GPU-Accelerated Batch Electromechanical Transient Simulation of Power System

State-of-the-art Graphics Processing Unit (GPU) has superior performances on float-pointing calculation and memory bandwidth, and therefore has great potential in many computationally intensive power system applications, one of which is batch-Electromechanical transient time simulation (ETTS) of power system. The computation speeds of the traditional method is slow. When dealing with batch simulation in multiple scenarios, the power consumption of multi-machine cluster system is large and the acceleration effect is limited by the number of processors. This paper proposes a superior GPU-Accelerated algorithm for batch-ETTS based on the implicit integration alternating solution method (IIASM), which extracts data-level fine-grained parallelism and increases the efficiency of memory access by combed design in solving batch dynamic element injection current and batch sparse linear systems (SLS). By offloading the tremendous computational burden to GPU, the algorithm of this paper can limit the time in one alternate iteration of single ETTS within 0.5 ms for one system with over 10,000 nodes.