An Adaptive Strategy-incorporated Integer Genetic Algorithm for Wind Farm Layout Optimization

Tao Zheng, Haotian Li, Houtian He, Zhenyu Lei, Shangce Gao*

*この論文の責任著者

研究成果: ジャーナルへの寄稿学術論文査読

4 被引用数 (Scopus)

抄録

Energy issues have always been one of the most significant concerns for scientists worldwide. With the ongoing over exploitation and continued outbreaks of wars, traditional energy sources face the threat of depletion. Wind energy is a readily available and sustainable energy source. Wind farm layout optimization problem, through scientifically arranging wind turbines, significantly enhances the efficiency of harnessing wind energy. Meta-heuristic algorithms have been widely employed in wind farm layout optimization. This paper introduces an Adaptive strategy-incorporated Integer Genetic Algorithm, referred to as AIGA, for optimizing wind farm layout problems. The adaptive strategy dynamically adjusts the placement of wind turbines, leading to a substantial improvement in energy utilization efficiency within the wind farm. In this study, AIGA is tested in four different wind conditions, alongside four other classical algorithms, to assess their energy conversion efficiency within the wind farm. Experimental results demonstrate a notable advantage of AIGA.

本文言語英語
ページ(範囲)1522-1540
ページ数19
ジャーナルJournal of Bionic Engineering
21
3
DOI
出版ステータス出版済み - 2024/05

ASJC Scopus 主題領域

  • バイオテクノロジー
  • バイオエンジニアリング
  • 生物理学

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