Solving the AC optimal power flow problem (AC-OPF) is critical to the efficient and safe planning and operation of power grids. Small efficiency improvements in this domain have the potential to lead to billions of dollars of cost savings, and significant reductions in emissions from fossil fuel generators. Recent work on data-driven solution methods for AC-OPF shows the potential for large speed improvements compared to traditional solvers; however, no large-scale open datasets for this problem exist. We present the largest readily-available collection of solved AC-OPF problems to date. This collection is orders of magnitude larger than existing readily-available datasets, allowing training of high-capacity data-driven models. Uniquely, it includes topological perturbations - a critical requirement for usage in realistic power grid operations. We hope this resource will spur the community to scale research to larger grid sizes with variable topology.

翻译：交流最优潮流问题的求解对于电网的高效安全规划与运行至关重要。该领域微小的效率提升可能带来数十亿美元的成本节约，并显著降低化石燃料发电机的排放。近期针对交流最优潮流的数据驱动求解方法研究显示，相较于传统求解器可能实现大幅速度提升；然而，目前尚无该问题的大规模开源数据集。我们提出了迄今为止规模最大、易于获取的已求解交流最优潮流问题集合。该集合的规模比现有易获取数据集大数个数量级，能够支持高容量数据驱动模型的训练。其独特之处在于包含了拓扑扰动——这是实际电网运行场景中使用的关键需求。我们希望这一资源将推动学界开展可变拓扑结构下更大规模电网的研究。