The paper deals with the analysis of inter-area oscillations. that originates from power transients occurred in high extension grids. The research activity is focused on the implementation of a method capable to provide the manager of the national transmission grid with a tool for real time and accurate monitoring of the power system stability. In particular, the authors present a signal-based algorithm which, starting from the values estimated by the Phasor Measurement Units (PMUs) on the grid, allows the online monitor of the parameters (damping and frequency) characterizing the inter-area oscillations. The proposed algorithm is based on the Particles Swarm Optimization (PSO) method, but the traditional PSO has been enhanced through the use of a Continuous Weighted Average (CWA) which, at each iteration step, filters the PSO outputs assuring the reliability of the estimates.
A novel PSO-CWA algorithm for the estimation of inter-area oscillation parameters / Angrisani, L.; Bonavolontà, F.; Di Noia, L. P.; Lauria, D.; Liccardo, A.; Tessitore, S.; Ruggiero, D.. - (2020), pp. 1-6. (Intervento presentato al convegno 2020 IEEE International Instrumentation and Measurement Technology Conference, I2MTC 2020 tenutosi a Dubrovnik, Croatia, Croatia (virtual conference) nel 2020) [10.1109/I2MTC43012.2020.9128935].
A novel PSO-CWA algorithm for the estimation of inter-area oscillation parameters
Angrisani L.;Bonavolontà F.;Di Noia L. P.;Lauria D.;Liccardo A.
;Tessitore S.;
2020
Abstract
The paper deals with the analysis of inter-area oscillations. that originates from power transients occurred in high extension grids. The research activity is focused on the implementation of a method capable to provide the manager of the national transmission grid with a tool for real time and accurate monitoring of the power system stability. In particular, the authors present a signal-based algorithm which, starting from the values estimated by the Phasor Measurement Units (PMUs) on the grid, allows the online monitor of the parameters (damping and frequency) characterizing the inter-area oscillations. The proposed algorithm is based on the Particles Swarm Optimization (PSO) method, but the traditional PSO has been enhanced through the use of a Continuous Weighted Average (CWA) which, at each iteration step, filters the PSO outputs assuring the reliability of the estimates.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
