风电功率波动特性的概率分布模型研究

为保证电网安全稳定运行,在大规模风电并网运行控制过程中,准确构建风电出力波动特性的概率分布模型具有重要意义.基于数据驱动的方法,采用加权高斯混合概率分布模型来拟合大规模风电基地的波动特性,模型拟合参数可采用基于期望最大化(Expectation Maximization,EM)的极大似然估计算法来获得,并提出了拟合评价指标来与其它多种概率分布模型进行对比,结果验证了加权高斯混合概率模型的有效性和适用性.

Research on Probabilistic Distribution Model of Wind Power Output Fluctuation Characteristics

It is of great significance for the safe and stable operation of power system to build the probabilistic distribution model of wind power output fluctuation characteristics within the large-scale wind power grid operation control process.Based on analyzing a large number of field measured data,a weighted Gaussian mixture probabilistic model is proposed to simulate short-time wind power fluctuation characteristics of wind farm cluster,and evaluation indices to reflect the short-time maximum fluctuation of wind power output,based on Expectation Maximization(EM) of maximum likelihood estimation algorithm to estimate model parameters is put forward.This model is compared with various other kinds of probability distribution model and the simulation results shows that the weighted Gaussian mixture distribution probability model possesses the highest precision,so as the effectiveness of the weighted Gaussian mixture probability model is verified.