Title :
Identification of parameters of an AC machine from standstill time domain data
Author :
Keyhani, A. ; Moon, S.-I. ; Xu, L.
Author_Institution :
Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA
Abstract :
The authors present an evaluation of the performance of the maximum likelihood (ML) method when used to estimate the linear parameters of a synchronous machine model from the standstill time-domain flux decay test data. It is shown that a unique set of parameters can be obtained and the noise effects can be dealt with effectively when the ML estimation technique is used. The results of study also show that accurate machine parameters can be identified even when signal-to-noise ratio is as low as 200:1
Keywords :
parameter estimation; synchronous machines; linear parameters; maximum likelihood method; signal-to-noise ratio; standstill time-domain flux decay test; synchronous machine; AC machines; Circuit noise; Equivalent circuits; Maximum likelihood estimation; Noise measurement; Nonlinear equations; Parameter estimation; Power system modeling; Testing; Time domain analysis;
Conference_Titel :
Electronic Applications in Transportation, 1990., IEEE Workshop on
Conference_Location :
Dearborn, MI
DOI :
10.1109/EAIT.1990.205484
