Initial results in electromechanical mode identification from ambient data

Power system loads are constantly changing. Over a time-span of a few minutes, these changes are primarily random. The random load variations act as a constant low-level excitation to the electromechanical dynamics of the power system which shows up as ambient noise in field measured voltage, current and power signals. Assuming the random variations are white and stationary over an analysis window, it is theoretically possible to estimate the electromechanical modal frequencies and damping from the spectral content of the ambient noise. In this paper, field collected ambient noise is analyzed by solving the Wiener-Hopf linear prediction equations to estimate the modal frequency and damping. These estimates are then compared with results from a Prony analysis on a ringdown resulting from a 1400 MW brake insertion under the same operating conditions as the ambient data. Results show that estimates are consistent between the ambient and ringdown analysis indicating that it is possible to estimate a power system's electromechanical characteristics simply from ambient data. These results demonstrate that it may be possible to provide power system control and operation algorithms with a real-time estimate of modal frequency and damping.