Bayesian State Estimation for Unobservable Distribution Systems via Deep Learning
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DOI: 10.1109/tpwrs.2019.2919157
Abstract: The problem of state estimation for unobservable distribution systems is considered. A deep learning approach to Bayesian state estimation is proposed for real-time applications. The proposed technique consists of distribution learning of stochastic power injection,… read more here.
Keywords: state estimation; bayesian state; estimation; estimation unobservable ... See more keywords