• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.941-944
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• 1997

In this paper, new algorithm is proposed to transform the heuristically approximated eigenvalue calculation procedure of the AESOPS algorithm to the Newton Rahpson method. The new algorithm is directly calculated from the original eigenvalue calculation of the AESOPS and thus a large number of the same data of the AESOPS algorithm can be used efficiently in this method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1394-1400
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• 1999

This paper presents and efficient improvement of the iterative eigenvalue calculation method and the selection of initial values in AESOPS algorithm. To determine the initial eigenvalues of the system, system state matrix is constructed with the two-axis generator model. From the submatrices including synchronous and damping coefficients, the initial eigenvalues are calculated by the QR method. Participation factors are also calculated from the above submatrices in order to determine the generators which have a important effect to the specific oscillation mode. Also, the heuristically approximated eigenvalue calculation method in the AESOPS algorithm is transformed to the Newton Raphson Method which is largely used in the nonlinear numerical analysis. The new methods are developed from the AESOPS algorithm and thus only a few calculation steps are added to practice the proposed algorithm.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.259-262
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• 1998

This paper presents a new eigenvalue calculation methods in AESOPS algorithm. The source program of the AESOPS algorithm is modified to practice in PC environment. Window95 is used as an operating system of PC and MicroSoft Power Station is used to compile the fortran source program. The heuristically approximated eigenvalue calculation method of the AESOPS algorithm is transformed to the Newton Raphson Method which is largely used in the nonlinear numerical analysis. The new methods are developed from the AESOPS algorithm and thus only a few calculation steps are added to practice the proposed algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.3
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• pp.127-133
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• 2002

This paper presents an efficient improvement of the iterative eigenvalue calculation method of the AESOPS algorithm. The intuitively and heuristically approximated iterative eigenvalue calculation method of the AESOPS algorithm is transformed to the Second Order Newton Raphson Method which is generally used in numerical analysis. The equations of second order partial differentiation of external torque, terminal and internal voltages are derived from the original AESOPS algorithm. Therefore only a few calculation steps are added to transform the intuitively and heuristically approximated AESOPS algorithm to the Second Order Newton Raphson Method, while the merits of original algorithm are still preserved.

• 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.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.76-78
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• 1993

This paper describes an efficient method of computing any desired number of the most unstable eigenvalues and eigenvectors of a large scale multi-machine power system. Approximate eigenvalues obtained by Hessenberg process are refined using Rayleigh quotient iteration with cubic convergence property. If further eigenvalues and eigenvectors are needed, the procedure described above are repeated with deflation. The proposed algorithm can cover all the model types of synchronous machines, exciters, speed governing system and PSS defined in AESOPS. The proposed algorithm applied to New England test system with 10 machines and 39 buses produced the results same with AESOPS in faster computation time. Also eigenvectors computed in Rayleigh quotient iteration makes it possible to make eigen-analysis for improving unstable modes.