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DOE OSTI · 1668501

Probabilistic Power Flow Based on a Gaussian Process Emulator

Xu, Yijun·Hu, Zhixiong·Mili, Lamine·Korkali, Mert·Chen, Xiao
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Abstract

In this letter, a novel Gaussian process emulator is proposed, for the first time, to conduct the probabilistic power-flow calculation. Based on Bayesian inference, a Gaussian process emulator is trained and served as a nonparametric, reduced-order model of the nonlinear power-flow model. This emulator has allowed us to evaluate the time-consuming power-flow solver at the sampled values with a negligible computational cost. The simulations reveal the excellent performance of this method.

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Xu, Yijun, Hu, Zhixiong, Mili, Lamine, Korkali, Mert, Chen, Xiao. 2020-04-01. Probabilistic Power Flow Based on a Gaussian Process Emulator. https://doi.org/10.1109/tpwrs.2020.2983603

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