An Intelligent Early Warning Method for High Voltage Power Equipment Risks Based on Cloud Modeling and Random Forest

The conventional risk intelligent early warning method for high-voltage power equipment mainly uses the WebService interface to calculate the similarity of risk early warning characteristics, which is vulnerable to the impact of spatio-temporal correlation fluctuations, leading to abnormal early warning in some states. Therefore, a risk intelligent early warning method for high-voltage power equipment based on cloud model and random forest is proposed. That is, the cloud model and random forest are used to extract the operation characteristics of high-voltage power equipment, and the intelligent risk early warning algorithm of high-voltage power equipment is designed, thus completing the intelligent risk early warning of high-voltage power equipment. The experimental results show that the average warning delay of the design method is 1.1ms, and the root mean square error of the warning does not exceed 0.05, which has certain application value.