OPF-Learn: An Open-Source Framework for Creating Representative AC
Optimal Power Flow Datasets

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OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets

1 November 2021

Trager Joswig-Jones

Ahmed S. Zamzam

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Papers citing "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets"

9 / 9 papers shown

Title
PGLearn -- An Open-Source Learning Toolkit for Optimal Power Flow Michael Klamkin Mathieu Tanneau Pascal Van Hentenryck 15 1 0 28 May 2025
NSW-EPNews: A News-Augmented Benchmark for Electricity Price Forecasting with LLMs Zhaoge Bi Linghan Huang Haolin Jin Qingwen Zeng Huaming Chen AI4TS 25 0 0 22 May 2025
Beyond the Neural Fog: Interpretable Learning for AC Optimal Power Flow S. Pineda Juan Pérez-Ruiz J. Morales AI4CE 113 0 0 28 Jan 2025
OPFData: Large-scale datasets for AC optimal power flow with topological perturbations Sean Lovett M. Zgubič Sofia Liguori Sephora Madjiheurem Hamish Tomlinson Sophie Elster Chris Apps Sims Witherspoon Luis Piloto AI4CE 60 9 0 11 Jun 2024
CANOS: A Fast and Scalable Neural AC-OPF Solver Robust To N-1 Perturbations Luis Piloto Sofia Liguori Sephora Madjiheurem M. Zgubič Sean Lovett Hamish Tomlinson Sophie Elster Chris Apps Sims Witherspoon 78 10 0 26 Mar 2024
Optimal Power Flow Based on Physical-Model-Integrated Neural Network with Worth-Learning Data Generation Zuntao Hu Hongcai Zhang AI4CE 56 7 0 10 Jan 2023
Gradient-Enhanced Physics-Informed Neural Networks for Power Systems Operational Support M. Mohammadian K. Baker Ferdinando Fioretto PINN AI4CE 93 23 0 21 Jun 2022
Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI Le Xie Xiangtian Zheng Yannan Sun Tong Huang Tony Bruton AI4CE 60 19 0 10 May 2022
Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems Jochen Stiasny Samuel C. Chevalier Rahul Nellikkath Brynjar Sævarsson Spyros Chatzivasileiadis 64 16 0 14 Mar 2022