Harmonics Estimation of a Noisy Power System Signal using Cubature Kalman Filter

Fast and accurate estimation of harmonics of a typical power system signal is very much desirable for power quality assessment. This paper proposes an application of the cubature Kalman filter (CKF) for estimating the parameters of harmonics, sub-harmonics, and inter-harmonics of a signal in presence of noise. CKF utilizes a third-degree spherical radial cubature rule to estimate the probability density functions of the states as well as the measurements. At the same time, this technique does not require any linearization and saves the computational time. The effectiveness of CKF has been compared with UKF by performing various test cases. It is observed from the simulation results that CKF exhibits superior performance in estimating the parameters of harmonics, inter-harmonics, and sub-harmonics of a distorted power system static as well as the dynamic signal by virtue of execution time and accuracy.