基于引力搜索算法的金属氧化物避雷器分级环设计优化

H. Illias, Chea Zern Hong, K. Aramugam, H. Mokhlis, A. M. Ariffin, Mohd Fairouz Mohd Yousof
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引用次数: 0

摘要

高压金属氧化物避雷器(MOA)用于保护电力系统免受过电压的影响。通过安装分级环,可以使MOA周围的电场均匀。如何合理设计低电场级配环,对设计具有重要意义。本课题在COMSOL Multiphysics软件中建立了150kv MOA模型。改变分级环尺寸,研究其对MOA周围电场的影响。研究发现,分级环的尺寸对避雷器周围电场的大小有较大的影响。采用重力搜索算法(GSA)对MOA模型的分级环进行了优化设计。通过与其他优化方法的比较结果表明,与遗传算法(GA)、粒子群优化算法(PSO)和模拟退火算法(SA)相比,GSA是最适合MOA分级环优化设计的方法。这是因为它产生的电场大小最小,收敛速度最快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization of Grading Ring Design for Metal Oxide Arrester Using Gravitational Search Algorithm
A high voltage metal oxide arrester (MOA) is used to protect power system against overvoltages. The electric field surrounding the MOA can be made uniform by installing a grading ring. It is important to have a proper way to design a grading ring with low electric field of the design. In this project, a model of 150 kV MOA was developed in COMSOL Multiphysics software. The grading ring dimensions were varied to study their effects on the electric field surrounding MOA. It was found that the grading ring dimensions strongly influence the electric field magnitude surrounding the arrester. Gravitational search algorithm (GSA) were used to obtain the optimum design of the grading ring for the MOA model. Comparison of the results between GSA and other optimization methods shows that GSA is the most suitable method to obtain an optimum design of the grading ring for MOA compared to genetic algorithm (GA), particle swarm optimization (PSO) and simulated annealing (SA). This is due to it yields the lowest electric field magnitude and has the fastest convergence.
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