Estimation of generator parameters using evolutionary programming

This paper presents a new approach of using evolutionary programming (EP) to estimate the synchronous generator parameters. The EP is very powerful to search the real values of the parameters with measurements of generator outputs which are highly contaminated by noises, by contrast to the extended Kalman filter which is used currently for parameter estimation. Comparison between the two different methodologies is given in the paper to show the potential of applications of the EP to parameter estimation and system modelling.