基于径向基函数神经网络的分布式代配电系统阻抗故障诊断

N. Rezaei, S. Javadian, N. Khalesi, M. Haghifam
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引用次数: 2

摘要

近年来,高级配电网故障诊断的复杂性,主要是由于分布式代和阻抗故障的使用增加,因此提出了基于神经网络的自适应故障定位技术。采用径向基神经网络进行故障诊断和定位。该方法降低了阻抗故障定位的复杂性。预测结果证明了所提出的在线自动程序在广泛的系统条件下对系统进行快速、准确的故障诊断的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnosis of impedance fault in distribution system with distributed generations using radial basis function neural network
In recent years, complexity of fault diagnosis in the advanced distribution networks, mainly due to the increased use of distributed generations and fault with impedance result in proposing of adaptive fault location technique using neural network. Radial basis function neural networks are used for fault diagnosis and fault location. The proposed approach reduces the complexity of the fault location in case of impedance fault. The predicted results prove the effectiveness of the proposed online automatic procedure for fast and accurate fault diagnosis of the system for a wide range of system conditions.
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