Complementary Analysis for DGA Based on Duval Methods and Furan Compounds Using Artificial Neural Networks

Abstract

Power transformers play an important role in electrical systems; being considered the core of electric power transmissions and distribution networks, the owners and users of these assets are increasingly concerned with adopting reliable, automated, and non-invasive techniques to monitor and diagnose their operating conditions. Thus, monitoring the conditions of power transformers has evolved, in the sense that a complete characterization of the conditions of oil–paper insulation can be achieved through dissolved gas analysis (DGA) and furan compounds analysis, since these analyses provide a lot of information about the phenomena that occur in power transformers. The Duval triangles and pentagons methods can be used with a high percentage of correct predictions compared to the known classical methods (key gases, International Electrotechnical Commission (IEC), Rogers, Doernenburg ratios), because, in addition to the six types of basic faults, they also identify four sub-types of thermal faults that provide important additional information for the appropriate corrective actions to be applied to the transformers. A new approach is presented based on the complementarity between the analysis of the gases dissolved in the transformer oil and the analysis of furan compounds, for the identification of the different faults, especially when there are multiple faults, by extending the diagnosis of the operating conditions of the power transformers, in terms of paper degradation. The implemented software system based on artificial neural networks was tested and validated in practice, with good results.

Application of Dissolved Gas Analysis Standards and Methods on Raw Gas Sample

“…It does not include a zone that represents normal condition. Thus, gas dissolved in the transformer due to normal insulation aging would be detected as fault, which leads to analysis error [7].…”

“…However, different DGA results of Duval Triangle and Pentagons may indicates that the transformer has a combination of faults. Thus, Duval Pentagons shall not replace Duval Triangle but to provide additional information [7].…”

Multilevel SVM and AI based Transformer Fault Diagnosis using the DGA Data

“…DGA can be used to determine the most likely situation inside transformers, provide early warnings and diagnoses, and boost the chance of acting appropriately, similar to how doctors check a human body with a stethoscope. DGA is a sensitive and reliable technology for locating problems in power transformers [20][21][22][23][24][25] The IEC Ratios method employs the following five gases: H2, CH4, C2H2, C2H4, and C2H6, as well as the following gas ratios: C2H2/C2H4, CH4/H2, and C2H4/C2H6. The following table correlates fault categories to gas ratios, and decisions are made such that when key-gas ratios surpass their specific limitations, an incipient fault in the transformer has occurred.…”

Improved Monitoring and Diagnosis of Transformer Solid Insulation Using Pertinent Chemical Indicators

“…The lifetime of a transformer is generally assumed to be equivalent to the lifetime of its solid insulation. This is because many dielectric defects or failures in the insulating system lead to transformer collapse [3][4][5][6]. Figure 1 depicts two sets of distribution transformers that have been removed from the power system due to damage to their solid insulation.…”