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Impedance Tracking and Estimation using Power Line Communications

机译:使用电力线通信进行阻抗跟踪和估算

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The broadband properties of impedance in power line communication (PLC) networks would enable smart PLC systems to implement fault detection and channel health monitoring in smart grid. In this paper, a novel real-time impedance estimation method for power line communication networks is proposed. We study the relationship between the channel frequency response (CFR) and the impedance behavior, CFR can be treated as the already known variable which is normally calculated by channel estimation algorithms in PLC devices, and find that the variation of certain key factor of the CFR curves including the frequency characteristics and values of Peak-Valley Difference and so on, could be used to tracking the impedance. A VMD (Variational Mode Decomposition) algorithm is used to obtain the useful frequency properties information in CFR waveform and machine learning method is used to estimate the parameters. Proposed impedance estimation method is verified by the computer simulations and the results show that it is a feasible solution for impedance estimation without any additional hardware and costs.
机译:电力线通信(PLC)网络中阻抗的宽带属性将使智能PLC系统能够在智能电网中实现故障检测和通道运行状况监视。本文提出了一种新的电力线通信网络实时阻抗估计方法。我们研究了信道频率响应(CFR)与阻抗行为之间的关系,可以将CFR视为通常由PLC设备中的信道估计算法计算出的已知变量,并发现CFR某些关键因素的变化包括频率特性和峰谷差值等的曲线可用于跟踪阻抗。使用VMD(可变模式分解)算法来获取CFR波形中有用的频率属性信息,并使用机器学习方法来估计参数。通过计算机仿真验证了所提出的阻抗估计方法,结果表明该方法是一种可行的阻抗估计解决方案,而无需任何额外的硬件和成本。

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