Spatial‐temporal decomposition approach for systematically tracking dominant modes, mode shapes and coherent groups in power systems

Abstract

This study proposes a novel spatial-temporal decomposition approach for systematically tracking dominant modes, mode shapes and coherent groups in bulk power systems using measurement data. First, components of the dominant oscillation modes, including frequencies and damping ratios, are identified from measurement data through a proposed recursive continuous wavelet transform. Second, cross-wavelet transform is employed to estimate the mode shapes using the wavelet coefficient of the dominant modes. Furthermore, a reconstructed wavelet coefficient, which integrates the wavelet coefficients of all the estimated dominant modes, is used to identify the coherent groups of generators via the cross-correlation coefficient. The proposed approach is evaluated on the simulation data from 16-machine 68-bus test system and China Southern Power Grid (CSG) as well as the field-measurement data collected from phasor measurement units of CSG. It is demonstrated that the proposed approach performs with high accuracy, robustness and efficiency in tracking dominant modes, mode shapes and coherent groups in the bulk power systems.