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A traveling-wave fault location technique for three-terminal lines based on wavelet analysis and Recurrent Neural Network using GPS timing

机译:基于小波分析的三端线路行走波断路故障定位技术,GPS时序经函数神经网络

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摘要

One of the most important features of smart distribution networks is handling fault situations in an efficient way. This paper describes a fault location algorithm for three-terminal transmission lines based on wavelet transform and Artificial Neural Network (ANN). Because of small size data base, Recurrent Neural Network (RNN) was utilized and for the purpose of synchronized time tagging, the Global Positioning System (GPS) with the highly-accurate timing capabilities is used. All the possible fault types are generated using the ATP-EMTP and results are discussed. Extensive simulation studies indicate that proposed network estimate fault location in different conditions with average error percentage less than 0.15% though practical limitations.
机译:智能配送网络最重要的特征之一是以有效的方式处理故障情况之一。本文介绍了一种基于小波变换和人工神经网络(ANN)的三端传输线故障定位算法。由于尺寸小的数据库,使用了经常性神经网络(RNN),并且为了同步时间标记,使用具有高精度定时能力的全球定位系统(GPS)。使用ATP-EMTP生成所有可能的故障类型,并讨论结果。广泛的仿真研究表明,在不同条件下的建议网络估计故障位置平均误差百分比虽然实际限制而小于0.15%。

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