Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727884
Title: Ageing assessment of transformer insulation through oil test database analysis
Author: Tee, Sheng Ji
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2016
Availability of Full Text:
Access from EThOS:
Access from Institution:
Abstract:
Transformer ageing is inevitable and it is a challenge for utilities to manage a large fleet of ageing transformers. This means the need for monitoring transformer condition. One of the most widely used methods is oil sampling and testing. Databases of oil test records hence manifest as a great source of information for facilitating transformer ageing assessment and asset management. In this work, databases from three UK utilities including about 4,600 transformers and 65,000 oil test entries were processed, cleaned and analysed. The procedures used could help asset managers in how to approach databases, such as the need for addressing oil contamination, measurement procedure change and oil treatment discontinuities. An early degradation phenomenon was detected in multiple databases/utilities, which was investigated and found to be caused by the adoption of hydrotreatment oil refining technique in the late 1980s. Asset managers may need to monitor more frequently the affected units and restructure long term plans. The work subsequently focused on population analyses which indicated higher voltage transformers (275 kV and 400 kV) are tested more frequently and for more parameters compared with lower voltage units (33 kV and 132 kV). Acidity is the parameter that shows the highest correlation with transformer in-service age. In addition, the influence of the length of oil test records on population ageing trends was studied. It is found that it is possible to have a representative population ageing trend even with a short period (e.g. two years) of oil test results if the transformer age profile is representative of the whole transformer population. Leading from population analyses, seasonal influence on moisture was investigated which implies the importance of incorporating oil sampling temperature for better interpretation of moisture as well as indirectly breakdown voltage records. A condition mismatch between dielectric dissipation factor and resistivity was also discovered which could mean the need for revising the current IEC 60422 oil maintenance guide. Finally, insulation condition ranking was performed through principal component analysis (PCA) and analytic hierarchy process (AHP). These two techniques were demonstrated to be not just capable alternatives to traditional empirical formula but also allow fast, objective interpretation in PCA case, as well as flexible and comprehensive (objective and subjective incorporations) analysis in AHP case.
Supervisor: Liu, Qiang Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.727884  DOI: Not available
Keywords: Seasonal Influence on Moisture ; Condition Mismatch ; Correlation with Age ; Analytic Hierarchy Process ; Health Index ; Principal Component Analysis ; Population Analysis ; Database Analysis ; Asset Management ; Condition Monitoring ; Ageing Assessment ; Ageing ; Transformer ; Early Degradation Phenomenon
Share: