A method for cable failure analysis based on ageing model and with consideration of daily temperatures

Huajie Yi, Andrew Mcdiarmid, Ralph Eyre-Walker, Chengke Zhou, Ian Hancock, Dong Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The physics- based electro-thermal ageing model has been widely used for analysis of cable failures and for evaluation of insulation status for single cable circuits. However, previously published approaches only reflect increased failure probability on an annual basis which cannot be used to explain the phenomenon that higher number of cable failures have been observed during summer time by Scottish Power Energy Networks (SPEN). Despite the insulation degradation accumulated annually, higher daily temperature during summer seasons resulted in extra stochastic stress applied on cable insulation and led to increasing cable failure probability. During summer seasons, the majority of cable failures occurred when daily temperature was higher than 10 °C. This paper aims to improve the electro-thermal model to evaluate remnant insulation strength and failure probability with consideration of stochastic stress due to higher daily temperature. Failure occurs when the stochastic stress overwhelms the remnant insulation strength. With the improved model, failure probability can reflect higher number of failures during the summer season.

Original languageEnglish
Title of host publication2020 8th International Conference on Condition Monitoring and Diagnosis (CMD)
PublisherIEEE
Pages114-117
Number of pages4
ISBN (Electronic)9781728159317
ISBN (Print)9781728159324
DOIs
Publication statusPublished - 16 Dec 2020

Publication series

NameProceeding - 8th International Conference on Condition Monitoring and Diagnosis, CMD 2020
PublisherIEEE
ISSN (Print)2374-0167
ISSN (Electronic)2644-271X

Keywords

  • ageing model
  • daily temperature
  • electro-thermal stress
  • remnant insulation strength
  • stochastic stress

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing
  • Energy Engineering and Power Technology
  • Safety, Risk, Reliability and Quality

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