Recursive-ARX for Grid-Edge Fault Detection

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Yaagoubi, Soufiane El, Moffat, Keith, Araujo, Eduardo Prieto, Dörfler, Florian
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866913911632035840
author Yaagoubi, Soufiane El
Moffat, Keith
Araujo, Eduardo Prieto
Dörfler, Florian
author_facet Yaagoubi, Soufiane El
Moffat, Keith
Araujo, Eduardo Prieto
Dörfler, Florian
contents Future electrical grids will require new ways to identify faults as inverters are not capable of supplying large fault currents to support existing fault detection methods and because distributed resources may feed faults from the edge of the grid. This paper proposes the use of real-time system identification for online power-system fault detection. Specifically, we implement Recursive ARX (rARX) system identification on a grid-connected inverter. Experiments demonstrate that the proposed rARX method is able to both detect large faults quickly, and distinguish between high-impedance faults and large load increases. These results indicate that rARX grid-edge fault detection is a promising research direction for improving the reliability and safety of modern electric grids.
format Preprint
id arxiv_https___arxiv_org_abs_2506_20011
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Recursive-ARX for Grid-Edge Fault Detection
Yaagoubi, Soufiane El
Moffat, Keith
Araujo, Eduardo Prieto
Dörfler, Florian
Systems and Control
Future electrical grids will require new ways to identify faults as inverters are not capable of supplying large fault currents to support existing fault detection methods and because distributed resources may feed faults from the edge of the grid. This paper proposes the use of real-time system identification for online power-system fault detection. Specifically, we implement Recursive ARX (rARX) system identification on a grid-connected inverter. Experiments demonstrate that the proposed rARX method is able to both detect large faults quickly, and distinguish between high-impedance faults and large load increases. These results indicate that rARX grid-edge fault detection is a promising research direction for improving the reliability and safety of modern electric grids.
title Recursive-ARX for Grid-Edge Fault Detection
topic Systems and Control
url https://arxiv.org/abs/2506.20011