Comparative analysis of metaheuristics optimization techniques to parameterize fault locators for power distribution systems.

Abstract

In this paper, a comparative analysis on the use of four metaheuristics for obtaining an optimal adjustment of a fault locator based on support vector machines (SVM), is presented. This research is aimed to determine those techniques which help to obtain the best performance at the specific problem of fault location. The proposed fault locator is tested in the 34 nodes IEEE power distribution system where the average precision obtained considering the best alternatives  is  around  99%,  using  a  database  of  13824  registers  from  single  phase,  phase  to  phase,  two  phase  to  ground and three phase faults. The comparison of the parameterization alternatives shows how those metahueristics based on population have better performance that those based on trajectory, having a good performance in all of the tested situations.