The frequent occurrence of extreme weather events poses a serious threat to the reliable operation of the power system. In order to cope with this uncertainty, there is an urgent need to construct a grid early warning system based on big data analysis to enhance the grid’s ability to resist disasters. The project uses significant amounts of meteorological data and operational data on power systems and applies big data principles to develop a distribution system early warning system, which operates in a big data environment. By monitoring its operational principles and meteorological conditions in real-time, the system can quickly and accurately predict and identify any potential faults or anomalies associated with extreme weather events affecting the power system. In tests, the warning accuracy can be as low as 95% or as high as 99%. The system has excellent warning accuracy, and can accurately identify grid faults, as well as the risks related to extreme meteorological conditions.