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

Abstract

The monitoring of power systems after faults or dis- turbances is an important problem. These disturbances generally give rise to oscillating modal components, which in a worst case scenario, can be exponentially growing sinusoids. The latter, if not detected and damped out, can pose a serious threat to system relia- bility. It is thus necessary to monitor whether any of these modes do exhibit exponential growth (rather than the more acceptable sce- nario of exponential decay). There are currently a number of ap- proaches to predicting/monitoring disturbances in power system networks. One approach is eigenanalysis, based on a linearized modeling of the power system (1). A more direct approach is spec- tral analysis of the signals recorded immediately after a fault or disruption. For this latter approach both Prony's method (2) and conventional Fourier techniques have been used (5). This paper presents a Fourier based algorithm for estimating the parameters of the oscillating modes which arise after a system disruption. The algorithm is based on the sliding window method discussed in (5), but has a number of innovations.