Identification of excitation system models based on on-line digital measurements

Author

Wang, Jin-Cheng ; Chiang, Hsiao-Dong ; Huang, Chiang-Tsung ; Chen, Yung-Tbng ; Chang, Chung-Liang ; Huang, Chiung-Yi

Author_Institution

Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA

Volume

10

Issue

3

fYear

1995

fDate

8/1/1995 12:00:00 AM

Firstpage

1286

Lastpage

1293

Abstract

Accurate and sufficient detailed excitation system models are essential to the precise calculations of power system stability limits. This paper presents, in detail, a procedure for identifying excitation system models based on the online digital measurements from a plant transient recorder system. A solution algorithm for identifying parameters of the excitation system models is devised and implemented. The gradient averaging stochastic approximation method is employed to handle nonlinearity of the power system models. Detailed numerical results based on the online measured data of the Taipower system are included

Keywords

approximation theory; electric machines; exciters; machine theory; parameter estimation; power system stability; stochastic processes; excitation system models; gradient averaging stochastic approximation method; model identification; numerical simulation; online digital measurements; power system stability limits; solution algorithm; Approximation methods; Least squares methods; Parameter estimation; Power system modeling; Power system planning; Power system stability; Power system transients; Stochastic systems; Testing; Voltage;

fLanguage

English

Journal_Title

Power Systems, IEEE Transactions on

Publisher

ieee

ISSN

0885-8950

Type

jour

DOI

10.1109/59.466525

Filename

466525