Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods

19 September 2019

Ferdinando Fioretto

Terrence W.K. Mak

Pascal Van Hentenryck

AI4CE

ArXiv PDF HTML

Papers citing "Predicting AC Optimal Power Flows: Combining Deep Learning and Lagrangian Dual Methods"

21 / 21 papers shown

Title
Generative Edge Detection with Stable Diffusion Caixia Zhou Yaping Huang Mochu Xiang Jiahui Ren Haibin Ling Jing Zhang 56 0 0 04 Oct 2024
Dual Interior Point Optimization Learning Michael Klamkin Mathieu Tanneau Pascal Van Hentenryck 23 2 0 04 Feb 2024
Approximating Solutions to the Knapsack Problem using the Lagrangian Dual Framework Mitchell Keegan Mahdi Abolghasemi 51 0 0 06 Dec 2023
Optimal Power Flow in Highly Renewable Power System Based on Attention Neural Networks Chen Li Alexander Kies Kai Zhou Markus Schlott O. Sayed Mariia Bilousova Horst Stoecker 19 4 0 23 Nov 2023
Predict-Then-Optimize by Proxy: Learning Joint Models of Prediction and Optimization James Kotary Vincenzo Di Vito Jacob K Christopher Pascal Van Hentenryck Ferdinando Fioretto 34 3 0 22 Nov 2023
Data-driven decision-focused surrogate modeling Rishabh Gupta Qi Zhang OffRL AI4CE 25 12 0 23 Aug 2023
Enriching Neural Network Training Dataset to Improve Worst-Case Performance Guarantees Rahul Nellikkath Spyros Chatzivasileiadis 36 3 0 23 Mar 2023
Compact Optimization Learning for AC Optimal Power Flow Seonho Park Wenbo Chen Terrence W.K. Mak Pascal Van Hentenryck 22 17 0 21 Jan 2023
Minimizing Worst-Case Violations of Neural Networks Rahul Nellikkath Spyros Chatzivasileiadis 38 3 0 21 Dec 2022
AutoML for Climate Change: A Call to Action Renbo Tu Nicholas Roberts Vishak Prasad Sibasis Nayak P. Jain Frederic Sala Ganesh Ramakrishnan Ameet Talwalkar W. Neiswanger Colin White 30 6 0 07 Oct 2022
Self-Supervised Primal-Dual Learning for Constrained Optimization Seonho Park Pascal Van Hentenryck 30 46 0 18 Aug 2022
Risk-Aware Control and Optimization for High-Renewable Power Grids Neil Barry Minas Chatzos Wenbo Chen Dahye Han Chao-Ming Huang ... Mathieu Tanneau Pascal Van Hentenryck Shangkun Wang Hanyu Zhang Haoruo Zhao 25 7 0 02 Apr 2022
Learning Optimization Proxies for Large-Scale Security-Constrained Economic Dispatch Wenbo Chen Seonho Park Mathieu Tanneau Pascal Van Hentenryck 19 42 0 27 Dec 2021
OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets Trager Joswig-Jones K. Baker Ahmed S. Zamzam 15 25 0 01 Nov 2021
Data-Driven Time Series Reconstruction for Modern Power Systems Research Minas Chatzos Mathieu Tanneau Pascal Van Hentenryck AI4TS 16 11 0 26 Oct 2021
A Review of Physics-based Machine Learning in Civil Engineering S. Vadyala S. N. Betgeri J. Matthews Elizabeth Matthews AI4CE 25 152 0 09 Oct 2021
Physics-Informed Neural Networks for AC Optimal Power Flow Rahul Nellikkath Spyros Chatzivasileiadis PINN 26 87 0 06 Oct 2021
Leveraging power grid topology in machine learning assisted optimal power flow Thomas Falconer Letif Mones 9 46 0 01 Oct 2021
Physics-Informed Neural Networks for Minimising Worst-Case Violations in DC Optimal Power Flow Rahul Nellikkath Spyros Chatzivasileiadis PINN 9 32 0 28 Jun 2021
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression Zhaozhi Qian W. Zame L. Fleuren Paul Elbers M. Schaar OOD 19 53 0 05 Jun 2021
Neural Networks for Encoding Dynamic Security-Constrained Optimal Power Flow Daniel Timon Viola Andreas Venzke George S. Misyris Spyros Chatzivasileiadis 16 38 0 17 Mar 2020