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

Keywords: inertia, power system, big data, PMU, synchrophasor

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

Editorial: IEEE
Fecha de publicación: 2021
Año de Inicio/Término: 22-26 March 2021
Página de inicio: 1
Página final: 5
Idioma: Inglés
Financiamiento/Sponsor: Project STICAMSUD 1l9-STIC-08 and DICYT 062117S.
URL: https://ieeexplore-ieee-org.ezproxy.usach.cl/document/9465263
DOI:

10.1109/ICAACCA51523.2021.9465263