Wide-area monitoring using phasor measurement units (PMUs) offers the possibility of detecting conditions during which the power system may be vulnerable to destabilizing events. Such events are often characterized by undamped oscillations and are preceded by conditions of very low damping. Current techniques for estimating damping from low SNR ambient data are less accurate than desired, although fairly accurate for estimating frequencies of oscillation. We introduce a robust persistence measure that can be used in lieu of damping estimates to assess conditions for vulnerability to dynamic instability. The measure relies on the calculation of the energies of normalized sample autocorrelations of select signals. In this paper we focus on the technical details associated with spectral smoothing and temporal isolation in the calculation of the normalized autocorrelations, to permit effective calibration of the metric for both stable and unstable systems. An example is provided using measurements from the field.

1 aLesieutre, Bernard, C.1 aRoy, Sandip uhttps://certs.lbl.gov/publications/calculating-and-calibrating01106nas a2200121 4500008004100000245011200041210006900153260003400222520061200256100001600868700002300884856007700907 2017 eng d00aA sample-autocorrelation-based approach for monitoring power-system damping from ambient synchrophasor data0 asampleautocorrelationbased approach for monitoring powersystem d aMorgantown, WVbIEEEc09/20173 aEstimation of power-system damping from synchrophasor frequency measurements is studied. Specifically, a procedure for determining the damping of a dominant mode from the turns ratio of the sample autocorrelation function is outlined. The main contribution of the work is to then develop performance bounds on the damping estimates, and demonstrate approximation of these bounds entirely from the measurement data. The technique has been applied to archived historical data from the Western Electricity Coordinating Council (WECC), and a real-time implementation has also been developed.

1 aRoy, Sandip1 aLesieutre, Bernard uhttps://certs.lbl.gov/publications/sample-autocorrelation-based-approach01218nas a2200121 4500008004100000245007700041210006900118260003400187520075800221100002600979700001601005856007501021 2017 eng d00aA system response persistence measure for use in ambient data monitoring0 asystem response persistence measure for use in ambient data moni aMorgantown, WVbIEEEc09/20173 aTo aid in the real-time monitoring of system stability, it is useful to assess the relative damping of an underlying impulse response from noisy, ambient data. This is typically done using modal decomposition, procedures that accurately and consistently estimate natural frequencies of oscillation but struggle with estimates of damping. Here we introduce a measure of “persistence” as a robust measure of the duration of an impulse response. The longer a natural response persists the less damping it is perceived to have. The proposed measure scales linearly with the duration of an impulse response. It is easy to calculate as the energy in a normalized autocorrelation signal, and it serves as a measure of (inverse) damping.

1 aLesieutre, Bernard, C1 aRoy, Sandip uhttps://certs.lbl.gov/publications/system-response-persistence-measure