Modeling of generator leading phase ability based on ant colony optimization and support vector machine

System operating overvoltage can be controlled through the generator leading phase operation effectively. However, generator leading phase operation is a nonlinear process. This paper presents that modeling of generator leading phase capacity based on ant colony optimization and support vector machine. Ant colony optimization can improve the efficiency of the operation and generalization ability of support vector machine effectively. This paper puts the active and reactive power as the input vectors of the SVM data points, and puts the generators power-angle and system or the stator voltage as the output vectors of the SVM data points. This paper used two generators as instance simulation model which rated power are 10MW and 300MW. The ACO-SVM algorithm has stronger generalization ability through comparative analysis, and ACO-SVM algorithm has the value in engineering.