IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 9, No 3: September 2020

Adaptive neuro-fuzzy inference system based evolving fault locator for double circuit transmission lines

A Naresh Kumar (Institute of Aeronautical Engineering)
P Sridhar (Institute of Aeronautical Engineering)
T Anil Kumar (Institute of Aeronautical Engineering)
T Ravi Babu (Institute of Aeronautical Engineering)
V Chandra Jagan Mohan (Institute of Aeronautical Engineering)



Article Info

Publish Date
01 Sep 2020

Abstract

Evolving faults are starting in one phase of circuit and spreading to other phases after some time. There has not been a suitable method for locating evolving faults in double circuit transmission line until now. In this paper, a novel method for locating different types of evolving faults occurring in double circuit transmission line is proposed by considering adaptive neuro-fuzzy inference system. The fundamental current and voltage magnitudes are specified as inputs to the proposed method. The simulation results using MATLAB verify the effectiveness and correctness of the protection method. Simulation results show the robustness of the method against different fault locations, resistances, time intervals, and all evolving fault types. Moreover, the proposed method yields satisfactory performance against percentage errors and fault location line parameters. The proposed method is easy to implement and cost-effective for new and existing double circuit transmission line installation

Copyrights © 2020






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...