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Aiming at the problem that the transformer condition evaluation factors have fuzzy and gray characteristics and fixed weight (FW) can not accurately evaluate the condition, we proposed a condition evaluation method for transformer based on fuzzy grey clustering and variable weight. The method is applied to evaluate transformer condition layer by layer. Firstly, the confidence degree of the association rules is introduced to determine the FW of key indicators. According to the classification of transformer state grade, the triangle whiten function is established. The grey clustering coefficient (GCC) matrix and fault layer evaluation results are obtained through grey clustering method. Then the variable weight (VW) is obtained by combining variable weight synthesis mode, and then the transformer condition is evaluated by fuzzy evaluation method. The transformer test report data is carried out as case analysis and the result shows that the method we proposed can assess the transformer condition objectively and accurately.

Comprehensive Evaluation of Transformer Condition Based on Fuzzy Grey Clustering and Variable Weight