An adaptive fuzzy based relay for protection of distribution networks

Dhivya Sampath Kumar, R. B. Menon, D. Srinivasan, T. Reindl
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引用次数: 8

Abstract

The high penetration of Distributed Generators (DGs) increases the need for monitoring and protection of the distribution system. The stochastic nature of the DGs may result in varying fault currents seen by the conventional over-current protection relays and thereby disturb the coordination of the relays. This necessitates an effective numerical relay that can capture the changes in the varying nature of DGs and take effective decisions according to the changing network conditions. Hence, an adaptive fuzzy relay, comprising of a fuzzy inference module and a neural network learning module, has been developed for deciding the optimal protection settings in the numerical relay corresponding to the changes in the network scenarios. A systematic comparison of the proposed adaptive fuzzy relay with conventional relay has been presented on a standard IEEE-test distribution system. The simulation results verify that the adaptive fuzzy relay is able to achieve the desired protection settings using a closed-loop approach.
配电网保护的自适应模糊继电器
分布式发电机(dg)的高度普及增加了对配电系统监测和保护的需求。DGs的随机特性可能导致传统过流保护继电器所看到的故障电流变化,从而干扰继电器的协调。这就需要一个有效的数字中继,它可以捕捉dg不同性质的变化,并根据不断变化的网络条件做出有效的决策。为此,设计了一种自适应模糊继电器,该继电器由模糊推理模块和神经网络学习模块组成,用于根据网络场景的变化确定数值继电器的最优保护整定。在标准的ieee测试配电系统上,对所提出的自适应模糊继电器与传统继电器进行了系统的比较。仿真结果验证了自适应模糊继电器采用闭环方法能够达到预期的保护整定值。
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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