Online monitoring and early warning of arc grounding fault overvoltage in 10kV distribution system based on Internet of Things technology

The purpose of this study is to explore the online monitoring and early warning method of arc grounding fault overvoltage of 10kV distribution system based on Internet of Things technology. By using the Internet of Things, triple exponential smoothing method, genetic algorithm and other technologies, this study proposes an innovative monitoring and early warning system to improve the security and reliability of the distribution network system. In order to accurately predict the occurrence of arc grounding fault overvoltage, this study uses three exponential smoothing method to process and model the historical monitoring data. In the optimization of prediction model, genetic algorithm is introduced in this study. By transforming the prediction problem into an optimization problem, the genetic algorithm can search for the optimal combination of model parameters, so that the prediction results can reach the highest accuracy. Through real-time data acquisition, intelligent prediction and visual early warning, the system provides a powerful tool for distribution network operation and maintenance, and improves the safety, reliability and operation efficiency of the distribution network system.