Robust control design of power system stabilizers using multivariable frequency domain techniques

Abstract

H , and structured singular value optimization techniques are used to design robust power system stabilizers (PSS) for a single-machine and a two-machine system with varying operating conditions. Realistic uncertainty models to represent the possible operating conditions as perturbations from a nominal operating condition are developed. System experience is used to select weighting functions to provide adequate damping and shape the controller frequency response. Computer simulations show that the PSS designed using the proposed technique provides improved damping compared to a conventional PSS.

Adaptive Control for Power System Stability Improvement

“…The stabilization of the synchronous generator has represented an attractive problem for testing different concepts of the modern control theory. The majority of the contributions have presented the application of adaptive control, robust control (Chow et al, 1990), variable structure control (Subbarao & Iyer, 1993), fuzzy control (Hassan & Malik, 1993), artificial neural network (Zhang et al, 1993), feedback linearization (Mielcszarski & Zajaczkowski, 1994), and internal model control (Law et al, 1994). The presented research has been focused to the study of adaptive stabilization methods.…”

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

“…In order to increase the damping of the power system response, classical controllers can be used which are usually designed for an operating point. If a phase lead transfer function is used in control mechanism, a conventional PSS is achieved [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Since the PSS is designed for one operational point, it has good performance only in the designed operating condition and it should be redesigned to achieve good performance in the other operational points.…”

“…Since in adaptive PSS, an identification mechanism is required to adapt the PSS parameters, the complexity of online controller computations will increase [3]. In contrast, in the robust PSS, a fixed controller for different operational points is designed [4][5][6][7][8][9][10][11][12][13][14][15] which makes it more convenient than adaptive PSS.…”

“…These nonlinear equations can be linearized around each operating point, such that small signal model of the power system can be determined. The Hefferon-Philips model is one of these power system linear models [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. The studies on linear system show that the system response has not enough damping ratio and it might be unstable in some operating points [1][2][3][4][5][6][7][8].…”

“…Therefore, the desired PSS should stabilize the power system in all operational points; ie, it should be robust against the changes in the operational conditions. Adaptive control [3] and robust control strategies [4][5][6][7][8][9][10][11][12][13][14][15] are two main methods for solving this problem in power system which have been led to adaptive PSS and robust PSS designs respectively. Since in adaptive PSS, an identification mechanism is required to adapt the PSS parameters, the complexity of online controller computations will increase [3].…”