A Study on Reliability of Smart Meters based on Monte-Carlo Method and Fault Trees
DOI:
https://doi.org/10.13052/dgaej2156-3306.3726Keywords:
Smart meters, reliability prediction, monte-carlo sampling, fault tree analysis.Abstract
Smart meters are widely used in the power supply system, and their oper-
ational reliability is closely related to the user’s power supply reliability. It
is difficult for intelligent power metering equipment to accurately predict its
operational reliability and lifespan based on the existing technical specifi-
cations. In order to improve the accuracy of predicting the reliability and
the maintenance cycle of the smart meter, this paper proposes a method for
predicting the reliability of the smart meter based on the Monte Carlo method
and fault tree. Firstly, the occurrence time of the bottom sampling event is
simulated by the Monte-Carlo method based on the statistical data of the
annual failure rate of each module of the smart meter. Then, according to the
Fault Tree analysis of smart meters, the occurrence of the event is transformed into the fault time of the whole smart meters. The interval statistics are used
to obtain the reliability value of the smart meter. In the end, the curve of the
reliability function is obtained after fitting the reliability value. The results
show that the reliability of the smart meter obeys the exponential distribution
during the operation of 100 years. When it comes to the tenth year, the
reliability is 0.9519. This algorithm provides a guide for accurately predicting
its reliability and maintenance cycles by modularly analyzing the faults of
smart meters.
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