Application of Immune-Based Optimization Method for Fault-Section Estimation in a Distribution System

In this paper, an immune algorithm (IA)-based optimization approach for the fault-section estimation of a distribution system is proposed. To apply the method to solve this estimation problem, each section of power system model can be considered as an antibody. Through the immunology evolution, an antibody that most fits the antigen of concern becomes the solution. An affinity calculation has been employed in this computation process to measure the combination intensity. As this method can operate the population of antibodies simultaneously, the process stagnation can be better prevented. The proposed approach has been tested on Taiwan Power System (Taipower) through the utility data. Test results demonstrated the feasibility and effectiveness of the method for the applications.