DocumentCode
3095198
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
fYear
1990
fDate
18-19 Oct 1990
Firstpage
107
Lastpage
112
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic Applications in Transportation, 1990., IEEE Workshop on
Conference_Location
Dearborn, MI
Type
conf
DOI
10.1109/EAIT.1990.205484
Filename
205484
Link To Document