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.

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