Offshore wind speed load predicting based on GA-SVM

Abstract

The accurate measurement of the effective wind speed is the basis of the wind generation system operation. The effective wind speed cannot be directly measured accurately. Because offshore wind farm is a three-dimensional time-varying environment, the wind speed distribution is different on the plane of blade rotation in the wind generation system. This paper uses support vector machine with genetic algorithm (GA-SVM) to estimate the effective wind speed. The simulation results show that this model has high prediction accuracy, which the mean error of the training data can reach 0.5689 m/s. This model can improve the control capability of the wind generation system, when the wind speed changes in a wide range. © 2013 Springer-Verlag.