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：本文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）的方法。我们重点探讨了性能瓶颈，并详细阐述了加速线性求解器（ACOPF中主导计算时间的核心组件）的优化工作。通过对两个大规模系统——合成美国东北电网（25,000个节点）与东部电网（70,000个节点）[1]——在GPU上进行ACOPF分析，结果显示相较于采用最先进求解器的中央处理器（CPU）分析，实现了显著的加速效果。据我们所知，这是首次证明在GPU上实现稀疏ACOPF显著加速的研究成果。