Parameter tuning of power system stabilizer using eigenvalue sensitivity

This paper proposes a method for PSS parameter tuning. The proposed method is based on the system identification using a Kalman filter. To eliminate the influence of inaccuracies of the mathematical model due to incomplete data of the system parameters, this paper proposes a procedure for identifying system parameters based on a Kalman filter. The identified system is the basis for determining the eigenvalue sensitivity function. PSS tuning is carried out based on the eigenvalue sensitivity analysis of changes of PSS parameters. In order to obtain the eigenvalue sensitivity function on the PSS parameter in a wider range of parameter values, it has been proposed to determine eigenvalues on the basis of the Bairstow method for solving polynomial equations. The entire procedure can be applied on-line, so the PSS structure and settings can be adaptive. Experimental tests carried out on a synchronous generator connected to an AC system demonstrate the effectiveness of the proposed method. Performance of the PSS tuned by using the proposed method was compared with the performance of the PSS tuned by using eigenvalue sensitivity.

► Eigenvalue sensitivity function is used for PSS parameter tuning.
► The proposed method is based on the system identification using a Kalman filter.
► Eigenvalue sensitivity function is determined by applying the Bairstow method.
► Performance of the PSS tuned by using the proposed method was experimentally tested.