 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.

AB - 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.

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