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Partial discharge (PD) activity is a key indicator of the cable insulation health in medium-voltage networks. Many of these cables are used as transmission media, because power line communication (PLC) modems are installed at their ends. This paper proposes two techniques that allow broadband PLC receivers to detect PDs at the same time that the PLC signal is being demodulated. The proposed techniques are based on how PDs alter both, null, and zero-bit loaded carriers, commonly used in orthogonal frequency division multiplexing modems. Using the proposed techniques, a simple firmware modification is sufficient to add this new functionality to the already installed modems. This paper is mainly concerned with theoretical aspects of the proposed techniques, and no experimental validation has been done. Nevertheless, simulation results show that the proposed techniques can be used to detect different types of PDs. Four cases studies are analyzed: short- and long-distance PDs, and low- and high-energy PDs. Finally, the impact of the inter-carrier interference on the detection capability is studied, and some recommendations are made to mitigate its effects.

The stability of power systems is very sensitive to voltage or current variations caused by the discontinuous supply of renewable power feeders. Moreover, the impact of these anomalies varies depending on the sensitivity/resilience of customer and transmission system equipment to those deviations. From any of these points of view, an instantaneous characterization of power quality (PQ) aspects becomes an important task. For this purpose, a wavelet-based power quality indices (PQIs) are introduced in this paper. An instantaneous disturbance index (ITD(t)) and a Global Disturbance Ratio index (GDR) are defined to integrally reflect the PQ level in Power Distribution Networks (PDN) under steady-state and/or transient conditions. With only these two indices it is possible to quantify the effects of non-stationary disturbances with high resolution and precision. These PQIs offer an advantage over other similar because of the suitable choice of mother wavelet function that permits to minimize leakage errors between wavelet levels. The wavelet-based algorithms which give rise to these PQIs can be implemented in smart sensors and used for monitoring purposes in PDN. The applicability of the proposed indices is validated by using a real-time experimental platform. In this emulated power system, signals are generated and real-time data are analyzed by a specifically designed software. The effectiveness of this method of detection and identification of disturbances has been proven by comparing the proposed PQIs with classical indices. The results confirm that the proposed method efficiently extracts the characteristics of each component from the multi-event test signals and thus clearly indicates the combined effect of these events through an accurate estimation of the PQIs.