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Post-Fault Power Grid Voltage Prediction via 1D-CNN with Spatial Coupling

https://doi.org/10.1109/AI4I54798.2022.00016

Hu, Carson ; Lin, Guang ; Wang, Bao ; Yue, Meng ; Xin, Jack ( September 2022 , International Conference on Artificial Intelligence for Industries)

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Glassoformer: a query-sparse transformer for post-fault power grid voltage prediction

https://doi.org/10.1109/ICASSP43922.2022.9747394

Zheng, Yunling ; Hu, Carson ; Lin, Guang ; Yue, Meng ; Wang, Bao ; Xin, Jack. ( January 2022 , IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP))

We propose GLassoformer, a novel and efficient transformer architecture leveraging group Lasso regularization to reduce the number of queries of the standard self-attention mechanism. Due to the sparsified queries, GLassoformer is more computationally efficient than the standard transformers. On the power grid post-fault voltage prediction task, GLassoformer shows remarkably better prediction than many existing benchmark algorithms in terms of accuracy and stability.
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