MODELLING AND SIMULATION OF FAULTS AND FAULT LOCATION DETECTOR FOR RADIAL DISTRIBUTION SYSTEM
- Authors
-
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Oji, I. C.
Federal University of Technology, Akure, Nigeria
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Ale, T. O
Federal University of Technology, Akure, Nigeria
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Odeyemi, C. S
Federal University of Technology, Akure, Nigeria
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- Keywords:
- Faults, Distribution network, Fault location, Impedance-based algorithm
- Abstract
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Distribution lines are always exposed to the environment due to their network configuration and this makes its possibility of fault occurrence to be very high. Fault, as a regular incidence on distribution power system, can lead to failure of equipment, fire outbreak, power instability and other forms of hazardous conditions causing huge financial loss and increased system downtime. To avoid these conditions, it is necessary to detect and locate the fault on the network as fast as possible so as to prevent power system damages and reduce system downtime. This study designed a fault location system model that can detected and located three-phase faults at the point of occurrence using a developed 33 kV Ubulu-Uku radial distribution system as a test feeder. Thereafter, fault location equations were formulated which resulted into one single equation for three-phase fault on the network. An impedance-based algorithm was designed which was used to detect and locate fault on the distribution line. The designed algorithm was evaluated using varying line impedances of 0.01 ?, 0.15 ?, 0.35 ?, 0.5 ? and 0.65 ? which produced faults located along path 6 section 17, path 8 section 21, path 8 section 21, path 4 section 12 and path 8 section 21 with fault distances of 3.72 km, 3.93 km, 4.03 km, 4.81 km, and 4.21 km respectively from the main substation. The overall percentage accuracy of the designed model was found to be 86 %. The results presented show performance of the designed algorithm. Encouraging the implementation of this study can improve fault location accuracy, reduce response time, lower maintenance cost and minimize supply interruptions.
- Author Biographies
- References
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Ale, T. O., and Saliu, R. A., (2017): Fault Detection on High Voltage Transmission lines using Discrete Wavelet Transform, Journal of
Emerging Trends in Engineering and Applied Science, 8 (3), 136 – 142
Awalin, L.J, Mokhlis, H., and Halim A.H.A, (2012): Improved Fault Location on Distribution Network Based on Multiple
Measurement of Voltage Sags Pattern, In Proceedings at the IEEE International Conference on Power and Energy (PECon), Kota Kinabalu, Malaysia, 2 – 5 December, 767 – 772
FUTAJEET Vol. 19 (1) (https://doi.org/10.51459/futajeet.2025.19.1.109 Hamid M., Rahman D., Karsten H., and Hamid R. S., (2021): Real Fault Location in a Distributed Network using Smart Feeder Meter Data, Energies 2021, 14, 3242, 1 – 16.
Hazarika J., and Roy O.P., (2021): Distribution System Fault Analysis using MATLAB / SIMULINK, Intelligent Computing and
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Hizan, H., and Crossley, P. A., (2012): Single- Ended Fault Technique on Radial Network using Fault Generated Current Signal, IEE
Transaction on Power Delivery, 19 (2), 153 – 161.
Oji, I. C., Ale, T. O., Odeyemi, C. S., Dare- Adeniran, I. O., Aliyu, O. A., (2024): Development of Smart Ground Fault Location Model for Radial Distribution System, International Journal of Innovative Science and Research Technology, 9 (4), 2456 – 2165, 2982 –2995
Jameli, S., Bahmanya, A., and Ranjbar, S., (2020): Hybrid Classifier for Fault Location in Active Distribution System, Protection and Control of Modern Power System, 1 -9.
Kulikov A., Ilyushin P., Suslov K., and Filuppov S.,(2023): Estimating the Error of Fault Location on Overhead Power Lines by Emerging State Parameters using an Analytical Technique, Energies 2023, 16, 1552.
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A.G., (2018): Artificial Neural Network Based Smart Shunt Fault Recognition System for the 33kV Nigerian Power lines, In Proceedings at the 1st International Conference and Exhibition on Technological Innovation and Global Competitiveness of Federal Polytechnic, Ilaro, 5 – 8 November, 1 – 7.
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Prajapat D. (2020), Faults and Effects in Electrical Power Systems, Madhav University Publication, India
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- 2025-05-29
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