Real and reactive power flow allocation in deregulated power system utilizing genetic-support vector machine technique

摘要: This paper presents a technique to allocate the real and reactive power flow in deregulated system environment by incorporating hybridization of Genetic Algorithm Least Squares Support Vector Machine (Genetic-SVM). The idea is use GA find optimal values hyper-parameters LS-SVM adapt supervised learning approach train model. manipulation proportional sharing method (PSM) utilized as teacher. Based on converged load followed PSM for allocation procedures, description inputs outputs training data are created. Genetic-SVM model will learn identify which generators supplying loads. In addition, equivalent transmission be discussed tracing methodology together with concept virtual both methods. this paper, 5- bus 25-bus southern Malaysia used show effectiveness proposed method. comparison other also given.