摘要
智能电能表因其信息采集的便利性以及功能的完善性而广泛普及,如何高效且有针对性地对数量如此庞大的智能电能表进行维护是电力运营企业面临的挑战。针对此问题,文中提出了基于数据挖掘技术的智能电能表故障预警方法,即利用C 5.0算法构建智能电能表的故障预警模型,通过大量训练集对模型进行训练,再利用测试集计算模型的预警准确度。通过VS 2016平台搭建了故障预警系统,仿真结果表明,此系统能够对智能电能表的运行状态进行准确预警,电力运营企业可根据预警结果对异常的电能表进行重点检查,由此节省由于逐户排查所浪费的人力物力。
Smart meters are widely used owing to the convenience of information collection and the perfection of their functions.How to maintain such a large number of smart meters efficiently and pertinently is a challenge for power operation enterprises.In order to solve this problem,a fault early-warning method of smart meter based on data mining technology is proposed in this paper.The fault early-warning model of smart meter is constructed by using C 5.0 algorithm,and the model is trained through a large number of training sets,and then,the early-warning accuracy of the model is obtained by using the test sets.A fault early-warning system is built through VS 2016 platform.The simulation results show that the system can accurately warn the running state of smart meter.According to the early-warning results,the power operation enterprises can carry on the key inspection to the abnormal meter according to the early-warning result,thus saving the manpower and material resources wasted due to the household investigation.
作者
张雅
樊艳芳
刘群杰
Zhang Ya;Fan Yanfang;Liu Qunjie(School of Electrical Engineering,Xinjiang University,Urumqi 830047,China;Zhoukou Power Supply Company,Zhoukou 466000,He’nan,China)
出处
《电测与仪表》
北大核心
2021年第1期183-188,共6页
Electrical Measurement & Instrumentation
基金
国家自然科学基金资助项目(51307020)。
