基于边缘计算的电网主设备状态实时监测方法OACSTPCD

Aiming at the problems of low real-time monitoring performance and anomaly detection accuracy of power grid main equip-ment,a real-time monitoring system of power grid main equipment based on edge computing is constructed.The system collects real-time data of the state of power grid main equipment through the sensor module.Simultaneous Localization and Mapping(SLAM)is used to monitor the main equipment of power grid.The edge node module uses wavelet denoising to denoise the collected data,and uses the Local Outlier Factor(LOF)algorithm to detect the data outliers.The network node module uses Message Queuing Telemetry Transport(MQTT)to transmit the processed result value to the management platform.Through the analysis and display,alarm processing and permission setting of the management platform module,the real-time detection and early warning of the power grid main equipment sta-tus are realized.The experimental results show that the system uses LOF algorithm to detect outliers.The false positive rate is 1.5％,the detection rate is 98.5％,and the accuracy rate can reach 98.6％.The average time delay of data transmission using MQTT protocol is 31.52 ms,and the transmission rate can reach 99.78％,which is highly practical.