Multi‐Objective Optimization Design of Vacuum Interrupter Structure Based on Improved Artificial Jellyfish Search Algorithm

Abstract

An improved multi‐objective optimization method based on artificial jellyfish search algorithm is proposed to solve the multivariable and multi‐objective optimization problem of vacuum interrupter with mutual coupling of structural parameters and mutual restriction of performance indexes. The finite element model of 40.5 kV/31.5kA vacuum interrupter is established. The structural parameters of seven important parts such as contact diameter and contact sheet thickness in vacuum interrupter are taken as optimization variables. The optimization objective is to maximize the longitudinal magnetic field strength and minimize the conductor resistance at the peak breaking short‐circuit current of vacuum interrupter. The artificial jellyfish search algorithm is improved on the population position initialization strategy and the population mutation cross‐update strategy. The Pareto front solution of the structural parameters of the vacuum interrupter is obtained by the joint simulation of finite element analysis and numerical calculation software. Finally, the multi‐parameter and multi‐objective optimization design of vacuum interrupter structure is realized. The comprehensive performance index is introduced into the optimal parameter group of jellyfish on the Pareto front. Under the constraint of weight variables, the optimal structural parameters of contact system are obtained. The axial magnetic induction intensity of the optimized vacuum interrupter contact is increased by 13.2%, and the conductor resistance is reduced by 25.4%. The comprehensive performance of vacuum interrupter is improved by 17.8%, and the stability and reliability of the power system are further improved. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.