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Design of wind farm layout using ant colony algorithm

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  • Eroğlu, Yunus
  • Seçkiner, Serap Ulusam

Abstract

The wind is a clean, abundant and entirely renewable source of energy. Large wind farms are being built around the world as a cleaner way to generate electricity, but operators are still searching for more efficient wind farm layouts to maximize wind energy capture. This paper presents an ant colony algorithm for maximizing the expected energy output. The algorithm considers wake loss, which can be calculated based on wind turbine locations, and wind direction. The proposed model is illustrated with three different scenarios of the wind speed and its direction distribution of the windy site and, comparing to evolutionary strategy algorithm available in literature. The results show that the ant colony algorithm performs better than existing strategy, in terms of maximum values of expected energy output and wake loss.

Suggested Citation

  • Eroğlu, Yunus & Seçkiner, Serap Ulusam, 2012. "Design of wind farm layout using ant colony algorithm," Renewable Energy, Elsevier, vol. 44(C), pages 53-62.
    • Handle: RePEc:eee:renene:v:44:y:2012:i:c:p:53-62
    DOI: 10.1016/j.renene.2011.12.013
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    References listed on IDEAS

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    1. Emami, Alireza & Noghreh, Pirooz, 2010. "New approach on optimization in placement of wind turbines within wind farm by genetic algorithms," Renewable Energy, Elsevier, vol. 35(7), pages 1559-1564.
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    5. Socha, Krzysztof & Dorigo, Marco, 2008. "Ant colony optimization for continuous domains," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1155-1173, March.
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    Cited by:

    1. Chen, Kaixuan & Lin, Jin & Qiu, Yiwei & Liu, Feng & Song, Yonghua, 2022. "Joint optimization of wind farm layout considering optimal control," Renewable Energy, Elsevier, vol. 182(C), pages 787-796.

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