Computing rightmost eigenvalues for small-signal stability assessment of large scale power systems

Knowledge of the rightmost eigenvalues of system matrices is essential in power system small-signal stability analysis. Accurate and efficient computation of the rightmost eigenvalues, however, is a challenge, especially for large-scale descriptor systems. In this paper we present an algorithm, based on Subspace Accelerated Rayleigh Quotient Iteration (SARQI), for the automatic computation of the rightmost eigenvalues of large-scale (descriptor) system matrices. The effectiveness and robustness of the algorithm is illustrated by numerical experiments with realistic power system models, and we also show how SARQI can be used to compute eigenvalues closest to any damping ratio and repeated eigenvalues. The algorithm can be used for stability analysis in any other field of engineering.