DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

Tan Zheng; Song Xueguan; Cao WenpingLiu ZhengTong Yibin

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DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

机译：DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

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摘要

This paper presents a surrogate-model-based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine's previous operational performance, the DFIG's stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization-based surrogate optimization techniques are used in conjunction with the finite element method to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

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来源
《IEEE Transactions on Energy Conversion》 |2015年第3期|1154-1162|共9页
作者
Tan Zheng; Song Xueguan; Cao WenpingLiu ZhengTong Yibin;
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作者单位

Beijing Jiao Tong Univ, Beijing 100044, Peoples R China;

Dalian Univ Technol, Dept Mech Engn, Dalian 116024, Peoples R China;

Queens Univ Belfast, Belfast BT7 1NN, Antrim, North IrelandNewcastle Univ, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类电工技术;
关键词
Doubly fed induction generator; operating conditions; particle swarm optimization; power loss; rewinding; surrogate model; wind power generation;

DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

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