Fault Detection and Identification in the Nkalagu to Enugu 132kV Power Transmission Line

References

[1] Atuchukwu J. A., Ochogwu S. O., Okonkwo I. I. and Ogboh V. C (2023) “Location of Faults on Nigeria 330kv Power Transmission Lines Using Traveling Wave” ICONIC Research and Engineering Journals vol.6 pp. 405-410

[2] Baseer, M. A. (2013). Travelling waves for finding the fault location in transmission lines. Journal Electrical and Electronic Engineering, vol.1(1), pp.1-19.

[3] Elmore, W. A. (2004). Protective Relaying: Theory and Applications. CRC Press.

[4] Horowitz, S. H., and Phadke, A. G. (2014). Power System Relaying. Wiley.

[5] Jamil, M., Singh, R., & Ansari, M. R. (2021). Artificial intelligence and Traveling wave-based methods for transmission line fault location: A Review IEEE Transactions on Smart Grid. Electric Power Systems Research, vol.19(5), pp.207-220

[6] Eneh I. I. Victor I. E., and Henry A, (2024) Improving the Protection of New Haven-Nkalagu 132kv Transmission Network Using A Genetic Trained Adaptive Relay Scheme International Journal of Science Academic ResearchVol.5(8) Pp.8075-8081

[7] IIoh J.P., Okowoko I.I and Anierobi, P.O. (2022) “Double Ended Method For Fault Location on Transmission Lines (A Case Study of Otukpo 132kV Transmission Lines)” Global

[8] Scientific Journals GSJ: Volume 10, pp. 159-174. www.globalscientificjournal.com

[9] Mohammad, M. A. (2013). Electrical Transmission and Distribution. McGraw-Hill.

[10] Transmission Company of Nigeria (TCN). (2023). Commissioning Report of 150 MVA Transformer at New Haven Substation. https://tcn.org.ng

[11] Razi-Kazemi, A., Shahabi, M., & Aghazadeh, M. (2018). A Review of Impedance-Based Fault Location Methods in Transmission Lines. Electric Power Systems Research, vol.16(3), pp.170–180.

[12] Razi-Kazemi, A., Vahedi, M., and Sedaghati, R. (2018). Limitations of impedance-based fault Location methods and the role of traveling wave techniques in high-voltage networks. International Transactions on Electrical Energy Systems, vol. 28(4), pp.25-31.

[13] Wesley F. (2019) “Fault Location Techniques Using the Traveling Wave Method and the Discrete Wavelet Transform” of Master thesis of Science in Electrical Engineering in the College of Engineering at the University of Kentucky

[14] Shahabodin, S., Jamil, M., & Razi-Kazemi, A. (2021) Smart Fault Identification in EHV Lines Using Machine Learning Algorithms. IEEE Access, 9, pp. 113245–113259.

[15] Shahabodin A., Mousa A., Mohammad M. and Benyamin P. (2021) Fault localization and diagnosis in transmission networks based on robust deep Gabor convolutional neural network and PMU measurements International Journal of Electrical Power & Energy Systems. the institution of engineering and technology vol.14(26) pp.6484-6492

@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},
  }