The invention discloses a power grid low-frequency oscillation fuzzy comprehensive early-warning method based on a steady-state learning mechanism. The power grid low-frequency oscillation fuzzy comprehensive early-warning method is characterized by comprising the steps of: 1) establishing an early-warning index; 2) developing a power fluctuation learning mechanism in a steady state; 3) preprocessing data in a window by adopting a sliding window technology, and calculating an early-warning index value; 4) calculating a current power system low-frequency oscillation safety state score by adopting a fuzzy analytic hierarchy process, giving a safety level and achieving rapid early warning; 5) exporting oscillation data of the current window when in an unsafe state, and starting a mode recognition program. The power grid low-frequency oscillation fuzzy comprehensive early-warning method achieves the beneficial effects that: the defects that the traditional early warning is slow in speed, has false alarm and relies on a power grid model can be effectively compensated by adopting the method of combining rapid early warning and mode recognition; and the effects of giving out power grid low-frequency oscillation safety state quickly and accurately and providing beneficial modal information for the dispatcher to take suppression measures are achieved under the condition that only actual measured data is provided.