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Analysis on the Fluctuation of Wind Power

机译:风电波动分析

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摘要

This paper is aimed at exploring the characteristic fluctuation of wind power based on samples from a certain wind farm. First, the paper is to analyze fluctuations of wind power at different time scales. According to a sliding difference algorithm to build wind power fluctuations evaluation. Wind power fluctuation index for different time scales are used to fit probability distributions, indicating that the best form of distribution of wind power fluctuations is t location scale distribution. Secondly, considering the wind power has the characteristics of non-linear, non-stationary signal of the data, it fully meets the wavelet neural network analysis of the characteristics of the data. Therefore, select wavelet neural network training and testing so as to make predictions about the future of the total power of wind farm. It points out the differences between different regions covered by the index from the fluctuation characteristics of wind power, thus further understanding the fluctuation characteristics of wind power: Influenced by the time and space distribution and other factors, there is a big difference between the output power fluctuation characteristics of single wind generator and wind farm, which is because of the different wind machine in the field by the wind energy differences, and the wake effect of organic groups, making frequent fluctuations in power distribution; the fluctuation of wind is gentle, i.e. with increasing spatial distribution scale, so gentle effect occurs to wind power fluctuations. Finally, through the analysis of the fluctuation characteristics of power, power factor and analyses the influence of the characteristics of fluctuation, the paper draws a conclusion of the following improvement programs to overcome the adverse effects of wind power fluctuation of power grid operation: the rational allocation of energy storage devices, expanding the coverage area of a wind farm, or improving the design of the windmill, which will make wind farms adapt to different wind directions, thus eliminating the impact of fluctuations on the power grid from the wind farm power output by the energy storage device, and covering the area of large wind farms can adapt to different wind directions, and with power complementary, it has achieved the amount of stable power transmission into the grid.
机译:本文旨在探索基于来自特定风电场的样品的风力发电的特征波动。首先,本文在不同时间尺度下分析风力的波动。根据一种滑动差分算法来构建风电波动评估。不同时间尺度的风力波动指数用于配合概率分布,表明风电波动的最佳形式是T位置比例分布。其次,考虑到风电具有非线性,非稳定信号的数据的特点,它完全满足了数据特性的小波神经网络分析。因此,选择小波神经网络培训和测试,以便对风电场总能力的未来进行预测。它指出了从风电波动特性所覆盖的不同区域之间的差异,从而进一步了解风电的波动特性:受时间和空间分布的影响等因素,输出功率之间存在很大差异单风力发电机和风电场的波动特性,由于风能差异的不同风机,以及有机群的唤醒效果,经常发出功率分布的波动;风的波动是温和的,即空间分布尺度的增加,因此风电波动发生温和的效果。最后,通过分析电力,功率因数的波动特性,分析了波动特性的影响,纸张的结论是克服电网运行风电波动的不利影响的结论:理性能量存储装置的分配,扩大风电场的覆盖面积,或改善风车的设计,这将使风电场适应不同的风向,从而消除了来自风电场功率输出的电网上的波动的影响通过能量存储装置,覆盖大风电场的面积可以适应不同的风向,并且具有功率互补,它已经实现了稳定的动力传递量进入栅格。

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