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http://dx.doi.org/10.5391/JKIIS.2010.20.5.710

Development of Wind Speed Estimator for Wind Turbine Generation System  

Kim, Byung-Moon (군산대학교 전자정보공학부)
Kim, Sung-Ho (군산대학교 전자정보공학부)
Song, Hwa-Chang (군산대학교 전자정보공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.20, no.5, 2010 , pp. 710-715 More about this Journal
Abstract
As wind has become one of the fastest growing renewable energy sources, the key issue of wind energy conversion systems is how to efficiently operate the wind turbines in a wide range of wind speeds. The wind speed has a huge impact on the dynamic response of wind turbine. For this purpose, many control algorithms are in need for a method to measure wind speed to increase performance. Unfortunately, no accurate measurement of the effective wind speed is online available from direct measurements, which means that it must be estimated in order to make such control methods applicable in practice. In this paper, a new method based on Kalman filter and artificial neural network is presented for the estimation of the effective wind speed. To verify the performance of the proposed scheme, some simulation studies are carried out.
Keywords
Renewable energy source; wind speed; Kalman filter; artificial neural network; estimation of effective wind speed;
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