The main subject of this paper is the sensing of network anomalies that span from harmless impedance changes at some network termination to more or less pronounced electrical faults, considering also cable degradation over time. In this paper, we present how to harvest information about such anomalies in distribution grids using high frequency signals spanning from few kHz to several MHz. Given the wide bandwidth considered, we rely on power line modems as network sensors. We firstly discuss the front-end architectures needed to perform the measurement and then introduce two algorithms to detect, classify and locate the different kinds of network anomalies listed above. Simulation results are finally presented. They validate the concept of sensing in smart grids using power line modems and show the efficiency of the proposed algorithms.

A major aspect in power line distribution networks is the constant monitoring of the network properties. With the advent of the smart grid concept, distributed monitoring has started complementing the information of the central stations. In this context, power line communications modems deployed throughout the network provide a tool to monitor high frequency components of the signals traveling through a power line network. We propose therefore to use them not only as communication devices but also as network sensors. Besides classical voltage measurements, these sensors can be designed to monitor high frequency impedances, which provide useful information about the power line network, as for instance status of the topology, cable degradation and occurrence of faults. In this article, we provide a technical analysis of different voltage and impedance measurement techniques that can be integrated into power line modems. We assess the accuracy of the techniques under analysis in the presence of network noise and we discuss the statistical characteristics of the measurement noise. We finally compare the performances of the examined techniques when applied to the fault detection problem in distribution networks, in order to establish which technique gives more accurate results.

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The aim of the present work is to provide the theoretical fundamentals needed to monitor power grids using high frequency sensors. In our context, network monitoring refers to the harvesting of different kinds of information: topology of the grid, load changes, presence of faults and cable degradation. We rely on transmission line theory to carry out a thorough analysis of how high frequency signals, such those produced by power line modems, propagate through multi-conductor power networks. We also consider the presence of electrical anomalies on the network and analyze how they affect the signal propagation. In this context, we propose two models that rely on reflectometric and end-to-end measurements to extrapolate information about possible anomalies. A thorough discussion is carried out to explain the properties of each model and measurement method, in order to enable the development of appropriate anomaly detection and location algorithms.

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