Asymmetrical Fault Recognition System on Electric Power Lines Using Artificial Neural Network

Mbamaluikem, Peter O and Bitrus, Irmiya and Okeke, Henry S (2019) Asymmetrical Fault Recognition System on Electric Power Lines Using Artificial Neural Network. International Journal of Engineering Trends and Technology (IJETT), 67 (11). pp. 61-66. ISSN 2231-5381

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Abstract

The occurrence of faults on electric power lines reduce the efficiency and reliability of the whole power system network. Against this backdrop, this paper applied artificial neural networks in recognizing asymmetrical faults in electric power lines to improve electric power line protection.The proposed artificial neural network based shunt fault recognition systems were trained using set of current and voltage data generated from simulating different asymmetrical faults states of the studied power system, modeled in MATLAB/Simulink environment. A comparative analysis of the three asymmetrical fault recognition models were done to establish which artificial neural network-based model/configuration leads to optimal performance. The results show that the artificial neural network-based model that uses both current and voltage data as input gave the best performance and hence,it may be employed in building asymmetrical faults detecting devices for electric power lines

Item Type:	Article
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	Mr Adedamola Bameke
Date Deposited:	30 Jun 2020 16:52
Last Modified:	30 Jun 2020 16:52
URI:	http://eprints.federalpolyilaro.edu.ng/id/eprint/862

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