Modeling and simulation of impedance-based algorithm on overhead power distribution network using matlab

SHOBAYO, Olamilekan, ABAYOMI-ALLI, O, ODUSAMI, M, MISRA, S and SAFIRIYU, M (2020). Modeling and simulation of impedance-based algorithm on overhead power distribution network using matlab. In: SENGODAN, T, MURUGAPPAN, M and MISRA, S, (eds.) Advances in Electrical and Computer Technologies. Select Proceedings of ICAECT 2019. Lecture Notes in Electrical Engineering (672). Singapore, Springer Singapore, 335-345.

[img] PDF (Version query, if AM make available)
Shobayoetal..pdf - Published Version
Restricted to Repository staff only
All rights reserved.

Download (382kB)
Official URL:
Link to published version::


Rapid location of faults in electrical distribution system is very critical for effective and efficient operation. The operation of the power system must be reliable and as economical as possible. The persistent lingering of fault conditions in the distribution networks is the lack of efficient technology to locate the faults in the distribution network and lack of proper maintenance of the equipment in the network. Most of the accidents caused to individuals (either the consumers or the workers) in this distribution networks are caused by some of these faults that not easily identified. This research proposes a model to locate faults in a distribution network using an enhanced impedance-based method for fault location. The model was simulated on the 2nd Avenue 11 kV feeder (Lagos) with the use of one-end impedance-based method. The results show a little marginal error when the location values obtained with the model are compared to doing physical inspection on the distribution line. The parameters that could affect the effectiveness of the method were analyzed.

Item Type: Book Section
Additional Information: Series ISSN: 1876-1100
Identification Number:
Page Range: 335-345
SWORD Depositor: Symplectic Elements
Depositing User: Symplectic Elements
Date Deposited: 16 May 2022 13:24
Last Modified: 12 Oct 2023 12:15

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics