• Proceedings of the KIEE Conference
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• summer
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• pp.345-347
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• 2004

In small signal stability analysis of power systems, eigenvalue analysis is the most useful method and the detailed modeling of generator has an important effect to the eigenvalues. Generator full model is used for precise dynamic analysis of generators and controllers while two-axis model is used for multi-machine systems because of the reduced order of the state matrix. Also, the eigenvalue sensitivity coefficients are used for optimizing controller parameters to improve system stability. This paper compare the first and second order eigenvalue sensitivity coefficients of controllers using generator full model with those of two-axis model. As a result of an example, the estimated eigenvalues using the first and the second eigenvalue sensitivity coefficients using generator full model is very close to those of state matrix. Also the error ratios throughout a wide range of controller parameters is less than $1\%$.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.119-121
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• 2003

In small signal stability analysis of power systems, eigenvalue analysis is the most useful method and the detailed modeling of generator gives an important effect to the eigenvalues. Generator full model is used for precise dynamic analysis of generators and controllers while two-axis model is used for multimachine systems because of the reduced order of the state matrix. Also, the eigenvalue sensitivity coefficients are used for optimization of controller parameters to improve system stability. This paper compare the first order eigenvalue sensitivity coefficients of controllers in case of generator full model with those of two-axis model. As a result of an example the estimated eigenvalues using sensitivity coefficients in case of generator full model is very close to those of state matrix within 1% error ratios.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.217-219
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• 2001

This paper presents a new eigenvalue sensitivity analysis method based on AESOPS algorithm. The additional calculation steps are derived from the original AESOPS algorithm. The additional calculation steps are performed directly from the AESOPS algorithm after iteratively calculating electro-mechanical oscillation modes in small signal stability problems. Owing to the structural characteristics of partitioned sub-matrix of state space equations, the partial differentiation terms of system state matrix for obtaining eigenvalue sensitivity indices can be calculated very simply. By the method presented in this paper, the AESOPS algorithm can be used in controller design problem as well as analysis of small signal stability problem.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.11
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• pp.577-584
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• 2002

This paper presents a novel approach based on eigenvalue perturbation of augmented matrix(AMEP) to estimate the eigenvalue for variation of controller parameter. AMEP is a useful tool in the analysis and design of large scale power systems containing many different types of exciters, governors and stabilizers. Also, it can be used to find possible sources of instability and to determine the most sensitivity parameters for low frequency oscillation modes. This paper describes the application results of AMEP algorithm with respect to all controller parameter of KEPCO systems. Simulation results for interarea and local mode show that the proposed AMEP algorithm can be used for turning controller parameter, and verifying system data and linear model.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.17-19
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• 2001

In this paper, eigenvalue perturbation theory and its applications for the augmented system matrix are described. This theory is quite useful in the cases where any change in a system parameter results in signifiant changes to most of the elements of the augmented matrix or where the forming of sensitivity matrix so complicate. And AMEP(augmented matrix eigenvalue perturbation) for the excitation system parameters are computed for analysis of small signal stability of KEPCO 215-machine 791-bus system.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.54-56
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• 1993

A systematic procedure for determining the elements of system state matrix is suggested. The interrelation of submatrices of the system matrix is investigated. Each element or each block can be represented in algebraic form. These results can be applied in the eigenvalue sensitivity analysis with respect to the changes in controller parameters.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.372-380
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• 1994

A systematic procedure for the elements of system state matrix in multimachine systems with loads and eigenvalue technique which utilize stage matrix have widespread application in the analysis of small signal stability. Synchronous machines are represented by either a two-axis model or classical model. The interrelationship of submatrices of system matrix is investigated. Once elements of one submatrix are determined, they can be used to calculate the elements of the other submatrix. The approach is useful in the eigenvalue sensitivity analysis for various initial conditions and for the adjustment of generator controller parameters. It is illustrated for a three-machine and nine-bus multimachine system(WSCC system) with constant impedance loads.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.623-630
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• 2003

Recently, Tanaka(1988) derived two influence functions related to an eigenvalue problem $(A-\lambda_sI)\upsilon_s=0$ of real symmetric matrix A and used them for sensitivity analysis in principal component analysis. In this paper, we deal with the perturbation expansions up to quadratic terms of the same functions and discuss the application to sensitivity analysis in principal component regression analysis(PCRA). Numerical example is given to show how the approximation improves with the quadratic term.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.157-160
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• 1992

An approximate method for the dominant eigenvalue of one machine connected to the infinite bus has been suggested. This method is based on combining the traditional eigenvalue sensitivity analysis and the structure of the system state matrix. Numerical examples are presented. This method is considered to be quite useful in the stability analysis for various initial conditions and for adjustment of generator controller parameters.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.749-753
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• 1996

This paper presents a new method for first and second order eigen-sensitivity analysis of system matrix in augmented form. Eigen-sensitivity analysis provides invaluable informations in power system planning and operation. However, conventional eigen-sensitivity analysis methods, which need all the eigenvalues and eigenvectors, can not be applicable to large scale power systems due to large computer memory and computing time required. In the proposed method, all sensitivity computations for a mode are carried out using the augmented system matrix and its own eigenvalue and right & left eigenvectors. In other words sensitivity analysis for a mode does not need informations on the other eigenvalues and eigenvectors and sparsity technique can be fully utilized. Thus compuations can be done very efficiently with moderate computer memory and computing time even for large power systems. The proposed algorithm is tested for one machine infinite bus system.