Improving The Convergence Rate Of Parareal-In-Time Power System Simulation Using The Krylov Subspace
Keywords
High-performance-computing; Krylov subspace; Numerical method; Parareal-in-time; Power system simulation
Abstract
The performance of parareal-in-time algorithms is determined on the number of sequential, coarse step iterations. A common tradeoff in designing an efficient parareal-in-time algorithm is between accuracy of the coarse solver and the number of iterations. Traditional parareal implementation for the power system simulation can also have difficulties handling complex power systems. In this paper, we propose a Krylov subspace enhanced parareal algorithm to reduce the number of coarse iterations. The proposed approach is demonstrated on a single-machine-infinite-bus system and the IEEE 10-machine 39-bus system. Noticeable decrease of number of iterations is observed in both cases.
Publication Date
12-21-2018
Publication Title
IEEE Power and Energy Society General Meeting
Volume
2018-August
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/PESGM.2018.8586354
Copyright Status
Unknown
Socpus ID
85060827270 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85060827270
STARS Citation
Duan, Nan; Simunovic, Srdjan; Dimitrovski, Aleksandar; and Sun, Kai, "Improving The Convergence Rate Of Parareal-In-Time Power System Simulation Using The Krylov Subspace" (2018). Scopus Export 2015-2019. 7606.
https://stars.library.ucf.edu/scopus2015/7606