Parallel multi-GPU implementation of fast decoupled power flow solver with hybrid architecture.

Abstract-Achieving high solution efficiency on conventional sequential computation architecture is a challenging task due to penetration of multiple renewable energy sources (RESs). This challenge has become the bottleneck for the application in real-time grid operation, grid planning and analysis of the large-scale and complicated modern power system. Therefore, this paper proposes a parallel multi-GPU and multi-process Fast Decoupled (FD) method to accelerate the power flow calculation, reducing the system responsive time and guaranteeing real-time performance on a large-scale modern power system. In this paper, two hierarchy architecture, task parallelism and data parallelism, are designed to optimize the FD solver parallelization. Moreover, the GPUDirect technology is employed to enhance efficiency of data transmission and drastically reduce copy overhead. The proposed method in this paper achieves a speedup of 9 × ∼ 33 × , compared to the single GPU on a sample large-scale power system. [ABSTRACT FROM AUTHOR]