In the modern power system, its state parameters are often mixed with noise since the existing of output power of renewable energy, load changing and other stochastic processes. Therefore, taking the appropriate method is needed to extract the valid system state parameters from observed signal involving stochastic disturbance. An outline of Kalman filtering method is described and the basic process of Kalman filter is given; then Kalman filter and its extended form on the application of short-term load forecasting, dynamic state estimation, power quality analysis, relay protection, wind speed forecasting, motor state and parameters estimation are surveyed; finally, the relevant conclusions of Kalman filter in the application of power system are pointed out and its development trend is proposed.