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Simulated Annealing Algorithm for Wind Farm Layout Optimization: A Benchmark Study

机译:用于风电场布局优化的模拟退火算法:基准研究

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摘要

The optimal layout of wind turbines is an important factor in the wind farm design process, and various attempts have been made to derive optimal deployment results. For this purpose, many approaches to optimize the layout of turbines using various optimization algorithms have been developed and applied across various studies. Among these methods, the most widely used optimization approach is the genetic algorithm, but the genetic algorithm handles many independent variables and requires a large amount of computation time. A simulated annealing algorithm is also a representative optimization algorithm, and the simulation process is similar to the wind turbine layout process. However, despite its usefulness, it has not been widely applied to the wind farm layout optimization problem. In this study, a wind farm layout optimization method was developed based on simulated annealing, and the performance of the algorithm was evaluated by comparing it to those of previous studies under three wind scenarios; likewise, the applicability was examined. A regular layout and optimal number of wind turbines, never before observed in previous studies, were obtained and they demonstrated the best fitness values for all the three considered scenarios. The results indicate that the simulated annealing (SA) algorithm can be successfully applied to the wind farm layout optimization problem.
机译:风力涡轮机的最佳布局是风电场设计过程中的一个重要因素,并且已经进行了各种尝试来派生最佳部署结果。为此目的,已经开发了许多优化使用各种优化算法的涡轮机布局的方法并应用于各种研究。在这些方法中,最广泛使用的优化方法是遗传算法,但遗传算法处理许多独立变量,并且需要大量的计算时间。模拟退火算法也是代表性优化算法,并且模拟过程类似于风力涡轮机布局处理。然而,尽管有其有用性,但它尚未被广泛应用于风电场布局优化问题。在这项研究中,基于模拟退火开发了一种风电场布局优化方法,通过将其与三个风情景下的先前研究的研究进行了评估了算法的性能;同样,检查了适用性。在以前的研究中获得了常规布局和最佳的风力涡轮机数量,并且他们在先前的研究中观察到,并且他们证明了所有三个所考虑的场景的最佳选择性值。结果表明,模拟退火(SA)算法可以成功应用于风电场布局优化问题。

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  • 作者

    Kyoungboo Yang; Kyungho Cho;

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  • 年度 2019
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  • 原文格式 PDF
  • 正文语种 eng
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