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

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10.1109/ICNN.1997.611648

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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",

note = "null ; Conference date: 09-06-1997 Through 12-06-1997",

}

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

TY - GEN

T1 - Neural network for wind power generation with compressing function

AU - Li, Shuhui

AU - Wunsch, Don C.

AU - O'Hair, Edgar

AU - Giesselmann, Michael G.

PY - 1997

Y1 - 1997

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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U2 - 10.1109/ICNN.1997.611648

DO - 10.1109/ICNN.1997.611648

M3 - Conference contribution

AN - SCOPUS:0030674698

SN - 0780341228

SN - 9780780341227

T3 - IEEE International Conference on Neural Networks - Conference Proceedings

SP - 115

EP - 120

BT - 1997 IEEE International Conference on Neural Networks, ICNN 1997

Y2 - 9 June 1997 through 12 June 1997

ER -

Neural network for wind power generation with compressing function

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