By Topic

Identification of high-order synchronous generator models from SSFR test data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
A. Keyhani ; Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA ; H. Tsai

This paper presents a direct maximum-likelihood estimation procedure to identify the synchronous machine models based on the standstill frequency response (SSFR) test data. The method presented in this study is the first and only algorithm utilizing all available SSFR test data under both shorted and open field circuit conditions to establish a unique equivalent circuit model by maximizing the conditional probability density function of the error residuals. The method is applied to the modeling of two well-known generators, namely the Rockport and Nanticoke generators, using the measured SSFR test data. The results of the study show that by incorporating both the open and short-circuit SSFR data in the modeling process, the SSFR characteristics of the two generators can be accurately represented by the established high order synchronous models up to 1 kHz. The identified synchronous machine model consists of five amortisseur windings on each axis. In addition, an eddy-current effect impedance is included in the d-axis model for representing the increased influence of rotor eddy current under the open-circuit test condition

Published in:

IEEE Transactions on Energy Conversion  (Volume:9 ,  Issue: 3 )