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Siting and sizing of wind farms taking into account stochastic nature of generation

机译:考虑到生成随机性质的风电场选址和尺寸

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The article deals with the problem of the negative impact of wind farms stochastic generation on power grid. One of the ways to reduce the stochasticity of the wind farms generation is their geographically distributed siting. A technique for sizing and distributed siting of wind farms from the standpoint of the influence on the variability of the total generated power is proposed. Modeling of wind power generation with hourly detailing is carried out using the developed Wind-MCA software based on data from archives of long-term observations of ground-based weather stations. The optimal distribution of wind turbines in potential locations is based on a genetic algorithm. The objective function is the coefficient of variation of the power generated by all wind farms in the sites under consideration, depending on the number of wind turbines in their composition. The genetic algorithm is implemented using the built-in MATLAB function. The proposed technique is applied to assess the capacity options and sites for wind farms in the Zabaykalsky Krai. The solution providing the minimum value of the coefficient of variation of the wind farms generated power and high value of the wind farms capacity utilization factor has been obtained.
机译:文章涉及风电场随机发电对电网的负面影响问题。减少风电场生成随机性的方法之一是他们的地理分布在地理位置。提出了一种从关于对总产生功率的可变性的影响的角度尺寸和分布风电场选址的技术。使用档案的风密软件基于来自地面气象站的长期观测的档案的数据来进行流量发电的风力发电建模。潜在位置中的风力涡轮机的最佳分布基于遗传算法。目标函数是所考虑的部位中所有风电场产生的功率的变化系数,这取决于其组成中的风力涡轮机的数量。遗传算法使用内置MATLAB函数实现。拟议的技术适用于评估Zabaykalsky Krai的风电场的容量选项和地点。提供了提供风电场的变化系数的最小值的溶液,已经获得了风电场容量利用因子的功率和高值。

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