Abrupt Change Detection of Fault in Power System Using Independent Component Analysis

TL;DR

This paper introduces a new fault detection method for power systems using independent component analysis, which improves real-time accuracy and robustness over existing techniques.

Contribution

The paper presents a novel fault detector based on ICA that reduces computational load and enhances fault classification and localization in power systems.

Findings

The proposed ICA-based method outperforms existing approaches in accuracy.

It is effective under various fault and disturbance conditions.

The method is suitable for real-time fault detection and localization.

Abstract

This paper proposes a novel fault detector for digital relaying based on independent component analysis (leA). The index for effective detection is derived from independent components of fault current. The proposed fault detector reduces the computational burden for real time applications and is therefore more accurate and robust as compared to other approaches. Further, a comparative assessment is carried out to establish the effectiveness of the proposed method as compared to the existing methods. This approach can be applied for fault classification and localization of a distance relay reflecting its consistency in all system changing conditions and thus validates its efficacy in the real time applications. The method is tested under a variety of fault and other disturbance conditions of typical power system.