Optimization of Shielding Electrode and Inner Shielding Structure for UHV Oil-gas Bushings with Improved Hybrid Algorithm Combining Particle Swarm Optimization and Back-Propagation Neural Network

Abstract

With the development of prototype for UHV oil-gas bushings, E-field distribution around bushing end and structure optimization for shielding electrode is an important issue to be studied. The basic principles and processes of hybrid algorithm combining particle swarm optimization and back-propagation neural network (PSO-BP algorithm) has been discussed in this paper. The optimization capability and accuracy of proposed algorithm has been verified with continuous explicit function. The structure optimization of shielding electrode has been conducted using PSO-BP algorithm. The study shows that PSO-BP algorithm can seek extreme point of testing function exactly, and jump over trap of local optimal solution; three-dimensional full model of bushing is needed in E-field distribution calculation; PSO-BP algorithm has found the best structure parameters of shielding electrode, with which more even E-field distribution can be obtained, and maximum electric strength can be reduced by 64.9%, moreover, the computing time is about 75.2% less than traditional PSO algorithm. The study results have been applied in bushing prototype manufacture which has passed through all testing experiments. The optimization method proposed in the paper can also be used in optimization design for other complex insulation structures.