文章基本信息

标题：Estimation of the wind turbine yaw error by support vector machines
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作者：Nida Sheibat-Othman ; Sami Othman ; Raoaa Tayari 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2015
卷号：48
期号：30
页码：339-344
DOI：10.1016/j.ifacol.2015.12.401
语种：English
出版社：Elsevier
摘要：AbstractWind turbine yaw error information is of high importance in controlling wind turbine power and structural load. Normally used wind vanes are imprecise. In this work, the estimation of yaw error in wind turbines is studied using support vector machines for regression (SVR). As the methodology is data-based, simulated data from a high fidelity aero-elastic model is used for learning. The model simulates a variable speed horizontal-axis wind turbine composed of three blades and a full converter. Both partial load (blade angles fixed at 0 deg) and full load zones (active pitch actuators) are considered. The validation step is done under different conditions of wind shear, speed and direction, giving good estimation results.
关键词：KeywordsWind turbinesupport vector machinesregression