  Sustained oscillations in power systems are dangerous. There are various
mechanisms, for instance, limit cycle and forced oscillation, that may lead to
sustained oscillations, which nevertheless are hard to differentiate. In this
paper, a novel periodogram-based method to distinguish different oscillation
mechanism is proposed, which can quantitatively extract essential signatures of
different mechanisms from power spectral density. Numerical study shows that
the proposed method can accurately distinguish different oscillation mechanisms
even when the forced oscillation frequency is close to the natural frequency.
