Abstract
In order to improve the accuracy and convergence speed of the transient estimation of the power system, taking into account the nonlinearity of the system, the Kalman filter (EKF) algorithm which is mainly used in the current status estimation of the power system, has the disadvantages of slow convergence and poor robustness, using particle filter (PF) algorithm in this work. In order to solve the problem of computationally occupied space and large amount of computation and sample degradation, a particle filter algorithm with sequence importance resampling is introduced on the basis of basic PF algorithm, which is closer to the approximate expression of true distribution of status. Compared with the EKF algorithm, the power system can converge to the real value quickly after the disturbance of the power system, and it has higher estimation precision and stability than the extended Kalman filter algorithm, achieving the requirement of accurate estimation.
