智能电能表表前工频阻抗异常辨识方法及适用性分析研究OA

To accurately detect abnormal conditions of the power frequency impedance in front of smart electricity meters on low-voltage lines,it is necessary to conduct an in-depth analysis of the feasibility and adaptability of ex-isting identification methods.Firstly,based on the single-phase loop impedance model of the low-voltage distribu-tion network,this paper elaborates on the calculation principles and implementation steps of the loop impedance method,impedance parameter estimation method,and neighbor meter voltage impedance method.Then,a single-phase multi-user electricity experiment platform is constructed to collect electricity meter voltage and current data under different states of the meter front line(switch).Finally,the feasibility and adaptability of the three identifi-cation methods are evaluated based on experimental data and actual electricity meter data from the distribution area.The study shows that the loop impedance method is only suitable for systems with relatively small loop impedance,requiring the load of the downstream meters to remain unchanged between two measurement instances,which is quite demanding on the data.The impedance parameter estimation method is not affected by system impedance,but its identification results depend on the size and variation of its own load,with a significant deviation between the es-timated value and actual value.The neighbor meter voltage impedance method is simple and easy to implement,has a wide range of applications,requires less data,and has a low false positive rate,but is only applicable to sce-narios with multiple meter positions.