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Fault Detection and Identification in the Nkalagu to Enugu 132kV Power Transmission Line
Subject area: Science,Engineering and Technology · Area of research: Fault Detection and Identification
Abstract
This study presents a comprehensive evaluation of fault detection and location techniques applied to the Nkalagu?Enugu 132?kV transmission line, a critical infrastructure component within Nigeria?s southeastern power grid. Given the line?s significance in ensuring uninterrupted power delivery to urban and industrial zones, timely and accurate fault diagnosis is imperative. The investigation begins with an overview of conventional methods?such as impedance-based and symmetrical component analyses?highlighting their limitations in complex or high-resistance fault conditions. To overcome these shortcomings, advanced approaches including the Takagi method, current differential protection and wavelet-based transient analysis were examined through simulations using MATLAB/Simulink. A realistic digital twin of the 38.5 km transmission corridor was developed using ?-model line representation and actual system parameters sourced from the Transmission Company of Nigeria (TCN). Fault scenarios were introduced across varying segments, and detection accuracy was evaluated under different fault resistances. The simulation results detect three phase (ABC) fault occurred at a distance point of 14.90km away from Bus B terminal, with a fault current 0.05pu and fault voltage of 0.051pu, also cleared the faults at 0.071sec, corresponding with the fault distance respectively, with minimal error margin, even under varying fault resistance and inception angles with errors consistently below 0.4%, affirming the robustness of the traveling wave-based model. Furthermore, the study confirms the influence of environmental and topographical factors on location precision, particularly over longer line segments. The findings advocate for the adoption of adaptive, intelligent protection schemes to bolster system resilience, minimize downtime, and support the evolving demands of Nigeria?s power transmission infrastructure.
Keywords
Fault detection, Fault identification, Transmission line, Impedance method, Nkalagu?Enugu, MATLAB/Simulink.
How to cite this paper
@article{1709266,
author = {Patrick O. Anierobi, Atuchukwu A. John, Okonkwo I. Ifeanyi, Arinze W. Nwosu},
title = {Fault Detection and Identification in the Nkalagu to Enugu 132kV Power Transmission Line},
journal = {Iconic Research And Engineering Journals},
year = {2025},
volume = {8},
number = {12},
pages = {1086-1093},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1709266.pdf},
abstract = {This study presents a comprehensive evaluation of fault detection and location techniques applied to the Nkalagu?Enugu 132?kV transmission line, a critical infrastructure component within Nigeria?s southeastern power grid. Given the line?s significance in ensuring uninterrupted power delivery to urban and industrial zones, timely and accurate fault diagnosis is imperative. The investigation begins with an overview of conventional methods?such as impedance-based and symmetrical component analyses?highlighting their limitations in complex or high-resistance fault conditions. To overcome these shortcomings, advanced approaches including the Takagi method, current differential protection and wavelet-based transient analysis were examined through simulations using MATLAB/Simulink. A realistic digital twin of the 38.5 km transmission corridor was developed using ?-model line representation and actual system parameters sourced from the Transmission Company of Nigeria (TCN). Fault scenarios were introduced across varying segments, and detection accuracy was evaluated under different fault resistances. The simulation results detect three phase (ABC) fault occurred at a distance point of 14.90km away from Bus B terminal, with a fault current 0.05pu and fault voltage of 0.051pu, also cleared the faults at 0.071sec, corresponding with the fault distance respectively, with minimal error margin, even under varying fault resistance and inception angles with errors consistently below 0.4%, affirming the robustness of the traveling wave-based model. Furthermore, the study confirms the influence of environmental and topographical factors on location precision, particularly over longer line segments. The findings advocate for the adoption of adaptive, intelligent protection schemes to bolster system resilience, minimize downtime, and support the evolving demands of Nigeria?s power transmission infrastructure.},
keywords = {Fault detection, Fault identification, Transmission line, Impedance method, Nkalagu?Enugu, MATLAB/Simulink. },
month = {June},
}