ANN Based Location of Fault for 500KV Transmission Line in Sudan from Merowe to Atbara

Mohammed Alnour Mustaffa, Eltahir Mohamed Hussein, Ahmed Mohammed Ishag
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Abstract

Today, transmission lines have become one of the important core components in systems of electrical power that are used to transport energy. Since transmission lines are prone in nature, the probability of failures in transmission lines is generally higher than that of other major components. This paper presents the fault of the transmission line from Merowe to Atbara in northern Sudan using artificial neural networks. A transmission line model was created in MATLAB R2014a using SIMULINK and SIMSCAPE with the SIMPOWERSYSTEM toolbox. The current and voltage values obtained from the transmission line model have been used as an entry for artificial neural networks. The results obtained from the proposed artificial neural networks were acceptable and the networks were found to be practically practicable for implementation. The significance of picking the most proper artificial neural network is to get the best performance from the neural networks. 
基于人工神经网络的苏丹梅洛维至阿特巴拉500KV输电线路故障定位
如今,输电线路已成为电力系统中用于输送能量的重要核心部件之一。由于输电线路的性质是易发的,因此输电线路的故障概率一般高于其他主要部件。本文利用人工神经网络对苏丹北部梅洛维至阿特巴拉输电线路的故障进行了分析。在MATLAB R2014a中,使用SIMULINK和SIMSCAPE工具,结合SIMPOWERSYSTEM工具箱,建立传输线模型。从传输线模型中得到的电流和电压值被用作人工神经网络的入口。所提出的人工神经网络得到的结果是可以接受的,并且该网络在实际应用中是可行的。选择最合适的人工神经网络的意义在于使神经网络的性能达到最佳。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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