Abstract
To enhance grid reliability, weak points must be monitored. One of the weaknesses is the cable joints, which are prone to failure and can cause great losses from both a technical and economical point of view. Joints failures are usually caused by impurities unintentionally added during installation that cause partial discharges (PDs). In time, these discharges erode the insulation and generate treeing up to a destructive discharge between the conductor and the ground shield. For this reason, a method for the early detection of defects in joint installation and their online monitoring is required. A previously developed sensor was improved by adapting it for this purpose. It is based on the measurement of the induced current on a conductor due to a charge variation. It was experimentally tested on an actual joint in which defects were artificially introduced. Results show that the sensor is able to detect partial discharges. Moreover, a method for PD localization was developed. The first results show a coherency between the possible defect location, numerical simulations and historical background.
Highlights
Joints failures are usually caused by impurities unintentionally added during installation that cause partial discharges (PDs)
A key factor in the enhancement of electrical grid reliability and early detection of faults is the online monitoring of weak points
These models are necessary when relevant parameters have to be found for remaining life assessment (RLA) of the device under study and, from there, planning reliability strategies to minimize the outages, which results in energy and economical losses [1,2]
Summary
A key factor in the enhancement of electrical grid reliability and early detection of faults is the online monitoring of weak points. Available devices can detect, classify (with machine learning algorithms) and identify the element affected by PD, but only in open air They provide only qualitative parameters (such as the intensity of apparent charge, expressed in Coulombs), which cannot be used as a reliable index of RLA, and it is difficult to estimate the service life of the device affected by PD. For this reason, the scientific community is focused on improving methods to detect and localize the source of PDs [20,21,22]. Results show that the sensor can detect the defect, if present, and provide a possible locus of the PD
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