Non-linear regression model for inertia identification using synchrophasors and Big Data
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
| Título según WOS: | A non-linear regression model for inertia identification using synchrophasors and Big Data |
| Título según SCOPUS: | A non-linear regression model for inertia identification using synchrophasors and Big Data |
| Título de la Revista: | 2021 IEEE International Conference on Automation/24th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2021 |
| Editorial: | Institute of Electrical and Electronics Engineers Inc. |
| Fecha de publicación: | 2021 |
| Año de Inicio/Término: | 22-26 March 2021 |
| Idioma: | English |
| 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 |
| Notas: | ISI, SCOPUS |