Characterizing transformer HV–LV winding FRA curves through derivation of transfer functions from FRA data

Abstract

Mechanical malfunctions pose a significant threat to the reliability of power transformers. Frequency Response Analysis (FRA) of transformer windings (TWs) serves as a predictive technology, allowing the assessment of mechanical conditions based on collected FRA data. Changes in the winding structure manifest in FRA characteristics, making it possible to detect incipient faults. This paper presents the derivation of transfer functions (TF) equations through processing FRA data, aiming to investigate and interpret the characteristics of TWs. The derived TFs are utilized to mathematically describe FRA curves, enabling the characterization of winding structures by observing the FRA curves generated from these TF equations. Not only do the derived TFs yield very similar FRA curves, but the TF estimation also provides valuable insights for assessing TW malfunctions. The similarity analysis, using calculated RMSE and MAE values of 0.4807 and 0.2020, respectively, demonstrates a strong correlation between the derived TF curves and the measured FRA curves. This affirms the validity of TF estimation and underscores its significant impact on the advancement of FRA technology.