This work bridges two research fields i.e. metaheuristics and wind farm layout design. Comparative performance of twelve metaheuristics (MHs) on wind farm layout optimisation (WFLO) was conducted. Four WFLO problems are proposed for benchmarking the various metaheuristics while the design problem is an attempt to simultaneously minimise wind farm cost and maximise wind farm totally produced power. Design variables are wind turbine placement with fixed and varied number of wind turbines. The Jansen’s wake model is used while two types of energy estimation with and without considering partially overshadowed wake areas are studied. The results obtained from using various MHs are statistically compared in terms of convergence and consistency while the best performer is obtained. Comparison results indicated that moth-flame optimisation (MFO) algorithm is the most efficient algorithms. The results obtained in this work are said to be the baseline for future study on WFLO using metahueristics.

这项工作桥接了两个研究领域，即元启发法和风电场布局设计。在风电场布局优化（WFLO）上进行了十二种元启发法（MH）的比较性能。提出了四个WFLO问题来对各种元启发法进行基准测试，而设计问题是试图同时最小化风电场成本并最大化风电场总发电量的尝试。设计变量是固定数量和变化数量的风力涡轮机的风力涡轮机位置。使用Jansen的尾流模型，同时研究了两种类型的能量估计，其中考虑和不考虑部分阴影区。通过统计比较从使用各种MH获得的结果的收敛性和一致性，同时获得最佳性能。比较结果表明，飞蛾优化（MFO）算法是最有效的算法。这项工作中获得的结果被认为是未来使用元语言学对WFLO进行研究的基准。