The Electrical and mechanical simulation and computer-aided geometric optimization of high voltage post-insulator based on RBF neural network and finite element method

Abstract

The High-voltage post insulators are widely used in power systems. The electrical and mechanical properties of post insulators are closely related to the operation stability of power system. Based on the three-dimensional finite element method (FEM), the mechanical and electrical properties of post insulator are modeled and analyzed. The results show that the maximum electric field strength of the insulator is located on the surface of the voltage-equalizing ring near the high voltage side, and the first principal stress maximum value of 150MPa is mainly concentrated on flange supporting side. The PSO-RBF hybrid algorithm is proposed to optimize nonlinear inversion structural parameters of the post insulator. The results show that the PSO-RBF neural network has good effect on the nonlinear fitting mapping of the original finite element calculation data, and the algorithm has good convergence. The mechanical and electrical properties of the post insulators and the configuration of the post insulator-related voltage sharing ring and shielding ring are obtained, which can provide the theoretical basis for the insulation structure design and fittings configuration of UHV and below post composite insulators.