On-line System Identification of Power System Linear Models

J. A. Moreno-Corbea, M. R.A. Paternina, D. Rodales, R. Reyes, F. Zelaya, A. Zamora, C. Toledo, C. Castrillón, A. Sánchez

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva


This paper deals with the provision of adequate testing simulation environments to facilitate the evaluation of new system identification techniques to enhance power system stability. It develops and implements a testing architecture for online system identification approaches, taking advantage of the use of two well-known computational programs (MatlabTM and DIgSILENT PowerFactoryTM). To ensure a reliable and optimal system identification, this platform exploits a mutually beneficial relationship among four well-established mathematical techniques (discrete Fourier transform, Teager-Kaiser energy operator, the fast Fourier transform, and eigensystem realization algorithm). Their symbioses can capture the synchrophasor information, detect the right disturbance instant, optimally extract the dominant frequency, and properly identify the Markov parameters that assemble the descriptor form of Multiple-Input and Multiple-Output (MIMO) linear systems for modeling modern power grids. Numerical results unveil the potential for recreating the real behavior of power systems; in particular, the proposed architecture can deal with any system identification technique to be tested.

Idioma originalInglés
Título de la publicación alojada2023 IEEE Power and Energy Society General Meeting, PESGM 2023
EditorialIEEE Computer Society
ISBN (versión digital)9781665464413
EstadoPublicada - 16 jul. 2023
Publicado de forma externa
Evento2023 IEEE Power and Energy Society General Meeting, PESGM 2023 - Orlando, Estados Unidos
Duración: 16 jul. 202320 jul. 2023

Serie de la publicación

Nombre2023 IEEE Power & Energy Society General Meeting (PESGM)


Conferencia2023 IEEE Power and Energy Society General Meeting, PESGM 2023
País/TerritorioEstados Unidos


Profundice en los temas de investigación de 'On-line System Identification of Power System Linear Models'. En conjunto forman una huella única.

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