A Single-End Line-to-Ground Fault Location Method for HVAC Transmission Lines Using Sequential Feed-Forward Neural Networks

Zienab R. Khaleel; Mohammed H. Al-Qaraghuli; Mahmoud A. Elsadd; Mohamed S. Zaky; Mahmoud Elgamasy

doi:10.48084/etasr.10557

Authors

Zienab R. Khaleel Department of Computer Engineering, Imamaladham College, Baghdad, Iraq
Mohammed H. Al-Qaraghuli Department of Computer Engineering, Imamaladham College, Baghdad, Iraq
Mahmoud A. Elsadd Electrical Engineering Department, Faculty of Engineering, Damanhour University, Egypt
Mohamed S. Zaky Department of Electrical Engineering, College of Engineering, Northern Border University, Arar 1321, Saudi Arabia https://orcid.org/0000-0002-6925-459X
Mahmoud Elgamasy Electrical Engineering Department, Faculty of Engineering, Menoufia University, Egypt

Volume: 15 | Issue: 4 | Pages: 24220-24225 | August 2025 | https://doi.org/10.48084/etasr.10557

Received: 13 February 2025 | Revised: 6 April 2025 | Accepted: 19 April 2025 | Online: 21 May 2025

Corresponding author: Mohamed S. Zaky

Abstract

The paper presents an Artificial Neural Network (ANN)-based single-ended fault location technique as a practical and robust solution for improving the protection and maintenance of High Voltage Alternating Current (HVAC) transmission systems. The proposed fault location method depends on utilizing multistage predictions implemented by sequential feed-forward neural networks. The proposed method is a single-end-based method that does not necessitate the acquisition of measured signals from the other end. The inputs to the first stage are the voltage and current sequence components derived from the measured signals at the sending end of the transmission system. The training data are optimized using fault analysis theorems to improve the accuracy of fault location prediction. The fault point voltage, obtained from the first stage, is identified as a key parameter. The rationale and justification for its effectiveness and significance are presented in the paper. This parameter is subsequently combined with selected primary data to serve as the input for fault location prediction in the final stage. Extensive testing is performed with the assistance of MATLAB software, considering the effect of various fault scenarios, including different fault resistances, fault inception angles, and load angles. The findings indicate that the maximum error of the proposed method does not exceed 1%, confirming its efficacy in locating line-to-ground faults in HVAC transmission lines.

Keywords:

fault location, HVAC, transmission

Downloads

Download data is not yet available.

References

Z. Zhang, Z. Zhao, and H. Yu, "Research on Fault Location Algorithm for Line Protection," in 2022 China International Conference on Electricity Distribution, Changsha, China, 2022, pp. 1317–1321. DOI: https://doi.org/10.1109/CICED56215.2022.9928979

"IEEE Guide for Determining Fault Location on AC Transmission and Distribution Lines," IEEE Std C37.114-2014 (Revision of IEEE Std C37.114-2004), pp. 1–76, Jan. 2015.

R. Probst and A. El-Rasheed, "Challenges and safety aspects for effective fault location on long HVAC and HVDC cables," in 19th International Conference on AC and DC Power Transmission, Glasgow, UK, 2023, pp. 322–327. DOI: https://doi.org/10.1049/icp.2023.1348

H. Panahi, R. Zamani, M. Sanaye-Pasand, and H. Mehrjerdi, "Advances in Transmission Network Fault Location in Modern Power Systems: Review, Outlook and Future Works," IEEE Access, vol. 9, pp. 158599–158615, 2021. DOI: https://doi.org/10.1109/ACCESS.2021.3129838

H. A. Abd el-Ghany, I. A. Soliman, E. S. Ahmed, and A. E. ElGebaly, "Generalized wide-area fault detection and location algorithm for transmission system based on optimal PMUs allocation," International Journal of Electrical Power & Energy Systems, vol. 155, no. B, Jan. 2024, Art. no. 109634. DOI: https://doi.org/10.1016/j.ijepes.2023.109634

C. C. Ukwuoma et al., "Power transmission system’s fault location, detection, and classification: Pay close attention to transmission nodes," International Journal of Electrical Power & Energy Systems, vol. 156, Feb. 2024, Art. no. 109771. DOI: https://doi.org/10.1016/j.ijepes.2023.109771

M. Najafzadeh, J. Pouladi, A. Daghigh, J. Beiza, and T. Abedinzade, "Fault Detection, Classification and Localization Along the Power Grid Line Using Optimized Machine Learning Algorithms," International Journal of Computational Intelligence Systems, vol. 17, no. 1, Mar. 2024, Art. no. 49. DOI: https://doi.org/10.1007/s44196-024-00434-7

M. Satea, M. Elsadd, M. Zaky, and M. Elgamasy, "Reliable High Impedance Fault Detection with Experimental Investigation in Distribution Systems," Engineering, Technology & Applied Science Research, vol. 14, no. 5, pp. 17248–17255, Oct. 2024. DOI: https://doi.org/10.48084/etasr.8292

Z. Liu, Y. Liu, D. Lu, M. Duan, and J. Qiu, "Phasor Domain Single-Ended Transmission Line Fault Location Method Based on Harmonics without Remote Side Information," in 2022 IEEE PES Innovative Smart Grid Technologies - Asia, Singapore, Singapore, 2022, pp. 630–634. DOI: https://doi.org/10.1109/ISGTAsia54193.2022.10003537

