Thesis

FDTD modelling of partial discharge in high voltage cables

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Awarding institution
  • University of Strathclyde
Date of award
  • 2014
Thesis identifier
  • T13827
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Department, School or Faculty
Abstract
  • Partial discharge (PD) is recognized as an effective insulation diagnostic tool. PD measurement on high voltage (HV) cables is performed to evaluate the cable insulation conditions and high frequency current transformers (HFCTs) are widely used as the PD sensor. Detected PD signals can be subject to significant attenuation caused by propagation in the cables. How to relate the detected signals to the PDs actually occurring at PD-producing defects and moreover find out the nature of the defects is a problem. To investigate this problem experimentally is both difficult and limited since some defect types cannot be easily reproduced. Exploring this problem through modelling can potentially provide useful insights. A hybrid modelling framework is proposed to simulate HFCT-based PD detection in HV cables regarding PD excitation and propagation in the cables and PD detection using HFCTs. The finite difference time-domain (FDTD) technique is used to simulate PD in the cables and transfer function theory is used to consider effects of HFCTs on the PD signals. The framework can be used to excite a PD pulse anywhere in a cable model and predict the output from HFCTs some distance away. Implementing the framework requires parameters such as cable material/propagation properties, currents owing on conductors in FDTD models and HFCT transfer functions. Based on available cable samples and HFCTs, methods to obtain these parameters were described or developed and implementation of the framework was demonstrated. Although only cable modelling was carried out, the framework is expected applicable to modelling of PD detection in cable accessories. Furthermore, some experience gained in implementing FDTD modelling of the cables was summarised to facilitate future applications.
Resource Type
DOI
Date Created
  • 2014
Former identifier
  • 1039349

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