• Corpus ID: 220265865

High-Fidelity Machine Learning Approximations of Large-Scale Optimal Power Flow

@article{Chatzos2020HighFidelityML,
  title={High-Fidelity Machine Learning Approximations of Large-Scale Optimal Power Flow},
  author={Minas Chatzos and Ferdinando Fioretto and Terrence W.K. Mak and Pascal Van Hentenryck},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.16356}
}
The AC Optimal Power Flow (AC-OPF) is a key building block in many power system applications. It determines generator setpoints at minimal cost that meet the power demands while satisfying the underlying physical and operational constraints. It is non-convex and NP-hard, and computationally challenging for large-scale power systems. Motivated by the increased stochasticity in generation schedules and increasing penetration of renewable sources, this paper explores a deep learning approach to… 

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