To analyze large sets of grid states, e.g. when evaluating the impact from the uncertainties of the renewable generation with probabilistic Monte Carlo simulation or in stationary time series simulation, large number of power flow calculations have to be performed. For the application in real-time grid operation, grid planning and in further cases when computational time is critical, a novel approach on simultaneous parallelization of many Newton-Raphson power flow calculations on CPU and with GPU-acceleration is proposed. The result shows a speed-up of over x100 comparing to the open-source tool pandapower, when performing repetitive power flows of system with admittance matrix of the same sparsity pattern on both CPU and GPU. The speed-up relies on the algorithm improvement and highly optimized parallelization strategy, which can reduce the repetitive work and saturate the high hardware computational capability of modern CPUs and GPUs well. This is achieved with the proposed batched sparse matrix operation and batched linear solver based on LU-refactorization. The batched linear solver shows a large performance improvement comparing to the state-of-the-art linear system solver KLU library and a better saturation of the GPU performance with small problem scale. Finally, the method of integrating the proposed solver into pandapower is presented, thus the parallel power flow solver with outstanding performance can be easily applied in challenging real-life grid operation and innovative researches e.g. data-driven machine learning studies.

翻译：为了分析大量的电网状态,例如,在评估具有概率性蒙特卡洛模拟或固定时间序列模拟的可再生能源的不确定性的影响时,必须进行大量的电流计算。对于实时电网操作、电网规划的应用,以及在计算时间十分关键的情况下的进一步情况下,提议采用新颖的办法,在CPU和GPU加速的情况下同时同时进行许多牛顿-拉斐逊电流计算。结果显示,与开放源工具pandower相比,在使用CPU和GPU的同一宽度模式的接收矩阵进行重复性电流时,系统电流计算的速度加快了x100以上。加速速度取决于对实时电网运行的改进和高度优化的平行化战略,这可以减少现代CPU和GPU的高硬件计算能力重复性和饱和。这可以通过拟议的分批稀释矩阵操作和分批线性线性求解能力来实现。分批线性线求解器显示,在与具有挑战性能的运行模式的Slodal Sloveal-lical Sol-lical Slicomlistal Prolistal Proligal Prolistal 和Slimallical-lical-lical-limallistral-listral-listal-listal-listal-ligal romodal-ligal 问题之间, 和Sligal-这是拟议的硬化的系统的系统的系统的系统的改进是更好的改进改进改进,因此将改进。