Reference
J. Fu, S. Peyghami, A. Núñez, F. Blaabjerg, and B. De Schutter,
"A tractable failure probability prediction model for predictive maintenance
scheduling of large-scale modular-multilevel-converters,"
IEEE
Transactions on Power Electronics, vol. 38, no. 5, p. 6533-6544, May
2023.
Abstract
Modular-multilevel-converters (MMCs) are vital components in direct current
transmission networks. Predictive maintenance scheduling of MMCs requires
estimations of the failure probabilities of MMCs during a period of time in the
future. Particularly, the predicted future failure probabilities are influenced
by two main factors, the mission profiles of the MMCs and the maintenance
decisions on the MMCs during the prediction period. This paper proposes a
failure probability prediction model (FPM) for MMCs by considering these two
factors. First, the expectations of the failure probabilities of the components
for all the scenarios of mission profiles are obtained. Second, in predictive
maintenance scheduling problems, the decisions to perform the maintenance
actions are represented by binary variables. When the number of submodules is
very large, using the binomial probability form currently used in reliability
engineering to express the "r-out-of-n" failure probability of arms of the MMCs
is intractable. Thus, this paper proposes a tractable form (T-form) in FPM by
observing that the submodules on one arm are homogeneous. Furthermore, an
approximation method, i.e., clustering and assignment (C&A), is proposed to
reduce the computation times for calculating the parameters needed by the
proposed T-form. Then, we perform a case study that assesses the accuracy and
computation time of the C&A approach. The results show that the accuracy of
the C&A approach is high and that the computation time is reduced
significantly compared with the accurate method. We also show that the
computation time for solving the predictive maintenance scheduling problem can
be reduced hugely by using the T-form instead of the binomial probability form.
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BibTeX
@article{FuPey:23-016,
author = {Fu, Jianfeng and Peyghami, Saeed and N{\'{u}}{\~{n}}ez, Alfredo
and Blaabjerg, Frede and De Schutter, Bart},
title = {A Tractable Failure Probability Prediction Model for Predictive
Maintenance Scheduling of Large-Scale
Modular-Multilevel-Converters},
journal = {IEEE Transactions on Power Electronics},
volume = {38},
number = {5},
pages = {6533-6544},
month = may,
year = {2023}
}