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Impedance Tracking and Estimation using Power Line Communications

机译:使用电力线通信阻抗跟踪和估计

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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)网络中阻抗的宽带特性将使智能PLC系统能够在智能电网中实现故障检测和信道健康监控。本文提出了一种用于电力线通信网络的新型实时阻抗估计方法。我们研究信道频率响应(CFR)和阻抗行为之间的关系,CFR可以被视为已知的变量,该变量通常是通过PLC设备中的信道估计算法计算的,并且发现CFR的某些关键因子的变化包括频率特性和峰值谷差值等的曲线可用于跟踪阻抗。使用VMD(变分模式分解)算法来获得CFR波形中的有用频率特性信息,并且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,没有任何额外的硬件和成本,它是阻抗估计的可行解决方案。

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