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Wind Farm Layout Optimization using Real Coded Multi-population Genetic Algorithm

机译:基于实数编码遗传算法的风电场布局优化

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Finding the optimal location of wind turbines is a challenging work by reason of the various effects of the turbine wake. Indeed, on a site gathering several wind turbines, if the turbines are too close the loss of power grows with the wake effect. In this paper, an RC-MPGA (Real Coded Multi-population Genetic Algorithm) method is proposed to search the optimal location of WTs (Wind Turbines) in Square shaped WF (wind farm), Installed on an area of 4000000 m2 ( 2000m×2000m), with the aim to maximize the electrical power generated by all WTs and grows the annual economic profitability of the WF. By using the same WF environment conditions, we can see that the proposed method is promising and presents an improvement in terms of maximum power generation when compared to other works previously studied in the literature.
机译:由于涡轮机尾流的各种影响,找到风力涡轮机的最佳位置是一项艰巨的工作。实际上,在聚集多个风力涡轮机的站点上,如果涡轮机太靠近,则功率损耗会随着尾流效应而增加。本文提出了一种RC-MPGA(实数编码多种群遗传算法)方法来搜索方形WF(风电场)中的WT(风轮机)的最佳位置,该区域安装在4000000 m2(2000m× (2000m),目的是使所有WT产生的电能最大化,并提高WF的年度经济收益。通过使用相同的WF环境条件,我们可以看到,与以前在文献中研究的其他工作相比,该方法很有希望,并且在最大发电量方面有所改进。

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