Maximum likelihood estimation of synchronous machine parameters from flux decay data

Author

Tumageanian, A. ; Keyhani, A. ; Moon, S.-I. ; Leksan, T. ; Xu, L.

Author_Institution

Ohio State Univ., Columbus, OH, USA

fYear

1992

fDate

4-9 Oct 1992

Firstpage

190

Abstract

A time-domain system identification procedure for estimating the parameters of a 5-kVA salient pole machine from standstill test measurements is proposed. The test consists of a DC flux decay signal applied to the d-axis and q-axis of the machine. From the recorded responses to this signal, the admittance transfer function models and the standstill frequency response (SSFR) equivalent circuit models are identified. The maximum-likelihood algorithm is used to estimate the model parameter values, and the Akaike criterion is used to select the best-fit model. The performance of the standstill models in the dynamic environment is studied through simulation of an online small-disturbance test. The results are compared with measured data

Keywords

equivalent circuits; frequency response; machine theory; maximum likelihood estimation; parameter estimation; synchronous machines; transfer functions; 5 kVA; Akaike criterion; DC flux decay signal; MLE; admittance transfer function models; d-axis; dynamic environment; equivalent circuit models; maximum likelihood estimation; online small-disturbance test; parameter estimation; q-axis; salient pole machine; standstill frequency response; standstill test measurements; synchronous machine; time-domain system identification; Admittance; Circuit testing; Maximum likelihood estimation; Parameter estimation; Signal processing; Synchronous machines; System identification; System testing; Time domain analysis; Transfer functions;

fLanguage

English

Publisher

ieee

Conference_Titel

Industry Applications Society Annual Meeting, 1992., Conference Record of the 1992 IEEE

Conference_Location

Houston, TX

Print_ISBN

0-7803-0635-X

Type

conf

DOI

10.1109/IAS.1992.244295

Filename

244295