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Prerequisites for Transformer Lifetime ModelingTowards a Better Understanding
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. (Reliability Centered Asset Management (RCAM))ORCID iD: 0000-0002-5138-0272
KTH, School of Electrical Engineering (EES), Electromagnetic Engineering. (Reliability Centered Asset Management (RCAM))ORCID iD: 0000-0002-2964-7233
2010 (English)In: 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2010, IEEE , 2010, 460-463 p.Conference paper, Published paper (Refereed)
Abstract [en]

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.
Keyword [en]
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
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-129982DOI: 10.1109/PMAPS.2010.5528966Scopus ID: 2-s2.0-77956442320ISBN: 978-142445723-6 (print)OAI: oai:DiVA.org:kth-129982DiVA: diva2:654010
Conference
2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2010; Singapore; Singapore; 14 June 2010 through 17 June 2010
Note

QC 20131007

Available from: 2013-10-07 Created: 2013-10-07 Last updated: 2014-08-26Bibliographically approved
In thesis
1. Lifetime modeling and management of transformers
Open this publication in new window or tab >>Lifetime modeling and management of transformers
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This work have studied and developed lifetime estimation methods for the power transformer and how these could be used for asset management purposes. It is researchperformed in the intersection of the fields of reliability theory, statistical analysis, and stochastic process theory applied to lifetime estimations and management of transformers.

The chosen approaches are the following. The thesis assess the effect of thermal stresses on the lifetime of the transformer. The effect of hotspot temperature is assessed with a loss of life measure. Within this study, improvements to the thermal model have been made.

The thesis moves on to an alternative method for lifetime estimation in which diagnostic measurements are forecasted using a stochastic process and iterative realizations of this stochastic process is used to estimate a probability distribution for the transformer.

The thesis moves on to study the loss of life measure from a system perspective by calculating the loss of life estimate from the load profiles of cold load pickup, increased electric vehicle penetration, and normal operation. These are applied in such a way that they can be used for asset management purposes.

Then, the thesis uses estimates of failure times with the aim to reach a probabilistic, dynamic capacity rating selection method which use a failure rate which is conditioned on the time-dependent load level.

Abstract [sv]

Det här arbetet har studerat och utvecklat metoder för estimering av transformatorlivslängden och hur dessa skulle kunna användas för hantering av tillgångar1. Detta är forskning framförd inom skärningspunkten mellan fälten: tillförlitlighetsteori, statistiskanalys och statistisk process teori. Detta har sedan blivit applicerat på hantering av transformatorer som tillgång.

En beskrivning av de valda ansatserna följer. Den här avandlingen skattar effekten av termisk påfrestning på livslängden av en transformator. Effekten av hotspot temperaturenestimeras med ett mått som skattar livslängdsförlusten för given drift. Inom den här studien så har förbättringar påden termiska modellen gjorts.

Avhandlingen går vidare till att utveckla en alternativ metod för livslängds estimering som nyttjar diagnostiska mätningar genom att prognosticera dessa med hjälp av en stokastisk process och genom iterativa realisationer av dessa, estimera sannolikhetsfördelningen för transformatorns livslängd.

Avhandlingen går vidare till att positionera livslängsförlustsmåttet i ett system genom att beräkna livslängdsförlusten under de olika driftförhållandena: kallastpåslag, ökad penetration av elektriska fordon, och normal drift. Dessa implementeras så att de kan användas med syftet att hantera tillgångar.

Slutligen så går avhandlingen vidare till att estimera feltider med syftet att välja en probabilistisk, dynamisk kapacitet som använder en felintensitet som är betingad på en tidsberoende belastningsnivå.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. xiii, 60 p.
Series
Trita-EE, ISSN 1653-5146 ; 2013:037
Keyword
transformers, lifetime modeling, asset management, thermal modeling, lifetime estimation
National Category
Engineering and Technology
Identifiers
urn:nbn:se:kth:diva-129971 (URN)978-91-7501-883-6 (ISBN)
Public defence
2013-10-21, F3, Lindstedtsvägen 26 (Entreplan), KTH, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

QC 20131007

Available from: 2013-10-07 Created: 2013-10-07 Last updated: 2013-10-07Bibliographically approved

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Rosenlind, Johanna

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