Research on power grid real-time condition monitoring and adaptive control strategy based on edge computing

In order to solve the problems of low real-time monitoring performance and accuracy of anomaly detection of power grid main equipment status, a real-time monitoring system of power grid main equipment status based on edge computing was constructed. The system uses the LOF algorithm to detect outliers in data, with a false alarm rate of 1.5%, a detection rate of 98.5%, and an accuracy rate of 98.6%. The average latency for transmitting data using the MQTT protocol is 31.52ms, and the arrival rate can reach 99.78%, indicating high practicality. In the hybrid microgrid, we connect to the energy storage system and achieve power adaptive control of the hybrid energy storage multi microgrid through power exchange control and autonomous power frequency division adaptive control. The experimental results show that the proposed method has good performance in power control of hybrid energy storage multi microgrids, with small active power control errors. It can effectively ensure the stable operation of hybrid energy storage multi microgrids and improve the accuracy of power adaptive control.