The most recent power transformers installed in the national transmission network are insulated using ester oils; these new insulating oils have a very high biodegradability and high flame and fire points. Thanks to a better fire behaviour of these new oils, ester insulated transformers are less exposed to the risk of fire and explosion and can be even operate at higher temperatures, with obvious advantages in terms of overloadability. However, the degradation mechanisms of the paper/ester insulating system, especially in particularly severe transformer operating conditions, are still little investigated and it is necessary to identify adequate diagnostic methodologies to detect early degradation.

The research activity of the 2019-2021 three-year period concerns the analysis of the degradation problems of power transformers insulated using ester oil and the related diagnostic methodologies. The activity carried out and described in this report concerned the examination of the state of the art of the on the issues of the solid ester insulating system and in particular the chemical markers produced by the degradation of the insulating paper: furfuraldehyde (2-FAL), alcohols (methanol, MeOH and ethanol, EtOH) and moisture content. This study showed that 2-FAL and methanol can both be used as indicators of degradation in esters. The concentrations of 2-FAL, especially those produced by the degradation of Thermally Upgraded Kraft (TUK) paper, are lower in ester oil than those released in mineral oil. However, the 2-FAL values reported in the literature still seem to be detectable with optical methods based on the use of optical sensors and sensitive MIP (Molecular Imprinted Polymer) interfaces. The functionality tests of the MIP interfaces conducted in ester insulating oil did not reveal any criticality: it is confirmed that the MIP technology is applicable for measurements in ester oil and that the MIP thickness is a crucial parameter to operate in the range of analysable refractive index values. Through subsequent standardisation tests in ester solutions at different 2-FAL concentrations, it will be possible to determine the sensitivity and ester affinity constant of the sensors used. The optical detection of methanol in the gaseous phase will instead require evaluating the application of new types of molecularly imprinted receptors and new sensor configurations.

To determine the moisture content in the paper-ester insulation system, the dielectric methodology was identified; one aspect to be investigated is the influence of the polar properties of the ester on the dielectric response of the solid ester insulation system and the related diagnostic parameters (capacitance, dissipation factor). An increase in the moisture content in the paper following the degradation of the solid insulation system could also have a negative impact on the tightening of the transformer windings; a loosening of the winding can make the transformer particularly exposed to permanent damage during an external short circuit. To increase the reliability of the diagnosis of these faults, the possibility of using Machine Learning methods applied to the analysis of vibration data of transformers was preliminarily assessed. This report describes the results of this first investigation which clearly show that by means of Support Vector Machine (SVM) algorithms of the vibration spectra, it is possible to correctly identify the loosening of the winding during subsequent repositioning of the sensor in the same position of the case. The plan is to extend the analysis to all measuring points of the transformer.