Title :
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
fDate :
8/1/1995 12:00:00 AM
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;
Journal_Title :
Power Systems, IEEE Transactions on
