Non-dominated Sorting Particle Swarm Optimization Based Fault Section Estimation in Radial Distribution Systems

Abstract

This paper addresses the fault section estimation as a real multi-objective optimization problem. Non-dominated sorting particle swarm optimization (NSPSO) based on the concept of NSGA-II, has been proposed to alleviate the problems associated with conventional multi objective evolutionary algorithms. An analytical fault analysis and iterative procedure to get the multiple estimates of fault location and NSPSO based optimization algorithm to further nail down the exact fault location has been presented. The techniques fully consider loads, laterals and customer trouble calls in radial distribution systems, take into account for all types of fault. Due to the presence of various conflicting objective functions, the fault location task is a multi-objective, optimization problem. In the proposed technique, the multi-objective nature of the fault section estimation problem is retained using non-dominated sorting approach. As a result, the proposed methodology is generalized enough to be applicable to any radial distribution systems. The applicability of the proposed methodology has been demonstrated through detail simulation studies on standard test systems. Results are used to reduce the possible number of potential fault location which helps and equips the operators to locate the fault accurately.