Summary

High Voltage Direct Current (HVDC) technology has many advantages over the traditional High Voltage Alternating Current (HVAC) due to its overall efficiency, high current carrying capability and small power losses over long distance transmission. Ascribed to these benefits, the demand for long-distance HVDC power transmission is increasing to interconnect power grids between land and islands or for wind farm, as most of the renewable energy resources are located far from urban cities. Therefore it is required to develop XLPE cable for HVDC grids with high reliability by considering insulation diagnosis to avoid unexpected failures. One of the diagnostic methods for power cables in AC grids is the detection of Partial discharge (PD) taking place inside the apparatus. For that PRPDA (Phase Resolved Partial Discharge Analysis) was the first method developed. In 2001, we also proposed a method, CAPD (Chaotic Analysis of Partial discharge), considering three normalized parameters obtained from the values between two consecutive PD pulses: Magnitude difference , Occurring time difference and applied voltage difference. However not many methods have been proposed for PD pattern analysis under DC stress in XLPE cable. Therefore, in this paper a method is proposed for the analysis of PDs occurring from the possible defects inside the XLPE cable insulation under DC stress. The partial discharge detection under DC stress and relevant analysis have been dealt with considering three main types of discharges produced from the defects introducible into DC XLPE cable system: void due to the cavities produced inside the insulation, surface discharge due to the field stress parallel to the dielectric surface and corona due to the presence of sharp wire located at the skirt of cable termination. PD signals are then analysed using the LabVIEW Software and defect related patterns are proposed. Since there is no phase information of the applied DC voltage, signal analysis has been adopted based on characteristics of two main parameters related to PD signals which are magnitude and time.

Additional informations

Publication type ISH Collection
Reference ISH2015_440
Publication year 2015
Publisher ISH
File size 787 KB
Price for non member Free
Price for member Free

Authors

Chen George, FU Mingli, Akbari Asghar, Hou Shuai, Pandey

An Identification of Insulation Defects in HVDC XLPE Cable based on the Analysis of PD Detection
An Identification of Insulation Defects in HVDC XLPE Cable based on the Analysis of PD Detection