State Estimation Of Power System Based On Kalman Filtering Method Under Colored Noise

State estimation is one of the most important parts of the energy management system(EMS),can forecast the state vector one step ahead.This paper studies the Kalman algorithm of the State estimation and some improved models presented by domestic and foreign scholars,then analyzes the main drawbacks of these algorithms in present applications of power system,finally proposes its new improvements and developments in future.This paper deduces the estimating variance covariance is analyzed on the basis of the residual vectors,innovation vectors and correction vectors of predicted state.It can control the effects of the correlation noise.Theoretical analysis and test results show that the modified procedure improves the precision and adaptability of Kalman filtering effectively.