ML-OPF-Bench: Benchmarking Machine Learning for Optimal Power Flow

arXiv:2610.04307 · eess.SY, cs.LG, cs.SY · Submitted 2026-10-03 · Read on arXiv

eess.SY, cs.LG, cs.SY

Submitted: 2026-10-03

Updated: 2026-10-03

Code: https://github.com/XinyiLiu04/ML-OPF-Bench

Terminology

• Benchmarking — 1× in this paper · explained in 3 episodes

Sources

• The Power Grid Library for Benchmarking AC Optimal Power Flow Algorithms
• Revisiting Deep AC-OPF
• Deep Learning Scaling is Predictable, Empirically
• Training Compute-Optimal Large Language Models
• Scaling Laws for Neural Language Models
• Adam: A Method for Stochastic Optimization
• Coordinated Expansion Planning of Transmission and Distribution Systems Integrated with Smart Grid Technologies
• Physics-Informed Neural Networks for AC Optimal Power Flow
• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• fev-bench: A Realistic Benchmark for Time Series Forecasting
• ProOPF: Benchmarking and Improving LLMs for Professional-Grade Power Systems Optimization Modeling
• Can LLMs Correct Themselves? A Benchmark of Self-Correction in LLMs
• Learning the Optimal Power Flow: Environment Design Matters

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