A GPU-based Transient Stability Simulation using Runge-Kutta Integration Algorithm

Abstract

Graphics processing units (GPU) have been investigated to release the computational capability in various scientific applications. Recent research shows that prudential consideration needs to be given to take the advantages of GPUs while avoiding the deficiency. In this paper, the impact of GPU acceleration to implicit integrators and explicit integrators in transient stability is investigated. It is illustrated that implicit integrators, although more numerical stable than explicit ones, are not suitable for GPU acceleration. As a tradeoff between numerical stability and efficiency, an explicit 4th order Runge-Kutta integration algorithm is implemented for transient stability simulation based on hybrid CPU-GPU architecture. The differential equations of dynamic components are evaluated in GPU, while the linear network equations are solved in CPU using sparse direct solver. Simulation on IEEE 22-bus power system with 6 generators is reported to validate the feasibility of the proposed method.