The University of Southampton
University of Southampton Institutional Repository

Identification of partial discharge sources and their location within high voltage transformer windings

Identification of partial discharge sources and their location within high voltage transformer windings
Identification of partial discharge sources and their location within high voltage transformer windings
This thesis is concerned with developing a new approach to high voltage transformers condition monitoring, which involve partial discharge (PD) measurement and localisation within high-voltage transformer windings. This is an important source of information for both diagnosis and prognosis of the health of power transformers. Generally, Partial discharges (PDs) existence in transformer windings are normally due to ageing processes, operational over stressing or defects introduced during manufacture. Although, the presence of PDs does not necessarily indicate imminent failure of a transformer, it is however, a serious insulation degradation or ageing mechanism which can be considered as a precursor of transformer failure. The initial approach taken in this thesis is based on a lumped parameter network model. The model was created and its parameters were approximated using analytical solutions based on the geometrical dimensions of transformer windings. Based on the lumped parameter network model, theoretically the rational function should be a positive-real (PR) function and it is shown later on in this thesis that the model does hold the theoretical assumptions. Nevertheless, impulse response of actual transformer windings constructed for laboratory assessment was shown differently although different methods were used to find rational functions with positive-real (PR). Due to the fact that real transformer windings do not hold the characteristic of positive real transfer function, thus, this thesis finds an alternative and proposes a different approach for PD localisation which is based on energy distribution and features extraction methods for localisation, particularly Wavelet Transform (WT) and Principal Component Analysis (PCA). The idea of the developed approach is based on the fact that any discharge occurring at any point along windings produce an electrical signal that will propagate as a travelling wave towards both ends of the windings. During the propagation of the PD signals along transformer windings, the response with respect to the propagation path taken and termination characteristics will cause attenuation and distortion to the waveforms, ultimately produced changes in the energy characteristics of the PD pulses when they reach measurement sensors.
Abd Rahman, M.S.
8217f865-63cf-4fa4-9f2b-19589bbdb2f0
Abd Rahman, M.S.
8217f865-63cf-4fa4-9f2b-19589bbdb2f0
Lewin, Paul
78b4fc49-1cb3-4db9-ba90-3ae70c0f639e

Abd Rahman, M.S. (2014) Identification of partial discharge sources and their location within high voltage transformer windings. University of Southampton, Faculty of Physical Sciences and Engineering, Doctoral Thesis, 254pp.

Record type: Thesis (Doctoral)

Abstract

This thesis is concerned with developing a new approach to high voltage transformers condition monitoring, which involve partial discharge (PD) measurement and localisation within high-voltage transformer windings. This is an important source of information for both diagnosis and prognosis of the health of power transformers. Generally, Partial discharges (PDs) existence in transformer windings are normally due to ageing processes, operational over stressing or defects introduced during manufacture. Although, the presence of PDs does not necessarily indicate imminent failure of a transformer, it is however, a serious insulation degradation or ageing mechanism which can be considered as a precursor of transformer failure. The initial approach taken in this thesis is based on a lumped parameter network model. The model was created and its parameters were approximated using analytical solutions based on the geometrical dimensions of transformer windings. Based on the lumped parameter network model, theoretically the rational function should be a positive-real (PR) function and it is shown later on in this thesis that the model does hold the theoretical assumptions. Nevertheless, impulse response of actual transformer windings constructed for laboratory assessment was shown differently although different methods were used to find rational functions with positive-real (PR). Due to the fact that real transformer windings do not hold the characteristic of positive real transfer function, thus, this thesis finds an alternative and proposes a different approach for PD localisation which is based on energy distribution and features extraction methods for localisation, particularly Wavelet Transform (WT) and Principal Component Analysis (PCA). The idea of the developed approach is based on the fact that any discharge occurring at any point along windings produce an electrical signal that will propagate as a travelling wave towards both ends of the windings. During the propagation of the PD signals along transformer windings, the response with respect to the propagation path taken and termination characteristics will cause attenuation and distortion to the waveforms, ultimately produced changes in the energy characteristics of the PD pulses when they reach measurement sensors.

Text
Abd Rahman.pdf - Other
Download (20MB)

More information

Published date: June 2014
Organisations: University of Southampton, EEE

Identifiers

Local EPrints ID: 369418
URI: http://eprints.soton.ac.uk/id/eprint/369418
PURE UUID: 49923c26-01fd-4808-ab01-848fb0b4401d

Catalogue record

Date deposited: 24 Oct 2014 14:06
Last modified: 16 Oct 2018 16:31

Export record

Contributors

Author: M.S. Abd Rahman
Thesis advisor: Paul Lewin

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×