Power transformer fault diagnosis using DGA and group decision making with intuitionistic fuzzy preference relations

Because of the importance of power transformers to the electrical system, operating from transmission lines to distribution, understand their condition is critical. Analysis of dissolved gases in the insulating oil of transformers is an efficient and reliable way to perform a diagnosis. However, in some situation each method of dissolved gases interpretation can indicate one different type of fault. Thus, this paper present a multi-criteria decision making method that aggregates the information of four traditional methods, and indicates the condition of transformer. The results were promising, in way that was possible to obtain a consistent response through three different interpretations.