风电功率短时骤降的极值统计分析

风电功率短时骤降是大规模风电发电中需要有效处理的问题之一,如何描述风电功率短时骤降的极值分布尚缺乏有效方法。基于大量实测数据的分析,研究了不同时间尺度的风电功率下降幅值的高分位数变化的规律,发现在较短时间尺度下风电功率骤降极值与风电功率下降幅值的总体分布的标准差的比值较大。采用广义Pareto分布描述风电功率短时骤降的概率分布的尾部,广义Pareto分布的T年重现水平适合作为风电功率骤降极值的指标。在不同并网容量和时间尺度利用广义Pareto分布对风电功率骤降极值进行建模,分析表明:并网容量的增加可以降低风电功率骤降极值与并网容量的比值,但在超过一定容量后有饱和效应,风电功率骤降极值随时间尺度的增加呈非线性缓慢增长。

Statistical analysis of extreme wind power ramp-down events

One of the major issues in large-scale wind power generation is dealing with wind power ramp-down events, but few common methods that properly describe the extreme value distribution are reported. Based on the field measurement, this paper studies statistical models of empirical quantile of wind power ramp-down magnitudes in different temporal scales. The ratio of the extreme ramp-down value to the standard deviation of wind power fluctuations is relatively large in shorter temporal scales. It's found that generalized Pareto distribution is suitable to identify the upper-tail probability of wind power ramp-down. The T year return level of wind power ramp-down magnitudes can be used as index of extreme ramp-down. The paper then establishes the generalized Pareto distribution model under different installed capacity and temporal scales. Analysis shows that the ratio of extreme wind power ramp-down magnitude to installed capacity gets smaller with a trend of saturation when the installed capacity increases and there is a non-linear slow growth in extreme wind power ramp-down magnitude when temporal scale increases.