Application of sparse eigenvalue techniques to the small signal stability analysis of large power systems

Journal Article · Tue May 01 04:00:00 EDT 1990 · IEEE Transactions on Power Systems (Institute of Electrical and Electronics Engineers); (USA)

DOI:https://doi.org/10.1109/59.54575· OSTI ID:6978183

Wang, L; Semlyen, A ^[1]

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1. Toronto Univ., ON (Canada). Dept. of Electrical Engineering

This paper presents two sparsity-based eigenvalue techniques---simultaneous iterations and the modified Arnoldi method---and their application to the small signal stability analysis of large power systems. Simultaneous iterations and the modified Arnoldi method are two recently developed methods for large, sparse unsymmetrical eigenvalue problems, and have been reported as very efficient in computing the partial eigensolution of several types of matrices, such as stochastic ones. This paper shows that they can also be applied successfully to the matrices derived for small signal stability studies of power systems. An algorithm utilizing these two methods is proposed for calculating the eigenvalues around a fixed point which can be placed at will in various parts of the complex plane. The sparsity is fully preserved in the algorithm by using the augmented system state equations as the linearized power system small signal model and performing the corresponding sparsity-oriented calculations. Several applications of the algorithm are discussed and illustrated by numerical examples.

• OSTI ID: 6978183
• Journal Information: IEEE Transactions on Power Systems (Institute of Electrical and Electronics Engineers); (USA), Journal Name: IEEE Transactions on Power Systems (Institute of Electrical and Electronics Engineers); (USA) Vol. 5:2; ISSN ITPSE; ISSN 0885-8950
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
240100* -- Power Systems-- (1990-)
99 GENERAL AND MISCELLANEOUS
990200 -- Mathematics & Computers
ALGORITHMS
EIGENVALUES
ENERGY SYSTEMS
ITERATIVE METHODS
MATHEMATICAL LOGIC
MATRICES
POWER SYSTEMS
S MATRIX
STABILITY
STOCHASTIC PROCESSES