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

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.

Domains: Electric power

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 & Energy Systems, 2014, 56, pp.209-219. ⟨10.1016/j.ijepes.2013.11.023⟩. ⟨hal-00903990⟩