M. K. Arpanahi, M. H. Fini, M. Sanaye-Pasand, and A. Ghorbani, "Generalized Equivalent Circuit and Algorithm for Single-End Fault Location in Transmission Systems," IEEE Transactions on Industrial Informatics, vol. 20, no. 3, pp. 4863–4873, Mar. 2024. DOI: https://doi.org/10.1109/TII.2023.3326157

J. P. Keshri and H. Tiwari, "Parameter-less fault locator using synchronized/un-synchronized data for overhead transmission line," in 2017 International Conference on Computer, Communications and Electronics (Comptelix), Jaipur, India, 2017, pp. 260–264. DOI: https://doi.org/10.1109/COMPTELIX.2017.8003975

K. Kalita, S. Anand, and S. K. Parida, "An Improved Parameter-Free Fault Locator for Untransposed Line With Unsynchronized Terminals," IEEE Transactions on Power Delivery, vol. 37, no. 6, pp. 5480–5483, Dec. 2022. DOI: https://doi.org/10.1109/TPWRD.2022.3207062

J. Wang and Y. Zhang, "Traveling Wave Propagation Characteristic-Based LCC-MMC Hybrid HVDC Transmission Line Fault Location Method," IEEE Transactions on Power Delivery, vol. 37, no. 1, pp. 208–218, Feb. 2022. DOI: https://doi.org/10.1109/TPWRD.2021.3055840

M. Parsi and P. A. Crossley, "Optimised Time for Travelling Wave Fault Locators in the Presence of Different Disturbances Based on Real-World Fault Data," IEEE Open Access Journal of Power and Energy, vol. 8, pp. 138–146, Mar. 2021. DOI: https://doi.org/10.1109/OAJPE.2021.3069365

O. Naidu and A. K. Pradhan, "A Traveling Wave-Based Fault Location Method Using Unsynchronized Current Measurements," IEEE Transactions on Power Delivery, vol. 34, no. 2, pp. 505–513, Apr. 2019. DOI: https://doi.org/10.1109/TPWRD.2018.2875598

Y. Xia, Z. Li, Y. Xi, G. Wu, W. Peng, and L. Mu, "Accurate Fault Location Method for Multiple Faults in Transmission Networks Using Travelling Waves," IEEE Transactions on Industrial Informatics, vol. 20, no. 6, pp. 8717–8728, Jun. 2024. DOI: https://doi.org/10.1109/TII.2024.3371998

R. Liang et al., "Fault Location Method in Power Network by Applying Accurate Information of Arrival Time Differences of Modal Traveling Waves," IEEE Transactions on Industrial Informatics, vol. 16, no. 5, pp. 3124–3132, May 2020. DOI: https://doi.org/10.1109/TII.2019.2903267

M. M. Elgamasy, A. I. Elezzawy, T. A. Kawady, N. I. Elkalashy, and M. A. Elsadd, "Tracing passive traveling surge-based fault management control scheme in unearthed distribution systems," Electrical Engineering, vol. 106, no. 5, pp. 5603–5624, Oct. 2024. DOI: https://doi.org/10.1007/s00202-024-02283-1

N. I. Elkalashy et al., "Earth fault distance estimation using travelling waves provided with triacs-based reclosing in distribution networks," IET Renewable Power Generation, vol. 15, no. 1, pp. 43–57, Jan. 2021. DOI: https://doi.org/10.1049/rpg2.12004

I. A. França, C. W. Vieira, D. C. Ramos, L. H. Sathler, and E. G. Carrano, "A machine learning-based approach for comprehensive fault diagnosis in transmission lines," Computers and Electrical Engineering, vol. 101, Jul. 2022, Art. no. 108107. DOI: https://doi.org/10.1016/j.compeleceng.2022.108107

S. R. Fahim, S. K. Sarker, S. M. Muyeen, S. K. Das, and I. Kamwa, "A deep learning based intelligent approach in detection and classification of transmission line faults," International Journal of Electrical Power & Energy Systems, vol. 133, Dec. 2021, Art. no. 107102. DOI: https://doi.org/10.1016/j.ijepes.2021.107102

M. Tabari and J. Sadeh, "Fault location in series-compensated transmission lines using adaptive network-based fuzzy inference system," Electric Power Systems Research, vol. 208, Jul. 2022, Art. no. 107800. DOI: https://doi.org/10.1016/j.epsr.2022.107800

M. Abasi, N. Heydarzadeh, and A. Rohani, "Broken Conductor Fault Location in Power Transmission Lines Using GMDH Function and Single-Terminal Data Independent of Line Parameters," Journal of Applied Research in Electrical Engineering, vol. 1, no. 1, pp. 22–32, Jan. 2022.

S. Verma, P. K. Roy, B. Mandal, and I. Mukherjee, "Artificial Hummingbird Algorithm-based fault location optimization for transmission line," Journal of Engineering and Applied Science, vol. 71, no. 1, Jul. 2024, Art. no. 149. DOI: https://doi.org/10.1186/s44147-024-00475-x

T. A. Kawady, A.-M. I. Taalab, and M. El-Sad, "An accurate fault locator for underground distribution networks using modified apparent-impedance calculation," in 10th IET International Conference on Developments in Power System Protection (DPSP 2010). Managing the Change, Manchester, United Kingdom, 2010, pp. 1–5. DOI: https://doi.org/10.1049/cp.2010.0302

M. A. Elsadd, N. I. Elkalashy, T. A. Kawady, A.-M. I. Taalab, and M. Lehtonen, "Incorporating earth fault location in management-control scheme for distribution networks," IET Generation, Transmission & Distribution, vol. 10, no. 10, pp. 2389–2398, Jul. 2016. DOI: https://doi.org/10.1049/iet-gtd.2015.1143