Optimization Design of Grading Ring for 220 kV Basin-type Insulator Based on Finite Element Method and Neural Network Method

Abstract

A method for optimizing the structural parameters of the grading ring was proposed for basin-type insulator in GIS. Firstly,a model of basin-type insulator was established by adopting the finite element method to calculate its electric field,hence the optimization objective of the grading ring structure was obtained. Then,the BP neural network algorithm was employed to optimize the structural parameters of the grading ring. In addition,the highly nonlinear mapping capability of the neural network is used to fit the optimization objective function with the structural parameters of the grading ring and goal,avoiding the huge calculation and large time consumption of the exhaustion method. Experimental results show that installation of the optimized grading ring to the basin-type insulator can greatly lower the maximum value of surface electric field,and apparently improve the surface electric field distribution of the basin- type insulator.