An Adaptive Neuro-Fuzzy Inference System Approach for Identifying Breakpoint Set for Directional Overcurrent Relays

2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM ) Pub Date : 2019-11-01 DOI:10.1109/HNICEM48295.2019.9073390

M. A. Teodoro, Pocholo James Loresco, Maria Angelica C. Gorospe

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引用次数: 2

Abstract

Primary and backup relays pairs are protection schemes for power systems which are set in conjunction to one another to ensure that the protection system operates by limiting an abnormality within its zone of protection. Breakpoints are the starting points of all assumptions and calculations done in protection systems. Previous methods of determining breakpoints favor linear graph theory and expert theory system rather than machine learning. In this study, an adaptive neuro-fuzzy inference (ANFIS) approach is used to determine the breakpoint set for directional overcurrent relays of a given 3-bus network. The two most influential input variables from 15 inputs affecting breakpoint set are determined by Exhaustive Search. The reduced inputs are then used to design the Sugeno type ANFIS. Experimental results show promising results in terms of Root Mean Square Error.

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定向过流继电器断点集辨识的自适应神经模糊推理系统方法

主备继电器对是电力系统的保护方案，它们相互连接，以确保保护系统通过限制其保护区域内的异常来运行。断点是保护系统中所有假设和计算的起点。以前确定断点的方法倾向于线性图理论和专家理论系统，而不是机器学习。在本研究中，采用自适应神经模糊推理(ANFIS)方法来确定给定三总线网络的定向过流继电器的断点集。从影响断点集的15个输入中选取两个最具影响力的输入变量，通过穷举搜索确定。然后使用减少的输入来设计Sugeno型ANFIS。实验结果表明，该方法在均方根误差方面取得了令人满意的结果。

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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2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management ( HNICEM )

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