Smart Electricity Meter Reliability Prediction based on Accelerated Degradation Testing and Modeling

Zhou Yang 1 Xun-Xia Chen 1 Yan-Fu Li 2 Enrico Zio 2 Rui Kang 1
1 Department of Reliability and System Engineering
2 SSEC - Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec
Abstract : The smart electricity meter (SEM) is one of the most critical elements of smart grids. The billing function of SEM is one of its most important functions to its operators and end-users. Because the SEM devices need to be highly reliable, in this study we conduct accelerated degradation tests (ADTs) for the prediction of SEM reliability with respect to the billing function. For designing the ADTs, we have identified five key modules and their components, two performance indicators, and three possible degradation stressors. Six ADTs are conducted under different configurations of the stressors. The test data are then used to fit degradation paths by linear regression models. Extrapolation to the failure threshold allows the prediction of the Time-to-Failure of SEM. Finally, the reliable lifetime of the SEM is predicted by an accelerated degradation function which is obtained by fitting a Weibull failure time distribution.
Document type :
Journal articles
Complete list of metadatas

Cited literature [31 references]  Display  Hide  Download
https://hal-supelec.archives-ouvertes.fr/hal-00903990
Contributor : Yanfu Li <>
Submitted on : Wednesday, November 13, 2013 - 3:07:01 PM
Last modification on : Monday, May 7, 2018 - 2:29:54 PM
Long-term archiving on : Friday, February 14, 2014 - 9:30:10 AM

File

Smart_Electricity_Meter_LifePr...
Files produced by the author(s)

Identifiers

Collections

EC-PARIS | SUPELEC | SUP_E3S | LGI | CENTRALESUPELEC | EDF | LGI-SR

Citation

Zhou Yang, Xun-Xia Chen, Yan-Fu Li, Enrico Zio, Rui Kang. Smart Electricity Meter Reliability Prediction based on Accelerated Degradation Testing and Modeling. International Journal of Electrical Power and Energy Systems, Elsevier, 2014, 56, pp.209-219. ⟨10.1016/j.ijepes.2013.11.023⟩. ⟨hal-00903990⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

881

Files downloads

1466

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD