基于自适应改进小波阈值限幅滤波的平抑风电波动策略

Strategy for Smoothing Wind Power Fluctuations Based on Adaptive Improvement of Wavelet Threshold Limiting Filter

  • 摘要: 基于风电功率的随机性与波动性对电网运行稳定性的负面影响,提出了一种加入限幅环节的改进小波阈值函数滤波,并通过改进的麻雀搜索算法对改进小波阈值函数的调节系数进行不同工业场景下的寻优,得到适应不同需求的波动平抑后并网功率曲线。对风电功率进行平抑后,以储能出力积累与波动平抑欧氏距离指标对不同场景下的并网功率曲线进行评估。算例研究表明,所提改进小波阈值函数限幅滤波能够很好平抑风电波动,并使并网功率限制在我国1 min、10 min尺度的MPFR限值以下,且可以适应不同工业需求调节目标函数权重值得到相应的并网功率曲线;同时验证了NTSSA算法在寻优性能上的优越性。

     

    Abstract: Based on the negative impact of stochasticity and volatility of wind power on the stability of power grid operation, an improved function filter of wavelet threshold with limiting links is proposed, and the improved sparrow search algorithm is used to optimize the improved wavelet threshold function based on the regulatory factors of different engineering models, and the grid-connected power curve is obtained after the fluctuation is smoothed to meet different demands. After the wind power is smoothed, the grid-connected power curves under different scenarios are evaluated using accumulation of energy storage output and Euclidean distance of index fluctuation flattening. The numerical examples show that the proposed improved wavelet threshold function limit-filtering can well smooth wind power fluctuations, and limit grid-connected power below the MPFR limit of 1 min and 10 min scale in China, and the weight of the objective function can be adjusted according to different industrial needs to obtain the corresponding grid-connected power. At the same time, the superiority of NTSSA algorithm in the optimization performance is verified.

     

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