Open AccessA cloud and evidential reasoning integrated model for insulation condition assessment of high voltage transformers
Author(s) -
Liao Ruijin,
Zhang Yiyi,
Yang Lijun,
Zheng Hanbo,
She Xu
Publication year - 2014
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.1738
Subject(s) - transformer , reliability engineering , randomness , evidential reasoning approach , engineering , distribution transformer , power transmission , fuzzy logic , computer science , voltage , electrical engineering , decision support system , data mining , artificial intelligence , power (physics) , mathematics , business decision mapping , statistics , physics , quantum mechanics
SUMMARY Power transformers of high voltage play a key role in the power transmission system. Statistics show that acquiring an accurate assessment of transformer insulation can avoid financial losses of electrical companies, because it can detect a potential failure and therefore decrease the risk of transformer failure. Condition assessment of transformers is full of uncertain, fuzzy and randomness information and can be considered as a multiple‐attribute decision‐making problem. Aiming at this problem, this study presents a cloud and evidential reasoning integrated approach for assessing the condition of transformers. Data from the main body, maintenance record and accessory were chosen to form the assessment index system. Analysis results show that the integrated approach is effective and provides some valuable information to the maintenance of high voltage transformer. Copyright © 2013 John Wiley & Sons, Ltd.