数据挖掘在智能电能表故障分析中的应用

Data Mining Application in Smart Meter Fault Analysis

自2009年推广以来,全国范围内已安装运行数亿只智能电能表,国家电网公司采取集中检定模式对其进行装出前的管理,并配套了用电信息采集系统监控其现场运行状态,管理部门可在相应平台上获得智能电能表海量的质量数据。文中尝试在矩阵实验室(MATLAB)环境下,通过训练神经网络,建立现场智能电能表故障数据与检定数据之间联系,讨论采用数据挖掘技术分析检定数据以提前获得智能电能表故障信息的可能性及有效性,为电能表的质量管控提供另一种工具。

Since 2009, hundreds of millions of smart meters have been installed nationwide. State Grid Corporation of China manages the asset by centralized inspection in large scale. Meanwhile, a system called Power User Electric Energy Data Acquire System was built up to monitor the operation status of these meters. Therefore, vast amounts of life-time data of the meters can be obtained from the centralized inspection system as well as the data acquire system. This paper proposed a way of establishing the connections between fault data and inspection data by training neural network under MATLAB environment. And then the possibility and effectiveness to obtain fault information of smart meters in advance by data mining is discussed, to provide an alternative way of quality control of smart meters.