The use of sliding spectral windows for parameter estimation inpower system disturbance monitoring

摘要

The monitoring of power systems after faults or disturbances is annimportant problem. These disturbances generally give rise to oscillatingnmodal components, which in a worst case scenario, can be exponentiallyngrowing sinusoids. The latter, if not detected and damped out, can posena serious threat to system reliability. It is thus necessary to monitornwhether any of these modes do exhibit exponential growth (rather thannthe more acceptable scenario of exponential decay). There are currentlyna number of approaches to predicting/monitoring disturbances in powernsystem networks. One approach is eigenanalysis, based on a linearizednmodeling of the power system. A more direct approach is spectralnanalysis of the signals recorded immediately after a fault orndisruption. For this latter approach both Prony's method andnconventional Fourier techniques have been used. This paper presents anFourier based algorithm for estimating the parameters of the oscillatingnmodes which arise after a system disruption. The algorithm is based onnthe sliding window method discussed by K. Poon et al. (see ibid.,np.1573-9, 1988) but has a number of innovations