Optimal design of direct-driven PM wind generator applying parallel computing genetic algorithm

Optimal design of the direct-driven PM wind generator, coupled with F.E.A(finite element analysis) and genetic algorithm(GA), has been performed to maximize the annual energy production(AEP) over the whole wind speed characterized by the statistical model of wind speed distribution. Internet distrib...

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Published in2007 International Conference on Electrical Machines and Systems (ICEMS) pp. 763 - 768
Main Authors Hochang Jung, Cheol-Gyun Lee, Sung-Chin Hahn, Sang-Yong Jung
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2007
Subjects
Algorithm design and analysis
Character generation
Coupled mode analysis
Distributed computing
Genetic algorithms
Internet
Parallel processing
Performance analysis
Wind energy generation
Wind speed
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Abstract Optimal design of the direct-driven PM wind generator, coupled with F.E.A(finite element analysis) and genetic algorithm(GA), has been performed to maximize the annual energy production(AEP) over the whole wind speed characterized by the statistical model of wind speed distribution. Internet distributed computing is proposed for the real world and complex optimization such as optimal design of direct-driven PM wind generator. Particularly, the parallel computing via internet web service has been applied to loose excessive computing times for optimization.
AbstractList Optimal design of the direct-driven PM wind generator, coupled with F.E.A(finite element analysis) and genetic algorithm(GA), has been performed to maximize the annual energy production(AEP) over the whole wind speed characterized by the statistical model of wind speed distribution. Internet distributed computing is proposed for the real world and complex optimization such as optimal design of direct-driven PM wind generator. Particularly, the parallel computing via internet web service has been applied to loose excessive computing times for optimization.
Author Hochang Jung
Sung-Chin Hahn
Cheol-Gyun Lee
Sang-Yong Jung
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  surname: Hochang Jung
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  organization: Department of Electrical Engineering, Dong-A University, Busan, Korea
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  surname: Cheol-Gyun Lee
  fullname: Cheol-Gyun Lee
  organization: Department of Electrical Engineering, Dong-Eui University, Busan, Korea
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  surname: Sung-Chin Hahn
  fullname: Sung-Chin Hahn
  organization: Department of Electrical Engineering, Dong-A University, Busan, Korea
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  surname: Sang-Yong Jung
  fullname: Sang-Yong Jung
  email: syjung@dau.ac.kr
  organization: Department of Electrical Engineering, Dong-A University, Busan, Korea
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Snippet Optimal design of the direct-driven PM wind generator, coupled with F.E.A(finite element analysis) and genetic algorithm(GA), has been performed to maximize...
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SubjectTerms Algorithm design and analysis
Character generation
Coupled mode analysis
Distributed computing
Genetic algorithms
Internet
Parallel processing
Performance analysis
Wind energy generation
Wind speed
Title Optimal design of direct-driven PM wind generator applying parallel computing genetic algorithm
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