Gaussian Process Learning-based Probabilistic Optimal Power Flow

The proposed GP-POPF method does not rely on uncertainty information and linearization assumptions on the power flow. Compared to data-based methods, the proposed method does not require extensive training samples of POPF solutions, thus reducing computation time.

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Parikshit Pareek, Hung D. Nguyen (2024). Dataset: Gaussian Process Learning-based Probabilistic Optimal Power Flow. https://doi.org/10.57702/004r5xsk

DOI retrieved: December 2, 2024

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Created December 2, 2024
Last update December 2, 2024
Author Parikshit Pareek
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Hung D. Nguyen