Identification of power transformer models from frequency response data: A case study

A recent frequency-domain, subspace-based algorithm as well as the well-known nonlinear least-squares algorithm are used in the identification of a power transformer whose frequency response has a dynamic range of 1 MHz. When the model complexity is not restricted, both the algorithms produce highly accurate models. Low-complexity models are extracted from the high-order identified ones via the method of balanced truncation. It is observed that this two-step procedure yields more accurate results than an approach of direct identification of a low-order model. The utility of identified models for the purpose of transformer fault detection is also briefly discussed. (C) 1998 Elsevier Science B.V. All rights reserved.