Nie Dexin
State Grid Electric Power Research Institute, Wuhan

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Transformer State Assessment Method Based on Fuzzy and Evidence Theories Xie Jianghong; Wang Haipeng; Nie Dexin; Song You; Cai Wei
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 7: July 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i7.pp5096-5103

Abstract

Accurate and reliable assessment of power equipment operation state is the premise and basis for maintenance of power system state. This article builds the transformer body state assessment model based on fuzzy and evidence theories taking 500kV oil-immersed transformer as the object of research. The representative parameters in preventive test are selected as state assessment indicators by making reference to the factory values and threshold-crossing values of which the indicator normalization is carried out to determine the degrees of membership of each indicator relative to different state assessment levels using fuzzy evaluation method. These indicators are divided into three sub-evidence bodies, i.e. gas dissolved in oil, oilation test and electrical test, and information combination of these three sub-evidence bodies is carried out using evidence theory to further assess the operation state of transformer body. The effectiveness of this assessment model applied in state assessment of transformer body is verified by example analysis of the data of a 500kV transformer. This assessment model has clear ideas and doesn’t need too much historical data, it provides a new method for transformer state assessment.