Improvement of DGA interpretation using scoring index method

Abstract

Dissolved gas analysis (DGA) is the most effective method to detect incipient faults in power transformers. It uses the concentrations of various gases dissolved in the transformer oil due to decomposition of the oil and paper insulation. Gases such as hydrogen, methane, acetylene, ethylene, and ethane are generated as a results of oil decomposition, while carbon monoxide and carbon dioxide are generated due to the paper degradation. In the meantime, faults such as partial discharge, overheating, and arcing produce a range of gases. The concentrations of these gases can be used to identify faults and estimate their severity. Various techniques have been developed to interpret DGA results such the key gas method, Doernenburg, Rogers, IEC ratio-based methods, Duval triangles, and the latest Duval Pentagon methods. However, each of these techniques relies on the accumulated knowledge and experience of experts rather than quantitative scientific models, therefore different diagnoses may be reported for the same oil sample. Hence the accountability of the judgment is questionable if it only relies on one interpretation technique. This paper proposes the use of scoring point method to improve the accountability of DGA interpretation process. In this context, DGA results of several transformer oil samples are analyzed with four existing interpretation techniques; Doernenburg, Rogers, IEC, and Duval triangle methods from which a scoring index is developed for all fault types. Based on this analysis, each technique is assigned with specific weighting factor. The summation of scoring point times weightage represents the scoring index for particular faults. The proposed method is validated through DGA historical data of various transformers of pre-known health condition and life span. Results show that the proposed method can increase the accuracy of the DGA interpretation process.