首先,介绍了基于直流潮流模型的故障筛选算法;然后,基于GPU的软硬件架构特点,提出了在任务分配、PCIe总线数据交互、线程分配方式、内存访问模式4个方面GPU算法设计应遵循的通用准则;最后,对GPU加速的故障筛选算法进行了详细设计和优化,提出了一种匹配GPU编程架构的并行直流故障筛选算法。算例分析结果表明,所提算法计算9 241节点算例的绝对执行时间仅为188 ms,相对于6核心CPU算法取得了11倍加速;所提4个设计准则具有通用性,可被应用于其他电力系统算法的GPU加速。
The CS(Contingency Screening) algorithms based on the DC power-flow model are introduced,the general principles of algorithm design based on the hardware and software architectures of GPU are proposed in four aspects:task assignment,data exchange via PCIe bus,thread allocation strategy and memory access mode. A CS algorithm accelerated by GPU is elaborately designed and optimized,and a parallel DC CS algorithm matching GPU programming architecture is proposed. The case calculation for a 9241-bus system shows that,the absolute computing time of the proposed CS algorithm is only 188 ms,ll times faster than that of the CS algorithm based on a 6-core CPU. The proposed four design principles can be generally applied to the GPU acceleration for other power system algorithms.