Dynamic State Estimation of Power System Considering Asynchronous Measurement

Abstract

In order to solve the problems that PMU measurement and SCADA are asynchronous and the measurement model is different, it is difficult to use them together. In this paper, a robust unscented Kalman filter based on quadratic constrained quadratic estimation is proposed to realize the fusion estimation of hybrid measurements. The algorithm realizes the following three functions: Firstly, the time scale of SCADA measurement is given and synchronized by sequential comparison and interpolation synchronization method; secondly, the strong tracking algorithm is introduced to solve the problem that the filtering effect of UKF is reduced when the process noise is abnormal; finally, the proposed algorithm is simulated in IEEE 30 test system. The test results show that the algorithm can realize the synchronization of asynchronous measurement, filter out the error caused by asynchronous problem, and effectively correct the influence of abnormal process noise on the filtering result, so as to realize the real-time tracking of the system state.