Recursive-ARX for Grid-Edge Fault Detection

TL;DR

This paper introduces a real-time Recursive ARX system identification method for grid-edge fault detection, capable of quickly identifying faults and differentiating fault types, enhancing grid reliability.

Contribution

It presents a novel application of Recursive ARX for online fault detection at the grid edge, addressing limitations of traditional methods with inverter-based resources.

Findings

Detects large faults rapidly

Distinguishes high-impedance faults from load increases

Improves reliability of modern electric grids

Abstract

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.