Dynamic phasor and frequency estimation of time-varying power system signals

Abstract

The paper presents a new approach for the estimation of the fundamental phasor and frequency of time varying power system signals encountered in power system control and protection areas. Further if the signals are nonstationary and corrupted by white noise of low signal to noise ratio, the signal parameters can be estimated in an optimal way by using a low complexity recursive Gauss–Newton algorithm. The forgetting factor for minimizing the error function used in this algorithm is tuned iteratively to provide faster convergence and better accuracy in the estimation process. The proposed algorithm is particularly suitable for the integration of distributed generating sources to micro grids, when fast detection of faults and islanding condition is required. Extensive simulation results for a wide variety of power system signals with time-varying amplitude, phase, and frequency parameters validate the robustness and accuracy of the new algorithm.