基于GPU的机电暂态仿真细粒度并行算法

摘要

提出一种基于图形处理器（GPU）并采用隐形梯度法的机电暂态仿真细粒度并行算法。该算法将整个系统分为发电机节点系统和非发电机节点系统,对发电机节点系统求解时,先将在网络中直接相连的发电机节点合并成一个子系统,然后在GPU中给每个子系统分配相应线程块进行并行求解,其中采用了LU并行分解来求解线性方程组。求解完成后,利用从发电机节点系统传递来的LU分解信息,再对非发电机节点系统使用GPU进行求解。通过对不同规模的算例进行分析表明：所提出的GPU并行算法的计算结果与CPU串行算法和BPA软件的计算结果大致相同,且随着系统规模的增加,GPU并行算法的加速效果更为明显。%A fine granularity parallel algorithm for electromechanical transient stability simulation is proposed based on the graphic processing unit（GPU） and implicit gradient method.The whole power system is divided into the generator system and non-generator system.When solving the generator system buses,first each subsystem composed of connected generator buses is allocated an independent GPU block and uses LU decomposition to solve the linear functions.Then the non-generator system is simulated on another GPU block,supported by LU messages from the generator system.Numerical results show that the accuracy of the parallel algorithm proposed is roughly the same as that of the CPU serial method and BPA software.Moreover,with an increase of the power system scale,the speedup effect is more obvious.