Failure Prediction and Replacement Strategies for Smart Electricity Meters Based on Field Failure Observation

Sensors (Basel). 2022 Dec 14;22(24):9804. doi: 10.3390/s22249804.

Abstract

It is helpful to have a replacement strategy by predicting the number of failures of in-service electricity meters. This paper presents a failure number prediction method for smart electricity meters based on on-site fault data. The prediction model was constructed by combining Weibull distribution with odds ratios, then the distribution parameters, failure prediction number, and confidence intervals of prediction number were calculated. A strategy of meter replacement and reserve were developed according to the prediction results. To avoid the uncertainty of prediction results due to the small amount of field data information, a Bayesian failure number prediction method was developed. The research results have value for making operation plans and reserve strategies for electricity meters.

Keywords: Bayesian; Weibull distribution; electricity meter; failure number prediction; replacement strategies.

MeSH terms

  • Bayes Theorem
  • Electricity*
  • Uncertainty

Grants and funding

This research was sponsored by the Science and Technology Project of State Grid Shandong Electric Power Company (2020A—134—Research and Application of Operational Situational Awareness and Reliability Assessment Technology for Area Measuring Equipment) and by the Project of Reserve Leaders of Heilongjiang Provincial Leading Talent Echelon.