  The dynamics of a power system with large penetration of renewable energy
resources are becoming more nonlinear due to the intermittence of these
resources and the switching of their power electronic devices. Therefore, it is
crucial to accurately identify the dynamical modes of oscillation of such a
power system when it is subject to disturbances to initiate appropriate
preventive or corrective control actions. In this paper, we propose a
high-order blind source identification (HOBI) algorithm based on the copula
statistic to address these non-linear dynamics in modal analysis. The method
combined with Hilbert transform (HOBI-HT) and iteration procedure (HOBMI) can
identify all the modes as well as the model order from the observation signals
obtained from the number of channels as low as one. We access the performance
of the proposed method on numerical simulation signals and recorded data from a
simulation of time domain analysis on the classical 11-Bus 4-Machine test
system. Our simulation results outperform the state-of-the-art method in
accuracy and effectiveness.
