A procedure is proposed where a power system is excited with a low-level pseudo-random probing signal and the frequency, damping, magnitude, and shape of oscillatory modes are identified using spectral density estimation and frequency-domain transfer function identification. Attention is focussed on identifying system modes in the presence of noise. Two example cases are studied: identification of electromechanical oscillation modes in a 16-machine power system; and turbine-generator shaft modes of a 3-machine power plant feeding a series-compensated 500-kV network.
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