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Modeling Characteristic Curves of Digital Overcurrent Relay (DOCR) for User-Defined Characteristic Curve Using Artificial Neural Network

机译:使用人工神经网络为用户定义的特性曲线建模数字过电流继电器(DOCR)的特性曲线

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Intelligent-based protective relays in the power system is currently growing very rapidly with the use of embedded systems and artificial intelligence algorithms. Overcurrent relays operated based on the standard characteristic curve will move toward digital overcurrent relay (DOCR) using a flexible characteristic curve based on the user settings. DOCR with the standard characteristic curve cannot be used if the user must make modifications to the curve for field implementation purpose. In this paper, a new DOCR based on modeling a characteristic curve using Artificial Neural Network (ANN) will be presented. Four types DOCR with the standard and user-defined characteristic curve were developed and tested. Results demonstrate their successful operation with highly accurate results. The results also prove that the proposed DOCR with user-defined characteristic curve may serve as a convenient alternative to the conventional DOCR particularly on the implementation phase.
机译:随着嵌入式系统和人工智能算法的使用,电力系统中基于智能的保护继电器正在迅速发展。基于标准特性曲线操作的过电流继电器将根据用户设置使用灵活的特性曲线向数字过电流继电器(DOCR)过渡。如果用户必须为现场实施目的对曲线进行修改,则不能使用带有标准特性曲线的DOCR。在本文中,将提出一种基于使用人工神经网络(ANN)建模特征曲线的新DOCR。具有标准和用户定义的特性曲线的四种类型的DOCR已开发和测试。结果证明了他们的成功操作,结果非常准确。结果还证明,所提出的具有用户定义的特性曲线的DOCR可以作为常规DOCR的便捷替代品,特别是在实施阶段。

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