Optimization algorithm of corrosion diagnosis for grounding grid

Substation grounding system is to ensure the power system operation safe and reliable. It is important to examine the state of grounding. In this paper, optimization algorithm is used for grounding grid fault diagnosis. The method that used combination of rotating and encouraging each location and incentives, many measurements, utilized the fact that the corrosion resistances must be increased, established a new constrained optimization model which target is minimum energy. Combined with the analysis of cultural algorithm and Particle Swarm Optimization based on the idea, a local random search operator is employed to construct the knowledge structure of the belief space, which is used to guide the evolution process of the advanced algorithm, by doing so, the efficiency and optimize performance optimization have been improved, so to solve and has better global search capability. Analysis and test show that the algorithm is feasible and effective.