基于运行误差估算的电能表准确性预计

Accuracy prediction of electricity meter based on operation error estimation

极值理论在误差分析中有着重要应用,电能表准确性取决于误差偏大数据的分布,且超过某一阈值的超出量数据近似符合广义帕累托分布。文中根据台区内考核表与分表的量测数据估算分表运行误差,引入超阈值(Peak-Over-Threshold,POT)模型、讨论了阈值选取、广义帕累托分布模型拟合,并给出了广义帕累托分布的参数估计公式,最终对分表运行误差的超阈值数据进行风险价值(Value at Risk,VaR)度量。结果表明,该方法能在不同阈值与置信水平下预测电能表运行误差超限的概率,进而评估台区内电能表的准确性,为预防电能表超差造成的风险提供较为可靠的依据。

Extreme value theory has an important application in error analysis.The accuracy of electricity meter depends on the distribution of data with large error,and the excess data exceeding a certain threshold approximately conforms to the generalized Pareto distribution.This paper estimates the sub-table operation error according to the measurement data of the evaluation table and sub-table in the station area,introduces the peak-over-threshold(POT)model,discusses the threshold selection and the fitting of the generalized Pareto distribution model,and the parameter estimation formula of the generalized Pareto distribution is given.Finally,the value at risk(VaR)of the over-threshold data of the sub-table operation error is measured.The results show that this method can predict the probability of over-limit operation error of electricity meter under different threshold and confidence levels,and then,evaluate the accuracy of electricity meter in the station area,so as to provide a more reliable basis for preventing the risk caused by over-error of electricity meter.