Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems

11 June 2022

Papers citing "Grid-SiPhyR: An end-to-end learning to optimize framework for combinatorial problems in power systems"

4 / 4 papers shown

Title
Physics-Informed Graph Neural Network for Dynamic Reconfiguration of Power Systems Jules Authier R. Haider Anuradha M. Annaswamy Florian Dorfler AI4CE PINN 17 4 0 01 Oct 2023
Topology-aware Graph Neural Networks for Learning Feasible and Adaptive ac-OPF Solutions Shaohui Liu Chengyang Wu Hao Zhu 32 47 0 16 May 2022
Solving Mixed Integer Programs Using Neural Networks Vinod Nair Sergey Bartunov Felix Gimeno Ingrid von Glehn Pawel Lichocki ... Pushmeet Kohli Ira Ktena Yujia Li Oriol Vinyals Yori Zwols 119 244 0 23 Dec 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