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An Intelligent Fault Location Algorithm for Double Circuit Transmission Line Based on DFT-ANN Approach

机译:基于DFT-ANN方法的双电路传输线智能故障定位算法

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This paper demonstrates an intelligent fault location algorithm based on DFT-ANN approach for a 400 kV double circuit transmission line of Chhattisgarh state power transmission system. In this proposed algorithm, standard deviations of three-cycle data of fundamental components of three-phase current signals (two circuits) and three-phase voltage signals at sending end bus are used as an input to erudite the hidden associations of neural network structure. An extensive simulation studies have been performed in MATLAB/Simulink software for all types of common shunt faults and the performance of DFT-ANN-based fault locator is appraised at diverse situations of power system by changing fault type and varying different fault parameters such as fault location, fault resistance, fault inception angle with existence of mutual coupling. The simulation results confide the efficacy of proposed algorithm at widespread fault scenarios. The percentage of error attained in fault location estimation is within acceptable limit.
机译:本文演示基于用于切蒂斯格尔状态电力传输系统的一个400千伏双回线路DFT-ANN的方法智能故障定位算法。在此提出的算法,在发送端总线三相电流信号(两个电路)和三相电压信号的基频分量的三个周期的数据的标准偏差被用作输入到博学神经网络结构的隐藏关联。广泛的模拟研究在MATLAB / Simulink的软件对所有类型的公共分流故障被执行的和基于DFT-ANN-故障定位仪的性能是通过改变故障类型和不同的不同的故障参数,如故障在电力系统中的各种情况评估位置,故障电阻,具有相互耦合的存在故障开始角度。仿真结果倾诉在广泛的故障情况算法的有效性。在故障位置估计获得误差的百分比是可以接受的限度内。

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