We present a solution of sparse alternating current optimal power flow (ACOPF) analysis on graphical processing unit (GPU). In particular, we discuss the performance bottlenecks and detail our efforts to accelerate the linear solver, a core component of ACOPF that dominates the computational time. ACOPF analyses of two large-scale systems, synthetic Northeast (25,000 buses) and Eastern (70,000 buses) U.S. grids [1], on GPU show promising speed-up compared to analyses on central processing unit (CPU) using a state-of-the-art solver. To our knowledge, this is the first result demonstrating a significant acceleration of sparse ACOPF on GPUs.

翻译：我们提出了一种在图形处理单元（GPU）上求解稀疏交流最优潮流（ACOPF）分析的方法。具体而言，我们讨论了性能瓶颈，并详细介绍了为加速线性求解器（主导计算时间的ACOPF核心组件）所做出的努力。在GPU上对两个大规模系统——合成美国东北部电网（25,000节点）和东部电网（70,000节点）[1]——进行的ACOPF分析表明，与使用最先进求解器在中央处理单元（CPU）上进行的分析相比，其加速效果显著。据我们所知，这是首个展示在GPU上显著加速稀疏ACOPF的研究成果。