Wind Speed Prediction with high efficiency convex optimization Support Vector Machine

Accurate prediction of wind speed is one of the most valuable ways to solve the problems of electricity security, stability and quality which are caused by the wind energy production for power system. This article constitutes a wind speed prediction with high efficiency convex optimization support vector machine(SVM). The principal component analysis is utilized to determine the outcome of the major factors affecting the wind speed. With increasing number of the parameters in SVM structure, particle swarm optimization (PSO) is incorporated to optimizing the parameters. Detailed analysis and simulation using the real time wind power plant data demonstrate the effectiveness of the SVM forecasting approach.