The monitoring of dynamic performances by means of WAMS allows keeping track of oscillation modes during the system operation and consequently detecting undesirable on comings of possible undamped oscillation behaviors of electric variables. In this paper, the problem of monitoring power system oscillation modes by means of a wavelet-based spectral analysis is addressed. A monitoring architecture, aimed at achieving the online supervision of power system dynamic performances, is presented. The feasibility of the proposed approach has been proved through simulations on a test grid and in presence of system noise and measurement noise, through simulations on a real-sized model of the Italian power system. The results of the eigenvalue analysis, applied to the same test case, have been adopted as common base in order to compare the results coming from the wavelet analysis with the results coming from the prony analysis.
Power system modal identification via wavelet analysis / Bronzini, Marco; Bruno, Sergio; De Benedictis, M.; LA SCALA, Massimo. - (2007), pp. 2041-2046. (Intervento presentato al convegno IEEE Lausanne POWERTECH 2007 tenutosi a Lausanne, Switzerland nel 1-5 July 2007) [10.1109/PCT. 2007.4538632].
Power system modal identification via wavelet analysis
BRONZINI, Marco;BRUNO, Sergio;LA SCALA, Massimo
2007
Abstract
The monitoring of dynamic performances by means of WAMS allows keeping track of oscillation modes during the system operation and consequently detecting undesirable on comings of possible undamped oscillation behaviors of electric variables. In this paper, the problem of monitoring power system oscillation modes by means of a wavelet-based spectral analysis is addressed. A monitoring architecture, aimed at achieving the online supervision of power system dynamic performances, is presented. The feasibility of the proposed approach has been proved through simulations on a test grid and in presence of system noise and measurement noise, through simulations on a real-sized model of the Italian power system. The results of the eigenvalue analysis, applied to the same test case, have been adopted as common base in order to compare the results coming from the wavelet analysis with the results coming from the prony analysis.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
