基于GSA训练的人工神经网络在电力变压器励磁涌流识别中的应用

M. Taghipour, A. Moradi, M. Yazdani-Asrami
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引用次数: 14

摘要

当变压器铁心在空载上电时被驱动到饱和状态时,变压器中会产生涌流。该电流由高幅值、大直流分量组成,并且具有较多的二次谐波含量。本文介绍了一种新的基于人工智能的励磁涌流原理及其与正常电流区分的计算机辅助仿真教学技术。该方法可作为一种很好的方法,在本科课程中进行浪涌电流概念及其识别技术的教学。在本科高年级学生中对所提出的方法进行评估对于他们对涌流概念的理解是非常有用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of magnetizing inrush current in power transformers using GSA trained ANN for educational purposes
Inrush current in transformers is generated when transformer cores are driven into saturation during no-load energization. This current consists of high amplitude, large DC component and also, has much 2nd harmonic content. In the proposed paper, a new computer-aided simulation technique for teaching inrush current principles and its discrimination from normal current based on artificial intelligence has been introduced. This method can be used for educating concepts of inrush current and its identification techniques during undergraduate curriculum as an excellent approach. Evaluation of the proposed approach with undergraduate senior students is very useful in terms of their understanding of the inrush current concepts.
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