Determination of generators´ contributions to, loads in pool based power system using Least Squares Support Vector Machine

This paper attempts to allocate the generators´ contributions to loads in pool based power system by incorporating the Least Squares Support Vector Machine (LS-SVM). The idea is to use supervised learning approach to train the LS-SVM. The technique that uses proportional tree method (PTM) which is applying the convention of proportional sharing principle is utilized as a teacher. Based on converged load flow and followed by PTM for power tracing procedure, the description of inputs and outputs of the training data for the LS-SVM are created. The LS-SVM will learn to identify which generators are supplying to which loads. The proposed technique is demonstrated using IEEE 14-bus system to illustrate the effectiveness of the LS-SVM technique compared to that of the PTM. The comparison result with Artificial Neural Network (ANN) technique is also will be discussed.