Non-Stationary Stabilized Fast Transversal RLS Filter for Online Power System Modal Estimation

Abstract

Online monitoring of inter-area oscillations is a vital need for secure operation of large-scale power systems. This paper aims at online estimation of inter-area modes by a novel stabilized fast transversal recursive least squares (SFTRLS) filter running on ambient power system data received from phasor measurement units. The SFTRLS filter is a fast finite-impulse response adaptive filter that is widely used in communication applications, such as noise and echo cancelation. It has the lowest computational complexity among least-squares filters and directly calculates coefficients of the parametric model selected for identifying a system under study. In the proposed method, the SFTRLS filter along with digital band-pass Butterworth filter and down-sampling blocks are implemented in online manner for identification of an autoregressive model that describes the measured power system ambient signal. Applicability and accuracy of the proposed method are evaluated using real measurement data of western systems coordinating council (WSCC) breakup on August 10, 1996, as well as simulated ambient data of the IEEE 16-machine, 5-area test system excited by white noise random load modulations. Its performance is investigated under different conditions of load modulations, measurement noises, sudden change in damping ratio, and occurrence of three-phase faults. The simulation results verify efficient and robust performance of the proposed method for modal estimation of real large-scale power systems.