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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
A Naresh Kumar
Institute of Aeronautical Engineering
Computer Science & IT Engineering

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Adaptive neuro-fuzzy inference system based evolving fault locator for double circuit transmission lines A Naresh Kumar; P Sridhar; T Anil Kumar; T Ravi Babu; V Chandra Jagan Mohan
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 9, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (441.025 KB) | DOI: 10.11591/ijai.v9.i3.pp448-455

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
Support vector machine based fault section identification and fault classification scheme in six phase transmission line A Naresh kumar; M Suresh Kumar; M Ramesha; Bharathi Gururaj; A Srikanth
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i4.pp1019-1024

Abstract

The higher complexity of a six phase transmission system (SPTS) construction and the large number of possible faults makes the protection task challenging. Moreover, the reverse & forward path faults in SPTS cannot be detected by traditional relay as it becomes under-reach. In this paper, a support vector machine (SVM) method including Haar wavelets for SPTS fault section identification and fault classification is focused. The positive-sequence component phase angle and currents at middle two buses are used to formulate a suggested method. Feasibility of suggested SVM is tested with a 138 kV, 300 km, 60 Hz, SPTS in MATLAB based Simulink platform. Several major parameters including far end and near end location conditions are taken to investigate the reach setting and accuracy of proposed SVM. This relaying method can detect the existence of fault in reverse & forward path in 1 ms time.
Co-Authors A Srikanth Bharathi Gururaj M Ramesha M Suresh Kumar P Sridhar T Anil Kumar T Ravi Babu V Chandra Jagan Mohan