FAULT DETECTION AND LOCATION BASED SVM FOR THREE PHASE TRANSMISSION LINES APPLYING POSITIVE SEQUENCE FAULT COMPONENTS

  • Ganesh Shingade INDUS Universisty,Ahemedabad,Gujrat,India
  • Dr.Sweta Shah INDUS University , Ahemedabad,Gujrat,India
Keywords: Fault identification, Fault classification, Support Vector Machine (SVM), Positive Sequence Analyzer, Transmission lines, Electrical fault detection

Abstract

Transmission lines are an imperative element of the modern power systems. Any faults in them can cause an undesirable interruption in power supply. Precise analysis of these faults is important in-order to ensure an incessant supply of power. For this purpose, fault detection and classification are needed to clear any such faults and re-establish the system to maintain its normal operation. In this paper, a novel integrated approach of protective relaying with enhanced support vector machine algorithm has been adopted for detecting faults and its location estimation in long transmission line. The proposed scheme is successfully able to detect and classify different symmetrical and unsymmetrical faults along with some peculiar cases related to High Impedance Faults (HIF) and evolving faults, current transformer (CT) saturation/ capacitive voltage transformer (CVT) transient, close-in faults, swing condition, source strength variation, etc. The comparative analysis with recent proposed techniques declared the potentiality and robustness of the scheme

Author Biography

Dr.Sweta Shah, INDUS University , Ahemedabad,Gujrat,India

Dr.Sweta Shah Born in Ahmedabad, India. Received Ph.D from Indus University in 2018.Research interest include Power system, Power System Protection and Artificial intelligence.Received M.E (power system) from B.V.M Engg. College in 2008.

Published
2023-09-19
How to Cite
Shingade, G., & Shah, S. (2023). FAULT DETECTION AND LOCATION BASED SVM FOR THREE PHASE TRANSMISSION LINES APPLYING POSITIVE SEQUENCE FAULT COMPONENTS. Transdisciplinary Journal of Engineering & Science, 14. https://doi.org/10.22545/2023/00234
Section
Articles