88 citations · 199 across the 21 of their papers we have counts for
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eess.SY2021★ 10 cited
Towards Model Reduction for Power System Transients with Physics-Informed PDE
Laurent Pagnier, Michael Chertkov, Julian Fritzsch +1
This manuscript reports the first step towards building a robust and efficient model reduction methodology to capture transient dynamics in a transmission level electric power syst…
eess.SY2021★ 2 cited
Embedding Power Flow into Machine Learning for Parameter and State Estimation
Laurent Pagnier, Michael Chertkov
Modern state and parameter estimations in power systems consist of two stages: the outer problem of minimizing the mismatch between network observation and prediction over the netw…
cs.LG2021★ 1 cited
Physics-Informed Graphical Neural Network for Parameter & State Estimations in Power Systems
Laurent Pagnier, Michael Chertkov
Parameter Estimation (PE) and State Estimation (SE) are the most wide-spread tasks in the system engineering. They need to be done automatically, fast and frequently, as measuremen…