A New Protection Scheme for Distribution Network with Distributed Generations Using Radial Basis Function Neural Network

Abstract

Distributed generations (DGs) have been increasingly connected on the distribution networks that will have the unfavorable impact on the traditional protection methods because the distribution system is no longer radial in nature and is not supplied by a single main power source. This paper presents a new automated protection method using radial basis function neural network (RBFNN) for a distribution system with DG units. In the proposed method, the fault type is determined first by normalizing the fault currents of the main source. For implementing fault location considering various types of faults, two staged RBFNNs have been developed. The first RBFNN is used for determining the fault distance from each power source and the second RBFNN is used for identifying the faulty line. To isolate the fault, another RBFNN has been developed for determining which circuit breakers (CBs) that must be open or close. Several case studies have been made to verify the accuracy of the method to specify the fault location and protection of the system in distribution networks with DGs. The predicted results showed that the proposed RBFNN based protection method can accurately determine the location of faults and isolate the faulted line in the test power system.