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

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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.

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Acknowledgements

This research was supported by Energy Cloud R&D Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT (No. 2016006843).

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Authors and Affiliations

  1. Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon, South Korea

    Jeong Woo Park & Ikjin Lee

  2. Daejeon Science High School, 46, Gwahak-ro, Yuseong-gu, Daejeon, South Korea

    Bo Sung An, Yoon Seung Lee & Hyunsuk Jung

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  1. Jeong Woo Park
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  2. Bo Sung An
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  3. Yoon Seung Lee
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Correspondence to Ikjin Lee.

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Park, J.W., An, B.S., Lee, Y.S. et al. Wind farm layout optimization using genetic algorithm and its application to Daegwallyeong wind farm. JMST Adv. 1, 249–257 (2019). https://doi.org/10.1007/s42791-019-00026-z

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  • DOI: https://doi.org/10.1007/s42791-019-00026-z

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