计及样本容量合理性的风电功率预测考核算法

在风功率预测误差服从正态分布的基础上,首先,提出了在给定置信水平、最大允许误差下最小样本容量的计算方法,以及在给定误差范围、样本容量下估计值置信水平的计算方法。其次,针对典型显著性水平、误差范围进行分析,论证了当样本容量较小时,样本统计指标置信水平低,无法代表总体指标。最后,提出了计及样本容量合理性的日前风电功率预测准确率考核算法,实际算例表明,所提考核算法更科学合理,避免了不合理的考核罚款。

Assessment Algorithm for Wind Power Prediction Considering Rationality of Sample Size

On the basis that the wind power prediction error obeys normal distribution, an algorithm for calculating the minimum sample size with the given confidence level and maximum permissible error is proposed, as is a method of computing the confidence level under the condition of the given error range and sample size. Then an analysis is carried out according to the typical significance level and the error range. It is demonstrated that the statistical confidence level of the sample is low when the sample size is small, which cannot represent the overall data. Finally, an assessment algorithm for wind power prediction is proposed by taking into account the rationality of sample size of the day-ahead wind power prediction accuracy rate. The actual examples show that the proposed method is more scientific and reasonable, avoiding unreasonable assessment fines.