Failure Prevention and Malfunction Localization in Underground Medium Voltage Cables

Abstract

A smart monitoring system capable of detecting and classifying the health conditions of MV (Medium Voltage) underground cables is presented in this work. Using the analysis technique proposed here, it is possible to prevent the occurrence of catastrophic failures in medium voltage underground lines, for which it is generally difficult to realize maintenance operations and carry out punctual inspections. This prognostic method is based on Frequency Response Analysis (FRA) and can be used online during normal network operation, resulting in a minimally invasive tool. In order to obtain the good results shown in the simulation section, it is necessary to develop a lamped equivalent circuit of the network branch under consideration. The standard π-model is used in this paper to analyse sections of a medium voltage cable and the parameter variations with temperature are used to classify the state of health of the line. In fact, the variation of the electrical parameters produces a corresponding variation in the frequency response. The proposed system is based on the use of a complex neural network with feedforward architecture. It processes the frequency response, allowing the classification of the cable conditions with an accuracy higher than 90%.

A Comprehensive Review of Fault Diagnosis and Prognosis Techniques in High Voltage and Medium Voltage Electrical Power Lines

“…Based on the data provided by the main Italian distribution system operator (DSO), 60% of failures on medium-voltage joints occur from June to August, when thermal stress is very high and dissipation is reduced due to the thermal resistivity of the soil [135]. In order to detect the process of insulation degradation in its early stage, a possible low intrusive method is presented in [136], where the cascade connection of several pi-models is used to describe the equivalent circuit of the network branch being tested (Figure 9a). Here, the electrical parameters of the cable can be calculated using the manufacturer's information about the conductor cross-section, the insulation material, the sheath material and the type of installation (Figure 9b).…”

“…Conductance variations can be evaluated using the information from [137,138]. The prognostic method proposed in [136] is based on the successive steps presented in Figure 10, where a complex-valued neural network allows for the classification of the line status by processing the equivalent admittance measurements. On the other hand, in the event of thermal malfunctions an increase in the conductor resistance is assumed and, in the initial stages of insulation degradation, also an increase in conductance.…”

“…Conductance variations can be evaluated using the information from [137,138]. The prognostic method proposed in [136] is based on the successive steps presented in Figure 10, where a complex-valued neural network allows for the classification of the line status by processing the equivalent admittance measurements. A similar approach is proposed by the same authors in [139], where the analysis of the line conditions is performed by processing the measurements of high-frequency signals injected through power line communication (PLC) devices.…”

Sequential-Fault Diagnosis Strategy for High-Speed Train Traction Systems Based on Unreliable Tests

“…If a system has a good testability, it can efficiently and accurately detect and locate faults. Testability is widely used in various fields and can be applied to fault diagnosis [3,4], as well as for analyzing power devices [5,6]. Testability design comes into being with testing.…”

Reliability Assessment of MV Power Connections

“…Obtaining information on the condition of the power grid elements enables network operators to further plan renovation and modernization works [21][22][23]. Moreover, it allows the planning of the further effective expansion of the power grid [24,25].…”