A new approach of DGA interpretation technique for transformer fault diagnosis

• The paper submits DGA method which is the most widely technique for transformer fault diagnosis.
• The paper represents a new technique for transformer fault diagnosis that based on the dissolved gas concentration and some suggested ratios between the dissolved gases.
• The probability distribution function is used to illustrate the overlapping that causes between the fault types and result in misleading of the correct diagnosis.
• Actual laboratory data are used with the confirmed results as well as data from the credited papers.
• The proposed technique improves the diagnosis of the transformer faults based on the comparison between its results and that using the traditional techniques for the same purposes.

Dissolved Gas Analysis (DGA) is one of the most common techniques to detect the incipient faults in the oil-filled power transformers. In this paper, a new approach of DGA technique is proposed to overcome the conflict that takes place in the traditional interpretation techniques for transformer fault diagnosis. The new approach is based on the analysis of 386 dissolved gas samples data set that collected from the Egyptian electric utility chemical laboratory as well as from credited literatures. These data sets are used to build the technique model and also as a tested data set to get the technique’s accuracy. The new approach DGA diagnoses the transformer fault types based on the gas concentration percentage limit of the sum of main five gases (Hydrogen (H2), Methane (CH4), Ethan (C2H6), Ethylene (C2H4), and Acetylene (C2H2)) and some suggested gases ratios depending on the sample data set analysis. The validation of the proposed approach of DGA technique is satisfied by comparing its results with the results of the IEC Standard Code, Duval triangle and Rogers methods for the collected data set. The results refer to the ability and reliability of the new approach in transformer faults diagnostic.