A non-linear regression model for inertia identification using synchrophasors and Big Data

Quiroz, Juan; Soto, Ismael; Toledo-Mercado, Esteban; Chavez, Hector; Zamorano-Illanes, Raul; Pereira-Mendoza, Jonathan; IEEE

Abstract

This work proposes a model for inertia identification of an electrical power system. A non-linear regression is used from a mathematical model that relates power and frequency variation, obtained from a synchrophasor network. Fitting of the non-linear regressions processed with Big Data, from the PMU and the different real generation contingencies, obtained from the national system operator, are presented.

Más información

Título según WOS: A non-linear regression model for inertia identification using synchrophasors and Big Data
Título de la Revista: 2021 IEEE IFAC INTERNATIONAL CONFERENCE ON AUTOMATION/XXIV CONGRESS OF THE CHILEAN ASSOCIATION OF AUTOMATIC CONTROL (IEEE IFAC ICA - ACCA2021)
Editorial: IEEE
Fecha de publicación: 2021
DOI:

10.1109/ICAACCA51523.2021.9465263

Notas: ISI