A Wide Range Robust PSS Design Based on Power System Pole-Placement Using Linear Matrix Inequality

Abstract

In this paper, a new method for robust PSS design based on the power system pole placement is presented. In this stabilizer, a feedback gain matrix is used as a controller. The controller design is proposed by formulating the problem of robust stability in a Linear Matrix Inequality (LMI) form. Then, the feedback gain matrix is designed based on the desired region of the closed loop system poles. This stabilizer shifts the poles of the power system in different operational points into the desired regions in s -plane, such that the response of the power system will have proper damping ratio in all the operational points. The uncertainties of the power system parameters are also considered in this robust technique. Finally, in order to show the advantages of the proposed method in comparison with conventional PSS, some simulation results are provided for a power system case study in different operational points.

Robust Optimization of Power System Stabilizer Parameters Based on Pole Placement Technique

“…4 and also far from the region boundary as much as possible. This requirement may be formulated as the following multi-objective function: (10) where σ n,k stands for the real part of n-the eigenvalue of the matrix A k which is obtained by combining matrix A gk with the matrix A p , B p , C p , and D p of the PSS, and ζ n,k denotes the corresponding damping factor. It can be seen that this multi-objective function tends to find PSS parameters such that σ max , the maximum real part of poles of all operating conditions, is minimum, and ζ min , the minimum damping ratio, is maximum.…”

“…In Ref. [10], a PSS design method based on the power system pole placement has been presented. Parameter uncertainty has been taken into consideration.…”

A new LPV modeling approach using PCA-based parameter set mapping to design a PSS

“…Therefore, the robustness of the PSS is a major issue [6], and synthesis of robust PSSs has been one of the most notable research topics in power and control engineering. In many research studies, such as literature reports [7], [8], [9], [10], robust performance of a controller in various operating points has been studied and investigated. Over the past years, several methods and approaches have been presented regarding robust control in power systems, especially for oscillation damping [11], [12], [13].…”

Neuro-fuzzy and nondominated sorting genetic algorithm based power system stabilizer design

“…The design methods of PSSs such as phase compensation and root locus (Ostojic, 1991), eigenvalue sensitivity analysis (Tse et al, 2001) and poles placement (Abido, 2000) are very suggestive. In (Ataei et al, 2012;Werner et al, 2003), the PSS adjustment issue is transformed into LMI problem; its solving determines the stabilizer parameters (Ataei et al, 2012). A new LMI based strategy with rank condition has been described in (Kim et al, 2010) to the design of effective PSS.…”