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Health Indexing of Norwegian Power Transformers

Brandtzæg, Georg
Master thesis
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13181_FULLTEXT.pdf (2.942Mb)
13181_ATTACHMENT.zip (3.218Mb)
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http://hdl.handle.net/11250/2368049
Utgivelsesdato
2015
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Samlinger
  • Institutt for elkraftteknikk [1941]
Sammendrag
In this thesis, a health index model for condition evaluation of power transformers

is proposed. A health index is a tool that processes service and condition data into

a score which describes the overall health of an asset. The motivation behind this

is to objectively and confidently assess the condition of power transformers so that

reinvestment and maintenance decisions might be justified. This way, the technical

lifetime of healthy assets might be safely increased, while risky assets can be identified

and taken care of before they fail. Health indexing is particularly useful for

evaluation of large transformer fleets, since it makes it easy to identify the assets

most in need of additional attention. An important prerequisite for a health index

to be useful is, however, that the availability of data is considered in the model

design. A health index intended for use in Norway will thus have to be customized

to the data availability faced by most Norwegian utilities and transformer users.

In order to identify which assessment methods that are suited for use in a Norwegian

health index, four existing health index models have been reviewed. Based

on these reviews and the general data collection practices of Norwegian utilities, a

health index model has been proposed. Its main inputs for assessment are: Dissolved

gas analysis, oil sample analysis, temperature or load history, maintenance

history and particular design data. This information is processed through assessment

modules that each evaluate different subsystems of the transformer. For these

assessment modules to reflect the degradation of transformers in a best possible

way, emphasis has been put on identifying the most important failure modes and

aging mechanisms.

In order to test the performance of the proposed model, it has been applied to

seven different transformers. The results from this analysis show that the model is

capable of differentiating between assets in different conditions and that the health

index score appears to be a rough, but reliable, indication of the actual condition

of a transformer.
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