Remote Fault Identification and Analysis in Electrical Distribution Network Using Artificial Intelligence-Reference-Cited by-同舟云学术

Remote Fault Identification and Analysis in Electrical Distribution Network Using Artificial Intelligence

Published:2022-12-30 Issue:4 Volume:10 Page:1213-1218
ISSN:2347-470X
Container-title:International Journal of Electrical and Electronics Research
language:en
Short-container-title:IJEER

Author:

Kumar Dr. N M G¹,Sekhar Dr. A. Hema²,Reddy Dr. K. Balaji Nanda Kumar³,M Angulakshmi⁴,Shah Dr. Devangkumar Umakant⁵

Affiliation:

1. Professor, Department of Electrical and Electronics Engineering, Mohan Babu University, Sree Vidyanikethan Engineering College, Tirupathi, Andhra Pradesh, India

2. Professor and HOD, Department of EEE, VEMU Institute of Technology, P. Kothakota, Chittoor, Andhra Pradesh, India

3. Associate Professor, Department of EEE, Annamacharya Institute of Technology & Sciences, Tirupati, Andhra Pradesh, India

4. Assistant Professor, School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

5. Principal and Professor, Department of Electrical Engineering, K. J. Institute of Engineering & Technology, Savli, Vadodara, India

Abstract

This research describes a method for wavelet decomposition and machine learning-based fault site classification in a radial power distribution network. The first statistical observation is produced using wavelet decomposition and wavelet-based detailed coefficients in terms of Kurtosis and Skewness parameters. For this objective, six distinct machine learning methods are deployed. They are evaluated and compared using unknown data sets with varying degrees of unpredictability. One approach has been shown to be the most accurate in locating the location of the problem bus.

Publisher

FOREX Publication

Subject

Electrical and Electronic Engineering,Engineering (miscellaneous)

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