用电异常行为分析系统构建及应用

Construction and Application of an Analysis System for Abnormal Electricity Usage Behavior

电力系统中用电异常行为的检测和分析对于保障电网安全和优化能源使用具有重要意义。构建了基于机器学习的用电异常行为分析系统。该系统架构包括数据收集、数据处理、特征提取、模型训练、结果分析。通过测试太原市电力公司的实际用电数据,验证了系统的有效性和实用性。系统能有效识别多种用电异常行为,如偷电、设备故障和异常用电模式,保障了电力系统的安全运行,减少了电力公司的经济损失。

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.