Prerequisites for Transformer Lifetime ModelingTowards a Better Understanding
2010 (English)In: 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2010, IEEE , 2010, 460-463 p.Conference paper (Refereed)
The transmission transformer represent a significant asset in the electrical network. The transformer is expensive to manufacture and it is costly to replace. The cost of the transformer replacement is approximately 4 million EURO which is larger than the average component replacement activity. Therefore it is desired to make the replacement both timely and smooth to reduce unnecessary costs. Life time modeling is a tool for achieving such cost efficient replacements. This paper highlights the prerequisites for the transformer lifetime modeling. The lack of statistical failure data and a method for an overall condition assessment are identified as main issues. Furthermore, this paper presents one approach for transformer lifetime modeling based on Bayesian statistics which combines the expert opinion with the failure data in order to model the failure rate. This paper also suggests that the subjective information from the expert can be evaluated by the use of the analytic hierarchy process to achieve quality assurance. The overall objective of this paper is to present the research within the RCAM research group of transformer lifetime modeling and to enhance the understanding of the topic.
Place, publisher, year, edition, pages
IEEE , 2010. 460-463 p.
Bayesian statistics, Component replacement, Condition assessments, Cost-efficient, Electrical networks, Expert opinion, Failure data, Failure rate, Life-times, Research groups, Statistical failure data, Subjective information, Transformer replacement
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-129982DOI: 10.1109/PMAPS.2010.5528966ScopusID: 2-s2.0-77956442320ISBN: 978-142445723-6OAI: oai:DiVA.org:kth-129982DiVA: diva2:654010
2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2010; Singapore; Singapore; 14 June 2010 through 17 June 2010
QC 201310072013-10-072013-10-072014-08-26Bibliographically approved