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A novel method of decision‐making for power transformer maintenance based on failure‐probability‐analysis
Author(s) -
Yang Hang,
Zhang Zhe,
Yin Xianggen
Publication year - 2018
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22618
Subject(s) - reliability engineering , transformer , engineering , condition based maintenance , electric power system , optimal maintenance , computer science , power (physics) , electrical engineering , voltage , physics , quantum mechanics
As the key requirement of the power system, the power transformer's running state of security is directly related to the safety and stability of entire power system. Since condition‐based maintenance for a power transformer cannot directly determine the best maintenance cycle, from a better engineering application perspective, this paper proposes a novel maintenance strategy based on failure probability analysis. First, the power transformer's basic fault probability curve is fitted using the nonlinear least‐squares method. Second, comprehensively considering the long‐term evolution factors and the short‐term sudden factors, the transformer's actual fault probability model is established through amending its basic fault probability model. Third, in accordance with the periodic maintenance experience and the transformer's actual fault probability model, the best maintenance cycle is suggested using the threshold constraint. Finally, the simulation results testify that the proposed maintenance strategy can provide a more accurate maintenance cycle than the existing condition‐based maintenance and can better meet the requirement of engineering applications. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.