Physics-Informed Neural Networks for Power Systems

9 November 2019

George S. Misyris

Andreas Venzke

Spyros Chatzivasileiadis

PINN

AI4CE

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Papers citing "Physics-Informed Neural Networks for Power Systems"

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Title
Enhanced physics-informed neural networks (PINNs) for high-order power grid dynamics Vineet Jagadeesan Nair PINN 43 0 0 10 Oct 2024
A Survey on Solving and Discovering Differential Equations Using Deep Neural Networks Hyeonjung Jung Jung Jayant Gupta B. Jayaprakash Matthew J. Eagon Harish Selvam Carl Molnar W. Northrop Shashi Shekhar AI4CE 35 5 0 26 Apr 2023
Physics-Informed Neural Networks for Time-Domain Simulations: Accuracy, Computational Cost, and Flexibility Jochen Stiasny Spyros Chatzivasileiadis PINN AI4CE 38 9 0 15 Mar 2023
On Approximating the Dynamic Response of Synchronous Generators via Operator Learning: A Step Towards Building Deep Operator-based Power Grid Simulators Christian Moya Guang Lin Tianqiao Zhao Meng Yue 32 8 0 29 Jan 2023
Minimizing Worst-Case Violations of Neural Networks Rahul Nellikkath Spyros Chatzivasileiadis 38 3 0 21 Dec 2022
Machine Learning for Smart and Energy-Efficient Buildings Hari Prasanna Das Yu-Wen Lin Utkarsha Agwan Lucas Spangher Alex Devonport Yu Yang Ján Drgoňa A. Chong S. Schiavon C. Spanos HAI AI4CE 34 19 0 27 Nov 2022
Ranking-Based Physics-Informed Line Failure Detection in Power Grids Aleksandra Burashnikova Wenting Li Massih-Reza Amini Deepjoyti Deka Yury Maximov AI4CE 11 0 0 31 Aug 2022
Thermodynamics of learning physical phenomena Elías Cueto Francisco Chinesta AI4CE 25 22 0 26 Jul 2022
Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs) J. Abbasi Paal Ostebo Andersen PINN AI4CE 25 14 0 29 May 2022
A comparison of PINN approaches for drift-diffusion equations on metric graphs J. Blechschmidt Jan-Frederik Pietschman Tom-Christian Riemer Martin Stoll M. Winkler 18 2 0 15 May 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 26 1,180 0 14 Jan 2022
Physics informed neural networks for continuum micromechanics Alexander Henkes Henning Wessels R. Mahnken PINN AI4CE 16 139 0 14 Oct 2021
Physics-Informed Neural Networks for AC Optimal Power Flow Rahul Nellikkath Spyros Chatzivasileiadis PINN 31 88 0 06 Oct 2021
DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks Christian Moya Guang Lin AI4CE PINN 59 37 0 09 Sep 2021
Predicting Basin Stability of Power Grids using Graph Neural Networks Christian Nauck M. Lindner Konstantin Schurholt Haoming Zhang P. Schultz Jürgen Kurths I. Isenhardt Frank Hellmann 21 22 0 18 Aug 2021
Physics-Informed Neural Networks for Minimising Worst-Case Violations in DC Optimal Power Flow Rahul Nellikkath Spyros Chatzivasileiadis PINN 11 32 0 28 Jun 2021
Transient Stability Analysis with Physics-Informed Neural Networks Jochen Stiasny Georgios S. Misyris Spyros Chatzivasileiadis PINN 21 13 0 25 Jun 2021
Which Neural Network to Choose for Post-Fault Localization, Dynamic State Estimation and Optimal Measurement Placement in Power Systems? A. Afonin Michael Chertkov 17 3 0 07 Apr 2021
Physics-Informed Graphical Neural Network for Parameter & State Estimations in Power Systems Laurent Pagnier Michael Chertkov 42 49 0 12 Feb 2021
Stochastic analysis of heterogeneous porous material with modified neural architecture search (NAS) based physics-informed neural networks using transfer learning Hongwei Guo X. Zhuang Timon Rabczuk 20 82 0 03 Oct 2020
Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods Ferdinando Fioretto Terrence W.K. Mak Pascal Van Hentenryck AI4CE 81 199 0 19 Sep 2019