Hierarchical Assessment Method of Transformer Condition Based on Weight-Varying Grey Cloud Model

被引：0
|
作者：
Du J. [1 ,2 ]
Sun M. [1 ,2 ]
机构：
[1] State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin
[2] Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin
来源：
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2020年 / 35卷 / 20期
关键词：
Cloud correlation; Cloud model; Condition assessment; Gray cloud clustering; Transformer; Weight-varying theory;
D O I：
10.19595/j.cnki.1000-6753.tces.190827
中图分类号：
学科分类号：
摘要：
In order to objectively and scientifically evaluate the transformer condition, a hierarchical index system for transformer condition evaluation was established, and a hierarchical assessment method for transformer condition based on weight-varying grey cloud model was proposed. Firstly, the cloud model was used to improve traditional whitening weight function to build grey cloud model. Compared with the traditional grey clustering whitening weight function, the grey cloud model could effectively reflect fuzziness, greyness and randomness for information of evaluation level. To better reflect the uncertainty of the transformer status information, the cloud correlation was calculated using index cloud model instead of index value. Then, the condition of transformer fault layer was obtained by association rules and grey cloud clustering. The overall condition of transformer was obtained by weight-varying fusion. To acquire the final evaluation result, the condition of transformer fault layer and the overall condition were considered comprehensively. Finally, the case studies verified that the proposed method is effective and superior. © 2020, Electrical Technology Press Co. Ltd. All right reserved.
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页码：4306 / 4316
页数：10
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