Using neural networks to predict wind power generation

Shuhui Li, Edgar O'Hair, Michael G. Giesselmann

Research output: Contribution to conferencePaperpeer-review

4 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 predict this changing power. In this paper, the characteristics of wind power generation are studied and a neural network is used to predict it. The data from a wind farm is analyzed, and the construction of the neural network is discussed. The performance of the neural network is studied compared with measured results and is found to predict the power generated accurately and present a good approximation to the behavior of wind turbine under changing wind conditions.

Original languageEnglish
Pages415-420
Number of pages6
StatePublished - 1997
EventProceedings of the 1997 International Solar Energy Conference - Washington, DC, USA
Duration: Apr 27 1997Apr 30 1997

Conference

ConferenceProceedings of the 1997 International Solar Energy Conference
CityWashington, DC, USA
Period04/27/9704/30/97

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