Prognostic modeling of transformer aging using Bayesian particle filtering

Catterson, Victoria (2014) Prognostic modeling of transformer aging using Bayesian particle filtering. In: 2014 IEEE Conference on Electrical Insulation and Dielectric Phenomena, 2014-10-19 - 2014-10-22.

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Abstract

The goal of condition monitoring is to accurately assess the current health of an asset, in order to generate a prognosis, i.e. predict its remaining useful life. In the absence of a fault which causes premature failure, transformer degradation is linked to paper aging. Research and experience have resulted in models of paper aging where hotspot temperature is the key driver. However, these deterministic equations give a false sense of certainty about remaining insulation life. This paper demonstrates the use of Bayesian particle filtering for transformer life prognostics. This technique allows quantification of the uncertainties surrounding aspects such as the initial degree of polymerization of the paper, the relationship between hotspot temperature and measurands, and the accuracy of measurements. A case study from an in-service 180 MVA transformer is used to illustrate its potential.

ORCID iDs

Catterson, Victoria ORCID: https://orcid.org/0000-0003-3455-803X

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  Item type:	Conference or Workshop Item(Paper)
  ID code:	49432
  Dates:	Date Event October 2014 Published
  Notes:	(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering
  Department:	Faculty of Engineering > Electronic and Electrical Engineering
  Depositing user:	Pure Administrator
  Date deposited:	01 Oct 2014 04:12
  Last modified:	12 Dec 2024 16:15
  Related URLs:	Event
  URI:	https://strathprints.strath.ac.uk/id/eprint/49432