DAE-PINN: A Physics-Informed Neural Network Model for Simulating
Differential-Algebraic Equations with Application to Power Networks

DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks

9 September 2021

Papers citing "DAE-PINN: A Physics-Informed Neural Network Model for Simulating Differential-Algebraic Equations with Application to Power Networks"

13 / 13 papers shown

Title
Physics-informed Multiple-Input Operators for efficient dynamic response prediction of structures Bilal Ahmed Yuqing Qiu Diab W. Abueidda Waleed El-Sekelly Tarek Abdoun M. Mobasher AI4CE 39 0 0 11 May 2025
DAE-KAN: A Kolmogorov-Arnold Network Model for High-Index Differential-Algebraic Equations Kai Luo Juan Tang Mingchao Cai Xiaoqing Zeng Manqi Xie Ming Yan 31 0 0 22 Apr 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 77 1 0 15 Dec 2024
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes Peter Zaspel Michael Günther 39 2 0 26 Jun 2024
Quantum Neural Networks for Solving Power System Transient Simulation Problem Mohammadreza Soltaninia Junpeng Zhan 27 0 0 19 May 2024
Physical Information Neural Networks for Solving High-index Differential-algebraic Equation Systems Based on Radau Methods Jiasheng Chen Juan Tang Ming Yan Shuai Lai Kun Liang Jianguang Lu Wenqiang Yang AI4CE 29 0 0 19 Oct 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
NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training B.-L. Lu Christian Moya Guang Lin PINN 37 11 0 03 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
DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories Christian Moya Shiqi Zhang Meng Yue Guang Lin 22 42 0 15 Feb 2022
glassoformer: a query-sparse transformer for post-fault power grid voltage prediction Yunling Zheng Carson Hu Guang Lin Meng Yue Bao Wang Jack Xin 73 2 0 22 Jan 2022
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 44 494 0 09 Feb 2021
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting Haoyi Zhou Shanghang Zhang J. Peng Shuai Zhang Jianxin Li Hui Xiong Wan Zhang AI4TS 169 3,885 0 14 Dec 2020