基于大数据和机器学习的用电异常行为分析系统

Analysis system of abnormal behavior of electricity consumption based on big data and machine learning

用户用电异常行为不仅对接入设备和用户本身产生影响,更会危及电网的正常运行,因此对用电异常行为的分析至关重要。基于大数据和机器学习技术,设计了一种用电异常行为分析系统,并提出了系统设计的总体框架和相关配置。所设计系统对用户用电的用电量、电压质量、负载及三相不平衡率、无功及功率因数等方面可以进行异常分析,并以可视化的方式向管理员和用户展示。同时,对高风险用户进行预警和跟踪处理,对窃电行为展开调查分析。本系统可以有效分析用户用电异常行为及进行窃电预警,对电网稳定运行起到关键作用。

Abnormal behavior of electricity consumption not only affects access equipment and users themselves,but also endangers the normal operation of power grid.Therefore,the analysis of abnormal behavior of electricity consumption is very important.Based on big data and machine learning technology,an analysis system of abnormal behavior of electricity consumption is designed,and the overall framework and relevant configuration of the system design are proposed.The designed system can analyze the abnormal factors such as power consumption,voltage quality,load,three-phase unbalance rate,reactive power and power factor,etc,and show them to administrators and users in a visual way.Meanwhile,early warning and tracking processing are conducted to high-risk users to carry out investigation and analysis of stealing electricity.The system can effectively analyze abnormal behaviors of users and give early warning of electricity theft,which plays a key role in the stable operation of power grid.