Model-Informed Generative Adversarial Network (MI-GAN) for Learning Optimal Power Flow. (arXiv:2206.01864v1 [cs.LG])

The optimal power flow (OPF) problem, as a critical component of power system
operations, becomes increasingly difficult to solve due to the variability,
intermittency, and unpredictability of renewable energy brought to the power
system. Although traditional optimization techniques, such as stochastic and
robust optimization approaches, could be used to address the OPF problem in the
face of renewable energy uncertainty, their effectiveness in dealing with
large-scale problems remains limited. As a result, deep learning techniques,
such as neural networks, have …

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