Physics-Informed Neural Networks for AC Optimal Power Flow

6 October 2021

Papers citing "Physics-Informed Neural Networks for AC Optimal Power Flow"

35 / 35 papers shown

Title
Towards graph neural networks for provably solving convex optimization problems Chendi Qian Christopher Morris 52 0 0 04 Feb 2025
Optimal Sensor Placement in Power Transformers Using Physics-Informed Neural Networks Sirui Li Federica Bragone Matthieu Barreau Tor Laneryd Kateryna Morozovska 48 0 0 01 Feb 2025
Physics-Informed GNN for non-linear constrained optimization: PINCO a solver for the AC-optimal power flow Anna Varbella Damien Briens B. Gjorgiev Giuseppe Alessio DÍnverno G. Sansavini 18 0 0 07 Oct 2024
Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed Neural Networks Tianchi Yu Jingwei Qiu Jiang Yang Ivan V. Oseledets 29 2 0 05 Oct 2024
Adaptive Training of Grid-Dependent Physics-Informed Kolmogorov-Arnold Networks Spyros Rigas M. Papachristou Theofilos Papadopoulos Fotios Anagnostopoulos Georgios Alexandridis AI4CE 34 21 0 24 Jul 2024
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models Shivvrat Arya Tahrima Rahman Vibhav Gogate TPM 39 2 0 17 Apr 2024
Advanced Intelligent Optimization Algorithms for Multi-Objective Optimal Power Flow in Future Power Systems: A Review Yuyan Li 24 1 0 14 Apr 2024
Correctness Verification of Neural Networks Approximating Differential Equations Petros Ellinas Rahul Nellikkath Ignasi Ventura Jochen Stiasny Spyros Chatzivasileiadis 37 1 0 12 Feb 2024
A Hybrid Approach of Transfer Learning and Physics-Informed Modeling: Improving Dissolved Oxygen Concentration Prediction in an Industrial Wastewater Treatment Plant Ece S. Koksal Erdal Aydin PINN AI4CE 28 0 0 20 Jan 2024
Power Flow Analysis Using Deep Neural Networks in Three-Phase Unbalanced Smart Distribution Grids Deepak Tiwari Mehdi Jabbari Zideh Veeru Talreja Vishal Verma S. K. Solanki J. Solanki 36 9 0 15 Jan 2024
QCQP-Net: Reliably Learning Feasible Alternating Current Optimal Power Flow Solutions Under Constraints Sihan Zeng Youngdae Kim Yuxuan Ren Kibaek Kim 41 2 0 11 Jan 2024
PINNs-Based Uncertainty Quantification for Transient Stability Analysis Ren Wang Ming Zhong Kaidi Xu Lola Giráldez Sánchez-Cortés Ignacio de Cominges Guerra 37 1 0 21 Nov 2023
Dual Conic Proxies for AC Optimal Power Flow Guancheng Qiu Mathieu Tanneau Pascal Van Hentenryck 37 8 0 04 Oct 2023
Equitable Time-Varying Pricing Tariff Design: A Joint Learning and Optimization Approach Liudong Chen Bolun Xu 18 0 0 26 Jul 2023
GPU-Accelerated Verification of Machine Learning Models for Power Systems Samuel C. Chevalier Ilgiz Murzakhanov Spyros Chatzivasileiadis 24 4 0 18 Jun 2023
AI Driven Near Real-time Locational Marginal Pricing Method: A Feasibility and Robustness Study Naga Venkata Sai Jitin Jami J. Kardoš Olaf Schenk Harald Kostler 13 0 0 16 Jun 2023
Self-supervised Equality Embedded Deep Lagrange Dual for Approximate Constrained Optimization Minsoo Kim Hongseok Kim 24 4 0 11 Jun 2023
Physics-Guided Graph Neural Networks for Real-time AC/DC Power Flow Analysis Meiying Yang Gao Qiu Yonghuang Wu Junyong Liu Nina Dai Yue Shui Kai Liu Lijie Ding AI4CE 14 1 0 29 Apr 2023
End-to-End Feasible Optimization Proxies for Large-Scale Economic Dispatch Wenbo Chen Mathieu Tanneau Pascal Van Hentenryck 26 29 0 23 Apr 2023
A Physics-Informed Machine Learning for Electricity Markets: A NYISO Case Study Robert Ferrando Laurent Pagnier R. Mieth Zhirui Liang Y. Dvorkin D. Bienstock Michael Chertkov 26 7 0 31 Mar 2023
Enriching Neural Network Training Dataset to Improve Worst-Case Performance Guarantees Rahul Nellikkath Spyros Chatzivasileiadis 36 3 0 23 Mar 2023
Physics Informed Piecewise Linear Neural Networks for Process Optimization Ece S. Koksal E. Aydın PINN 22 11 0 02 Feb 2023
Compact Optimization Learning for AC Optimal Power Flow Seonho Park Wenbo Chen Terrence W.K. Mak Pascal Van Hentenryck 27 17 0 21 Jan 2023
Optimal Power Flow Based on Physical-Model-Integrated Neural Network with Worth-Learning Data Generation Zuntao Hu Hongcai Zhang AI4CE 27 6 0 10 Jan 2023
Minimizing Worst-Case Violations of Neural Networks Rahul Nellikkath Spyros Chatzivasileiadis 38 3 0 21 Dec 2022
Global Performance Guarantees for Neural Network Models of AC Power Flow Samuel C. Chevalier Spyros Chatzivasileiadis 10 6 0 14 Nov 2022
Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems R. Haider Anuradha M. Annaswamy 31 2 0 11 Jun 2022
Model-Informed Generative Adversarial Network (MI-GAN) for Learning Optimal Power Flow Yuxuan Li Chaoyue Zhao Chenang Liu 20 4 0 04 Jun 2022
Learning-based AC-OPF Solvers on Realistic Network and Realistic Loads Tsun Ho Aaron Cheung Mingliang Zhou Ming Chen 32 1 0 19 May 2022
Topology-aware Graph Neural Networks for Learning Feasible and Adaptive ac-OPF Solutions Shaohui Liu Chengyang Wu Hao Zhu 35 47 0 16 May 2022
Closing the Loop: A Framework for Trustworthy Machine Learning in Power Systems Jochen Stiasny Samuel C. Chevalier Rahul Nellikkath Brynjar Sævarsson Spyros Chatzivasileiadis 29 14 0 14 Mar 2022
Ensuring DNN Solution Feasibility for Optimization Problems with Convex Constraints and Its Application to DC Optimal Power Flow Problems Tianyu Zhao Xiang Pan Minghua Chen S. Low 17 10 0 15 Dec 2021
Risk-Aware Learning for Scalable Voltage Optimization in Distribution Grids Shanny Lin Shaohui Liu Hao Zhu 20 9 0 04 Oct 2021
IRMAC: Interpretable Refined Motifs in Binary Classification for Smart Grid Applications Rui Yuan S. A. Pourmousavi W. Soong Giang Nguyen Jon A. R. Liisberg 11 7 0 23 Sep 2021
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