An optimal geographical location of wind turbines can ensure the optimum total energy output of a wind farm. This study introduces a new solution to the optimization of wind farm layout (WFLO) problem based on a three-step strategy and particle swarm optimization as the main method. The proposed strategy is applied to a certain WFLO to generate highly efficient optimal output power. Three case scenarios are considered to formulate the non-wake and wake effects at various levels. The required wind turbine positions within the wind farm are determined by the particle swarm optimization method. The rule of thumb, which determines the wind turbine spacing, is thoroughly considered. The MATLAB simulation results verify the proposed three-step strategy. Moreover, the results are compared with those of existing research works, and it shows that the proposed optimization strategy yields a better solution in terms of total output power generation and efficiency with a minimized objective function. The efficiencies of the three case studies considered herein increase by 0.65%, 1.95%, and 1.74%, respectively. Finally, the simulation results indicate that the proposed method is robust in WFLO design because it further minimizes the objective function.

中文翻译：

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基于粒子群算法的风力发电机组风电场布局优化

风力涡轮机的最佳地理位置可以确保风电场的最佳总能量输出。本研究以三步策略和粒子群算法为主要方法，为风电场布局（WFLO）问题的优化提出了一种新的解决方案。所提出的策略被应用于特定的WFLO，以产生高效的最佳输出功率。考虑了三种情况，以形成不同级别的非唤醒和唤醒效应。风电场内所需的风力涡轮机位置由粒子群优化方法确定。决定风力涡轮机间距的经验法则已得到全面考虑。MATLAB仿真结果验证了所提出的三步策略。此外，将结果与现有研究成果进行了比较，结果表明，所提出的优化策略在总输出功率产生和效率方面具有最小的目标函数，从而提供了更好的解决方案。本文考虑的三个案例研究的效率分别提高了0.65％，1.95％和1.74％。最后，仿真结果表明，该方法在WFLO设计中具有鲁棒性，因为它进一步最小化了目标函数。