Maximum likelihood estimation of synchronous machine parameters and study of noise effect from DC flux decay data
Ali Keyhani, S. I. Moon
Ohio State Univ, Columbus, OH, USA ;
This paper appears in : IEE Proceedings on Generation, Transmission and Distribution
Date: January 1992
Abstract:
The paper presents 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 also show that accurate machine
parameters can be identified when the signal/noise
ratio is approximately 200 : 1.