Wind farm layout optimization using genetic algorithm and its application to Daegwallyeong wind farm

This paper proposes a new wind farm layout optimization methodology based on a genetic algorithm by implementing a simulation model considering wake effect. This method consists of (1) batch optimization to efficiently obtain a rough wind farm layout for the maximum energy production in a large scal...

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Published in:	JMST Advances Vol. 1; no. 4; pp. 249 - 257
Main Authors:	Park, Jeong Woo, An, Bo Sung, Lee, Yoon Seung, Jung, Hyunsuk, Lee, Ikjin
Format:	Journal Article
Language:	English
Published:	Seoul Korean Society of Mechanical Engineers 01.12.2019
Subjects:	Control Dynamical Systems Engineering Industrial and Production Engineering Letters Mechanical Engineering Vibration Wind farms Jensen’s model Daegwallyeong wind farm Genetic algorithm Optimization
ISSN:	2524-7905, 2524-7913
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Abstract	This paper proposes a new wind farm layout optimization methodology based on a genetic algorithm by implementing a simulation model considering wake effect. This method consists of (1) batch optimization to efficiently obtain a rough wind farm layout for the maximum energy production in a large scale, and (2) post-optimization to obtain a refined layout to further improve the energy production in a small scale. The proposed two-step optimization enables to efficiently optimize wind farm layout and thus can be applicable to layout optimization of large-scale wind farms. A case study with the actual Daegwallyeong wind farm shows that wake loss is improved by 2.3% point after the proposed layout optimization which means about 2.5% more energy production compared with the existing layout.
AbstractList	This paper proposes a new wind farm layout optimization methodology based on a genetic algorithm by implementing a simulation model considering wake effect. This method consists of (1) batch optimization to efficiently obtain a rough wind farm layout for the maximum energy production in a large scale, and (2) post-optimization to obtain a refined layout to further improve the energy production in a small scale. The proposed two-step optimization enables to efficiently optimize wind farm layout and thus can be applicable to layout optimization of large-scale wind farms. A case study with the actual Daegwallyeong wind farm shows that wake loss is improved by 2.3% point after the proposed layout optimization which means about 2.5% more energy production compared with the existing layout.
Author	Lee, Yoon Seung Park, Jeong Woo An, Bo Sung Lee, Ikjin Jung, Hyunsuk
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SubjectTerms	Control Dynamical Systems Engineering Industrial and Production Engineering Letters Mechanical Engineering Vibration
Title	Wind farm layout optimization using genetic algorithm and its application to Daegwallyeong wind farm
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