Transformer Winding Deformation and Insulation Characteristic Effects on Frequency Response Analysis

摘要

Frequency Response Analysis (FRA) is considered an accurate, fast, economical and non-destructive method for the detection of winding deformation within power transformers, providing detailed information on electrical properties of this asset. Changes in winding configuration, as well as other transformer active part structures would almost certainly cause variation in the frequency response spectrum. This can be exploited for mechanical defect recognition. On the other hand, transformer oil deterioration, temperature variation as well as water absorbed by the paper can cause transformer insulation characteristics to change over the time. In fact, capacitances, self- and mutual inductances and conductor resistances might be altered due to any changes in above mentioned factors. In turn, the frequency response of the winding will change accordingly. Thus in the interpretation of the FRA spectrum for evidence of winding deformation, the influence of insulation characteristic on the spectrum must be taken into consideration. FRA deviation due to the winding deformation or insulation characteristic changes becomes even more complicated to interpret when FRA baseline and measured spectra are taken under different temperatures and moisture contents. In such a case, existing FRA evaluation methods using statistical indicators are likely to reveal incorrect prognosis. Hence in this thesis, the aim of the research is to distinguish the insulation characteristic impacts on FRA spectrum from winding deformation. To this end, resonances and anti-resonances in FRA spectrum over different frequency bands are examined in detail and interpretations are provided. FRA deviation due to the transformer winding deformation is discussed analytically, modelled and simulated. The results are then compared to practical measurements. Insulation characteristic changes in transformer are studied through temperature and moisture variations to recognise their influences on FRA data. FRA capability in recognising moisture migration from the paper insulation of transformer winding is recommended and its potential application in transformer winding dry-out process evaluation is revealed in this research. Finally, possible offline and online solutions to distinguish the impact of moisture and temperature variations on winding deformation diagnosis are provided. Online FRA measurement and its required setup as a potential future approach in transformer condition monitoring are discussed.