An application of artificial bee colony algorithm with least squares support vector machine for real and reactive power tracing in deregulated power system

Abstract

This paper presents a new method for real and reactive power tracing in a deregulated power system by introducing the hybrid artificial bee colony (ABC) algorithm and least squares support vector machine (LS-SVM), namely as ABC-SVM. The idea is to use ABC algorithm to obtain the optimal values of regularization parameter, γ and Kernel RBF parameter, σ 2, which are embedded in LS-SVM toolbox and adopt a supervised learning approach to train the LS-SVM model. The technique that uses Superposition method is utilized as a teacher. Based on power flow solution and power tracing procedure by Superposition method, the description of input-output for training and testing data are created. The generators' contributions to real and reactive loads in the test system are expected can be traced accurately by proposed ABC-SVM model. In this paper, IEEE-14 bus system is used to illustrate the effectiveness of the proposed ABC-SVM model compared to that of Superposition method. The comparison with the cross-validation (CV) technique and other hybrid technique to obtain the hyper-parameters also has been presented in this paper.