Parallel computation of transient stability using symplectic Gauss method and GPU

Abstract

This study presents a new parallel algorithm for power system transient stability computation based on symplectic Gauss method. The s-stage 2s-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.