Optimal design of direct-driven PM wind generator using adaptive univariate dynamic encoding algorithm for searches (uDEAS)

被引:3
作者
Jung, Sang-Yong [2 ]
Lee, Dongsu [2 ]
Choi, Min-Goo [1 ]
Kim, Jong-Wook [1 ]
机构
[1] Dong A Univ, Dept Elect Engn, Pusan, South Korea
[2] Sungkyunkwan Univ, Sch Informat & Commun Engn, Suwon, South Korea
基金
新加坡国家研究基金会;
关键词
Permanent magnet generator; optimization methods; wind power generation; univariate dynamic encoding algorithm for searches; gradient information; PARAMETER-IDENTIFICATION; OPTIMIZATION; SYSTEM;
D O I
10.3233/JAE-2011-1403
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, optimal design of the direct-driven PM wind generator, combined with uDEAS (univariate Dynamic Encoding Algorithm for Searches) and FEA (Finite Element Analysis), has been performed to maximize the Annual Energy Production (AEP) over the whole operating wind speed. In particular, an adaptive scheme of arranging search variable sequence in uDEAS is newly proposed according to variable's measured gradient to cost function. The proposed adaptive scheme is embedded in uDEAS and validated through two test functions, and the modified uDEAS is applied to optimal design of the direct-driven PM wind generator. With the comparable quality of the attained solution, uDEAS enormously reduces computation time when compared with Genetic Algorithm (GA) implemented by the parallel computing method.
引用
收藏
页码:167 / 180
页数:14
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