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The absence of complete model data of a power system hinders complete eigenvalue analysis of that system. System identification methods have been used to identify operating-point-dependent equivalent linear model of a power system. Such identified models do not allow a complete eigenvalue analysis. To resolve this, the identification problem can be formulated in such a way to utilize any a-priori knowledge of the system. Model data of a synchronous machine consists of machine data and controller parameters. Methods to determine synchronous machine parameters are well established. In this paper, knowledge of the machine data and knowledge of eigenvalues of the system at multiple distinct operating points, extracted by a system identification method, are used to determine auxiliary controller parameters of the synchronous machine. Model data that are determined by the proposed method is independent of the operating point. Therefore, it can be easily integrated into a complete small signal stability study at any operating point of the synchronous machine. [ABSTRACT FROM AUTHOR]

This paper presents a design of a power system damping controller using partial right eigenstructure assignment. The eigenstructure assignment technique selects a set of closed-loop eigenvalues along with their right or left eigenvectors. The selection of eigenvectors offers extra flexibility which is exploited in this paper by designing a robust damping controller which provides the required damping under multiple operating conditions. A multi-input controller is used to increase the degrees of freedom available for the design. Remote measurements available from synchronised phasor measurements are also considered. The problem is formulated as a multi-objective nonlinear optimization problem and solved using the nonlinear simplex function in MATLAB. The proposed technique is used to design a robust power system stabilizer for the interconnected New England New York simplified power system model. Four contingencies are selected as additional operating conditions. The designed controller is validated using a nonlinear simulation. [ABSTRACT FROM AUTHOR]