Mathematical Morphology-Based Feature-Extraction Technique for Detection and Classification of Faults on Power Transmission Line

Revati Godse,Sunil Bhat

doi:10.1109/access.2020.2975431

Abstract

The permanency of highly-reliable power supply is a core trait of an electric power transmission network. A transmission line is the main part of this network through which power is transmitted to the utility. These lines are often damaged by accidental breakdowns owing to different random origins. Hence, researchers are trying to detect and identify these failures at the earliest to avoid financial losses. This paper offers a new real-time fast mathematical morphology-based fault feature extraction scheme for detection and classification of transmission line faults. The morphological median filter is exploited to wrest unique fault features which are then fed as an input to a decision tree classifier to classify the fault type. The acquired graphical and numerical results of the extracted features affirm the potency of the offered scheme. The proposed scheme is verified for different fault cases simulated on high-voltage transmission line modelled using ATP/EMTP with varying system constraints. The performance of the stated technique is also validated for fault detection and classification on real-field transmission lines. The results state that the proposed method is capable of detecting and classifying the faults with adequate precision and reduced computational intricacy, in less than a quarter of a cycle.

Highlights

During the past few decades, with the emergence of hitech innovations, the conventional electrical power systems up all over the globe are in the throes of transformation to smart power system integrating advanced monitoring and control approaches [1]–[3]
The results showed that the proposed morphological median filter (MMF)-DTbased scheme is more competent compared to others and the fault detection and classification is achieved in less than quarter of a cycle
The MMF-based new, simple real-time fault feature extraction technique to achieve speedy and precise fault detection and classification on the HV transmission line is proposed in this paper

Summary

Introduction

During the past few decades, with the emergence of hitech innovations, the conventional electrical power systems up all over the globe are in the throes of transformation to smart power system integrating advanced monitoring and control approaches [1]–[3]. The consumer demand for high-quality reliable and uninterrupted power has been escalating unceasingly. This headed for the installation of loads of new transmission and distribution lines making electrical power system an enormously intricate system [4]. The electric power transmission line is one of the most vital elements of the power system network since it conveys the electricity from generation to distribution end. The performance of these lines plays a pivotal role for continuous power supply. One of the most significant aspects that obstruct the continuity of electric power supply is a fault on these lines which is inevitable and way beyond the control

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Discussion

Conclusion