Construction and Application of an Analysis System for Abnormal Electricity Usage Behavior
The detection and analysis of abnormal electricity usage behavior in the power system is of great significance for ensuring grid safety and optimizing energy use.Have developed a machine learning based system for analyzing abnormal electricity usage behavior.The system architecture of this department includes data collection,data processing,feature extraction,model training,and result analysis.By testing the actual electricity consumption data of Taiyuan Electric Power Company,the effectiveness and practicality of the system have been verified.The system can effectively identify various abnormal electricity usage behaviors,such as power theft,equipment failure,and abnormal electricity usage patterns,ensuring the safe operation of the power system and reducing the economic losses of power companies.
power systemabnormal electricity usagemachine learning algorithms
NETL
NSTL
万方数据
