Real-time Data Analysis Model of Power Grid Equipment Based on Big Data Monitoring

With the steady progress of power grid intelligence, we should use the massive equipment status data, power grid operation data and meteorological environment data accumulated by power grid companies. It is innovative and feasible to use data mining technology to mine the correlation between equipment operating environment and state quantity and then summarize different data characteristics by sorting and classifying the data. It is innovative and feasible to conduct differentiated power equipment state evaluation according to other data types. In this paper, using the powerful data mining method, the status data are hidden in the power equipment data are mined, and the characteristics of different data are summarized. According to the various data characteristics, other equipment status evaluation methods are selected to evaluate the equipment health status accurately, which has exceptionally high scientific significance and application value.