Affiliations: [a] School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, P.R. China | [b] Qingyao Science and Technology Co., Ltd , Zhengzhou, China
| [c] Power Supply Service Management Center of State Grid Jiangxi Electric Power Co., Ltd, Nanchang, China
Correspondence:
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Corresponding author. Lintao Zhou, School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, P.R. China. E-mail: [email protected].
Abstract: Accurately diagnosing power transformer faults is critical to improving the operational reliability of power systems. Although some researchers have made great efforts to improve the accuracy of transformer fault diagnosis, accurate diagnosis of multiple faults is still a difficult problem. In order to improve the accuracy of transformer multiple faults diagnosis, a multiple fault diagnosis method based on interval fuzzy probability is proposed. Different from the previous methods which provide single-value probability, this method use probability interval to represent the occurrence degree of various possible faults, which can objectively predict the potential faults that occurring in a transformer and provide a more reasonable explanation for the diagnosis results. In the proposed method, the interval fuzzy set is used to describe the evaluation of state variables and the interval fuzzy probability model based on interval weighted average is applied to integrate the fault information. The representative matrix of fault types based on fuzzy preference relationship is established to estimate the relative importance of each gas in the dissolved gases. The proposed method can provide the probability of probable faults in transformer, help engineers quickly determine the type and location of faults, and improve the accuracy of diagnosis and maintenance efficiency of transformer. The effectiveness of the method is verified with case studies.
Keywords: Multiple faults diagnosis, Power transformer, Interval fuzzy probability, Interval weighted average
