High frequency simulation of transformer windings for diagnostic tests
The change in business dynamics, brought on by the deregulation of the electricity industry has had an impact on the technical operations of the companies involved. To maintain competitiveness, industries must maintain a high level of efficiency and reliability. This has led to the shift to condi...
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ndltd-UBC-oai-circle.library.ubc.ca-2429-175502018-01-05T17:39:00Z High frequency simulation of transformer windings for diagnostic tests Singh, Arvind The change in business dynamics, brought on by the deregulation of the electricity industry has had an impact on the technical operations of the companies involved. To maintain competitiveness, industries must maintain a high level of efficiency and reliability. This has led to the shift to condition monitoring from scheduled maintenance schemes especially for expensive assets which are not immediately replaceable such as power transformers. High current surges impacting power transformers often cause winding deformations. These pose safety risks and heavy financial losses to the utility in spot market buying when failures occur. Long replacement times can have crippling financial effects on a company if there is no replacement for the transformer when a failure occurs. As a result of this diagnostic methods which estimate the transformer condition have become increasingly important. These allow personnel to make decisions on replacing or relocating a power transformer, in keeping with the financial objectives of the company. In this report an overview of the methods used in obtaining winding signatures used for condition monitoring is presented. An equivalent circuit winding model based on multiphase transmission line theory is developed which includes enough detail to allow for an accurate simulation. The circuit model for a specific transformer winding was implemented using Microtran software. The model was used to compare the response of the commonly used transadmittance signature to the characteristic impedance signature of the winding for different types of deformations (simulated by changing different capacitances in the model). It was found that the methods were comparable in sensitivity with the transadmittance being only marginally better. The characteristic impedance signature however had the advantage of showing a constant percentage change over its frequency range for a given distortion. This makes it easier to quantify winding movement. The use of both methods in conjunction may serve as a more efficient method of classifying physical winding changes. Applied Science, Faculty of Electrical and Computer Engineering, Department of Graduate 2010-01-06T00:04:29Z 2010-01-06T00:04:29Z 2006 2006-05 Text Thesis/Dissertation http://hdl.handle.net/2429/17550 eng For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
collection |
NDLTD |
language |
English |
sources |
NDLTD |
description |
The change in business dynamics, brought on by the deregulation of the electricity
industry has had an impact on the technical operations of the companies involved. To
maintain competitiveness, industries must maintain a high level of efficiency and
reliability. This has led to the shift to condition monitoring from scheduled maintenance
schemes especially for expensive assets which are not immediately replaceable such as
power transformers.
High current surges impacting power transformers often cause winding deformations.
These pose safety risks and heavy financial losses to the utility in spot market buying
when failures occur. Long replacement times can have crippling financial effects on a
company if there is no replacement for the transformer when a failure occurs. As a result
of this diagnostic methods which estimate the transformer condition have become
increasingly important. These allow personnel to make decisions on replacing or
relocating a power transformer, in keeping with the financial objectives of the company.
In this report an overview of the methods used in obtaining winding signatures used for
condition monitoring is presented. An equivalent circuit winding model based on
multiphase transmission line theory is developed which includes enough detail to allow
for an accurate simulation. The circuit model for a specific transformer winding was
implemented using Microtran software. The model was used to compare the response of
the commonly used transadmittance signature to the characteristic impedance signature of
the winding for different types of deformations (simulated by changing different
capacitances in the model).
It was found that the methods were comparable in sensitivity with the transadmittance
being only marginally better. The characteristic impedance signature however had the
advantage of showing a constant percentage change over its frequency range for a given
distortion. This makes it easier to quantify winding movement. The use of both methods
in conjunction may serve as a more efficient method of classifying physical winding
changes. === Applied Science, Faculty of === Electrical and Computer Engineering, Department of === Graduate |
author |
Singh, Arvind |
spellingShingle |
Singh, Arvind High frequency simulation of transformer windings for diagnostic tests |
author_facet |
Singh, Arvind |
author_sort |
Singh, Arvind |
title |
High frequency simulation of transformer windings for diagnostic tests |
title_short |
High frequency simulation of transformer windings for diagnostic tests |
title_full |
High frequency simulation of transformer windings for diagnostic tests |
title_fullStr |
High frequency simulation of transformer windings for diagnostic tests |
title_full_unstemmed |
High frequency simulation of transformer windings for diagnostic tests |
title_sort |
high frequency simulation of transformer windings for diagnostic tests |
publishDate |
2010 |
url |
http://hdl.handle.net/2429/17550 |
work_keys_str_mv |
AT singharvind highfrequencysimulationoftransformerwindingsfordiagnostictests |
_version_ |
1718590556415721472 |