Frequency estimation of distorted power system signals using extended complex Kalman filter

Abstract

The paper proposes an extended complex Kalman filter and employs it for the estimation of power system frequency in the presence of random noise and distortions. From the discrete values of the 3-phase voltage signals of a power system, a complex voltage vector is formed using the well known @-transform. A nonlinear state space formulation is then obtained for this complex signal and an extended Kalman filtering approach is used to compute the true state of the model iteratively with significant noise and harmonic distortions. As the frequency is modeled as a state, the estimation of the state vector yields the unknown power system frequency. Several computer simulations test results are presented in the paper to highlight the usefulness of this approach in estimating near nominal and off-nominal power system frequencies.

Power Grid Impedance Tracking With Uncertainty Estimation Using Two Stage Weighted Least Squares

“…In case of nonsynchronously sampled signals, what is common in phasor measurement units (PMUs), interpolated DFT methods can be used [23]. There are also adaptive filtering methods, which allow for direct calculation of leakage-free complex samples of V and I from nonsynchronously sampled time domain signals like Kalman filtering [24,25] or phase locked loop (PLL) based [26].…”

Estimation of Electrical Power Quantities by Means of Kalman Filtering

“…Firstly proposed in (Girgis & Hwang, 1984), an extended Kalman filter (EKF) is applied to a signal model composed by three state variables which only considers the fundamental component (grid frequency, inphase and in-quadrature components). (Dash et al, 1999) considers a three-phase configuration by means of a complex signal model; again, voltage harmonics are not modelled. In order to reduce the response time of the Kalman filter, (Dash et al, 2000) proposed to include a hysteresis method for resetting the covariance matrix after a signal transient.…”

Robust sliding‐mode observers for large‐scale systems with application to a multimachine power system

“…In addition, observer design in the presence of unknown signals is challenging. An extended Kalman filter is used in [24,25] to enhance frequency estimation of distorted power signals. However, in real time, it is difficult to implement this Kalman filter due to the poor flexibility in dealing with higher order systems.…”