Optimal Allocation of Test Poles For Grounding Grids Diagnosis Based on Genetic Algorithm

In order to make all of the branches of a grounding grid testable, test poles are suggested to implant on some nodes of the grounding grid. A hierarchical simplification model of grounding grids is proposed, based on which, the testability of the branches is evaluated by an iteration approach. A genetic algorithm based test poles allocation optimization approach is presented. The purpose is to make all of the branches clear with the minimum number of test poles. The coding of chromosomes and the ways to avoid of the unfeasible solutions in the processes of the initial population forming, crossover and mutation operation are discussed. Taking the disturbance in the test into consideration with a Monte-Carlo method, the most robust scheme can be selected from the feasible individuals worked out by the genetic algorithm based approach. A grounding grid with sixty branches is used as an example to show the feasibility of the proposed approach.