GA design for efficiency optimization of a superconducting generator

ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501) Pub Date : 2001-08-18 DOI:10.1109/ICEMS.2001.970631

Sangil Han, I. Muta, T. Hoshino, T. Nakamura

引用次数: 2

Abstract

This paper deals with a design method for the efficiency optimization of 223 MVA class superconducting generator. In consideration of the electrical characteristics based on electromagnetic analysis, GA (genetic algorithm), which has been successfully applied to various design problems in electric machines and devices, is used as an approach method of the optimized design with some variables and constraints. The results designed by this method are found to be reasonable and effective as compared with those obtained by the methods of trial and error until now.

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超导发电机效率优化的遗传算法设计

本文研究了223 MVA级超导发电机效率优化的设计方法。考虑到基于电磁分析的电气特性，将遗传算法作为一种具有一定变量和约束条件的优化设计的方法，遗传算法已成功地应用于电机器件的各种设计问题。与目前用试错法得到的结果相比，该方法设计的结果是合理有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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ICEMS'2001. Proceedings of the Fifth International Conference on Electrical Machines and Systems (IEEE Cat. No.01EX501)

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