Modelling transformer short-circuit reliability using multi-stress accelerated test data

B Patel, Z D Wang, J V Milanovic, P Jarman

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

The high level of reliability experienced by power transformers has led to the situation that a large number of aged units are still operating in the power systems. However, uncertainty on how transformers behave when aged causes concerns over the existence of possible hidden failure modes, which have yet to be revealed by failure data. In order to establish whether aged transformers are able to maintain their operational capability when exposed to system events, such as short-circuits, multi-stress parameter analysis is required. In this paper the procedure of modelling multi-stress accelerated test data is demonstrated by using the results of a previously published paper concerning the combined effect of ageing and short-circuit forces. The results are subsequently used to determine the short-circuit reliability of transformers, through the use of a cumulative damage model. It is shown that reliability models can be constructed and justified based on an understanding of the failure mode. However, application of the results remains tentative due to the recognised shortcomings of the modelling procedure.
Original languageEnglish
Title of host publicationProbabilistic Methods Applied to Power Systems (PMAPS), 2014 International Conference on
Pages1-6
Number of pages6
DOIs
Publication statusPublished - 2014
Event13th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014 - Durham, UK
Duration: 7 Jul 201410 Jul 2014

Conference

Conference13th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014
CityDurham, UK
Period7/07/1410/07/14

Keywords

  • accelerated aging
  • ageing
  • Aging
  • asset management
  • censored data
  • cumulative damage model
  • Data models
  • hidden failure modes
  • Insulation
  • life testing
  • lifetime modelling
  • maximum likelihood estimation
  • multistress accelerated test data
  • multistress parameter analysis
  • power transformer insulation
  • power transformers
  • power transformer testing
  • reliability
  • Stress
  • transformer short-circuit reliability

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