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Found 4 papers, 1 papers with code
Physics-informed Graphical Neural Network for Power System State Estimation
State estimation is highly critical for accurately observing the dynamic behavior of the power grids and minimizing risks from cyber threats.
Geodesic-Former: a Geodesic-Guided Few-shot 3D Point Cloud Instance Segmenter
This paper introduces a new problem in 3D point cloud: few-shot instance segmentation.
Distributed Dynamic State Estimation for Microgrids
To resolve this problem, this paper proposes a dynamic state estimation scheme for microgrids using the state-space model derived from differential equations of power networks.
Distributed Dynamic State-Input Estimation for Power Networks of Microgrids and Active Distribution Systems with Unknown Inputs
This paper proposes a joint input and state dynamic estimation scheme for power networks in microgrids and active distribution systems with unknown inputs.
