Open AccessParallel computation of transient stability using symplectic Gauss method and GPU
Author(s) -
Liao Xiaobing,
Wang Fangzong
Publication year - 2016
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2016.0033
Subject(s) - computer science , preconditioner , parallel computing , graphics processing unit , linear system , system of linear equations , generalized minimal residual method , gauss–seidel method , computational science , iterative method , algorithm , mathematics , mathematical analysis , geometry
This study presents a new parallel algorithm for power system transient stability computation based on symplectic Gauss method. The s ‐stage 2 s ‐order symplectic Gauss method is used to convert the differential‐algebraic system simultaneously at s time points into a set of non‐linear algebraic equations, and the algebraic system is then solved by Newton method. Based on the block matrix characteristics, the solution of the linear equations involved in Newton method's process can be divided into two parts: the first part is fully parallelisable in time, and the second part is solved by preconditioned GMRES method while an efficient preconditioner has been proposed based on the V ‐transformation. For test, the proposed algorithm is implemented on three programming models, the first is the traditional central processing unit (CPU) computing, the second is CPU‐single graphics processing unit (GPU) cooperative computing, and the last one is CPU‐multiple GPUs cooperative computing. The results show that, the proposed parallel algorithm is accurate, has good convergence, and has good scalability both in the problem size and in the number of used GPU.