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

Naresh Kumar, ASridhar, PAnil Kumar, TRavi Babu, TChandra Jagan Mohan, V
IAES International Journal of Artificial Intelligence (IJ-AI) (Sinta 1)Vol. 0 No. 01 September 2020
DOI10.11591/ijai.v9.i3.pp448-455

Abstrak

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

Kata Kunci

Fuzzy Logic,Neural Network, ANFIS

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Adaptive neuro-fuzzy inference system based evolving fault locator for double circuit transmission lines | IAES International Journal of Artificial Intelligence (IJ-AI) | Publiora