PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow

The paper introduces PGLearn, a comprehensive suite of standardized datasets and evaluation tools designed to facilitate research in machine learning applications for Optimal Power Flow (OPF) problems, addressing current challenges of data scarcity and inconsistent benchmarking. By providing realistic, diverse datasets and a robust benchmarking toolkit, PGLearn aims to democratize access, promote fair comparison, and accelerate innovation in ML-driven energy grid optimization.