Diagnostic Tool for Transformer Fault Detection Based on Dissolved Gas Analysis

Abstract

Dissolved gas analysis (DGA) is a diagnostic tool that used to detect the incipient faults of power transformers through the correlation between the content of gases dissolved in transformers oil and a particular malfunction. Transformer failures are often due to the lack of the dielectric strength of oil insulation and will lead to a negative impact on electrical power systems. Early stage detection of transformer faults can reduce considerably the cost of repairing the damaged transformers and hence maintain the stability of the system. Some classical methods that depend on gases concentration in transformers oils are used to interpret transformer faults such as Dornenburg, Rogers, Duval triangle and key gases methods. These methods in some cases did not give the same results; therefore, an expertise method is developed to assess the kind of fault based on the DGA. A software code is designed using logic functions to get the type of the faults in transformers from laboratory data DGA based. A comparison between the laboratory results and the code results will be accomplished. This comparison explains that the code is reliable to determine the transformer fault. The age of transformer is taken into account in our calculations. The results from the software code illustrate the program reliability as an early detection tool of transformer faults. Key