Abstract
An efficient parallel Krylov-Schur method is proposed for computing eigenvalues and eigenvectors related with oscillating modes of low damping for large-scale power systems. Improved restarting techniques are explained and demonstrated in details, which focus on a refined selection of kept subspace in contraction and a reliable mechanism of no missing target eigenvalues. Cayley and shift-invert transforms are used to decouple the computation of eigen-analysis and enable the proposed parallelization with a master-slave scheme. Based on the improved restarting techniques, the strategy for adaptive allocation of shifts and the coordination of parallel computing tasks, the proposed method is capable of computing a large number of eigen-pairs with satisfactory accuracy, convergence rate and parallel acceleration. The computational efficiency is validated by three test cases from real-world large-scale power systems on a symmetric multi-processing (SMP) computer.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
