In order to solve the problem of response lag and insufficient adaptability of dynamic coloring rules in the monitoring screen of the power grid

this paper puts forward an adaptive threshold model

a topological association coloring strategy and a priority mechanism driven by deep learning. The optimization method improves the efficiency of state identification and risk early warning ability

reduces the scheduling load

and provides reliable visual decision-making support for high-proportion new energy grids.