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Comparison of Monte Carlo Simulation and Genetic Algorithm in Optimal Wind Farm Layout Design in Manjil Site Based on Jensen Model

机译:基于Jensen模型的Manjil网站最优风电场布局设计中蒙特卡罗仿真与遗传算法的比较

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Optimal arrangement of turbines in wind farms is very important to achieve maximum energy at the lowest cost. In the present study, the use of Vestas V-47 wind turbine and uniform one-way wind in achieving the optimal arrangement of horizontal axis turbines in Manjil with genetic and Monte Carlo algorithms has been investigated. Jensen model is used to simulate the wake effect on the downstream turbines. The objective function is considered as the ratio of cost to power of the power plant. The results show that the Monte Carlo method compared with genetic algorithm will give a better result. Under the same conditions, the Monte Carlo algorithm will give 29% and 40% better results in terms of the number of turbines and output power, respectively. In terms of optimization, in the Monte Carlo algorithm, its fitness value is 16% less than the genetic algorithm, which indicates its better optimization.
机译:风电场中涡轮机的最佳布置对于实现最低成本的最大能量非常重要。 在本研究中,研究了Vestas V-47风力涡轮机的使用和均匀的单通风在实现与遗传和蒙特卡罗算法中的Manjil中水平轴涡轮机的最佳布置。 Jensen模型用于模拟下游涡轮机的唤醒效果。 目标函数被认为是电厂的功率成本的比率。 结果表明,与遗传算法相比的蒙特卡罗方法将提供更好的结果。 在相同的条件下,蒙特卡罗算法分别在涡轮机和输出功率的数量方面将产生29%和40%。 在优化方面,在蒙特卡罗算法中,其适应值比遗传算法小于16%,表示其更好的优化。

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