Optimal design of permanent magnet wind generator for maximum annual energy production

Ho Chang Jung; Sang Yong Jung; Sung Chin Hahn; Cheol Gyun Lee

Optimal design of permanent magnet wind generator for maximum annual energy production

Ho Chang Jung, Sang Yong Jung, Sung Chin Hahn, Cheol Gyun Lee

Department of Electronic and Electrical Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

The wind generators have been installed with high output power to increase the energy production and efficiency. Hence, Optimal design of the direct-driven PM wind generator, coupled with F.E.M(Finite Element Method) 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. Particularly, the parallel computing via internet web service has been applied to loose excessive computing times for optimization. The results of the optimal design of Surface-Mounted Permanent Magnet Synchronous Generator(SPMSG) are compared with each other candidates to verify the usefulness of the maximizing AEP model.

Original language	English
Pages (from-to)	2109-2115
Number of pages	7
Journal	Transactions of the Korean Institute of Electrical Engineers
Volume	56
Issue number	12
State	Published - Dec 2007

Keywords

Annual Energy Production(AEP)
Finite element method(F.E.M)
Genetic Algorithm(GA)
Parallel computing
PM wind generator

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "Optimal design of permanent magnet wind generator for maximum annual energy production",

abstract = "The wind generators have been installed with high output power to increase the energy production and efficiency. Hence, Optimal design of the direct-driven PM wind generator, coupled with F.E.M(Finite Element Method) 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. Particularly, the parallel computing via internet web service has been applied to loose excessive computing times for optimization. The results of the optimal design of Surface-Mounted Permanent Magnet Synchronous Generator(SPMSG) are compared with each other candidates to verify the usefulness of the maximizing AEP model.",

keywords = "Annual Energy Production(AEP), Finite element method(F.E.M), Genetic Algorithm(GA), Parallel computing, PM wind generator",

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year = "2007",

month = dec,

language = "English",

volume = "56",

pages = "2109--2115",

journal = "Transactions of the Korean Institute of Electrical Engineers",

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AU - Jung, Ho Chang

AU - Jung, Sang Yong

AU - Hahn, Sung Chin

AU - Lee, Cheol Gyun

PY - 2007/12

Y1 - 2007/12

N2 - The wind generators have been installed with high output power to increase the energy production and efficiency. Hence, Optimal design of the direct-driven PM wind generator, coupled with F.E.M(Finite Element Method) 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. Particularly, the parallel computing via internet web service has been applied to loose excessive computing times for optimization. The results of the optimal design of Surface-Mounted Permanent Magnet Synchronous Generator(SPMSG) are compared with each other candidates to verify the usefulness of the maximizing AEP model.

AB - The wind generators have been installed with high output power to increase the energy production and efficiency. Hence, Optimal design of the direct-driven PM wind generator, coupled with F.E.M(Finite Element Method) 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. Particularly, the parallel computing via internet web service has been applied to loose excessive computing times for optimization. The results of the optimal design of Surface-Mounted Permanent Magnet Synchronous Generator(SPMSG) are compared with each other candidates to verify the usefulness of the maximizing AEP model.

KW - Annual Energy Production(AEP)

KW - Finite element method(F.E.M)

KW - Genetic Algorithm(GA)

KW - Parallel computing

KW - PM wind generator

UR - https://www.scopus.com/pages/publications/37249045623

M3 - Article

AN - SCOPUS:37249045623

SN - 1975-8359

VL - 56

SP - 2109

EP - 2115

JO - Transactions of the Korean Institute of Electrical Engineers

JF - Transactions of the Korean Institute of Electrical Engineers

IS - 12

ER -

Optimal design of permanent magnet wind generator for maximum annual energy production

Abstract

Keywords

UN SDGs

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