Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
2006.00544
Cited By
Data-driven Optimal Power Flow: A Physics-Informed Machine Learning Approach
IEEE Transactions on Power Systems (IEEE Trans. Power Syst.), 2020
31 May 2020
Xingyu Lei
Zhifang Yang
Juan Yu
Junbo Zhao
Qian Gao
Hongxin Yu
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Data-driven Optimal Power Flow: A Physics-Informed Machine Learning Approach"
18 / 18 papers shown
Study Design and Demystification of Physics Informed Neural Networks for Power Flow Simulation
Milad Leyli-abadi
Antoine Marot
Jérôme Picault
AI4CE
125
0
0
23 Sep 2025
A Survey of Physics-Informed AI for Complex Urban Systems
En Xu
Huandong Wang
Yunke Zhang
Sibo Li
Yinzhou Tang
...
Yuming Lin
Yuan Yuan
Xiaochen Fan
Jingtao Ding
Yong Li
AI4CE
226
6
0
09 Jun 2025
Time and Frequency Domain-based Anomaly Detection in Smart Meter Data for Distribution Network Studies
Petar Labura
Tomislav Antic
Tomislav Capuder
221
1
0
25 Apr 2025
Robust Deep Reinforcement Learning for Inverter-based Volt-Var Control in Partially Observable Distribution Networks
Applied Energy (Appl. Energy), 2024
Qiong Liu
Ye Guo
Tong Xu
OffRL
257
4
0
13 Aug 2024
PowerGraph: A power grid benchmark dataset for graph neural networks
Anna Varbella
Kenza Amara
B. Gjorgiev
Mennatallah El-Assady
G. Sansavini
262
27
0
05 Feb 2024
Power Flow Analysis Using Deep Neural Networks in Three-Phase Unbalanced Smart Distribution Grids
IEEE Access (IEEE Access), 2024
Deepak Tiwari
Mehdi Jabbari Zideh
Veeru Talreja
Vishal Verma
S. K. Solanki
J. Solanki
264
20
0
15 Jan 2024
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
196
6
0
23 Nov 2023
Operational risk quantification of power grids using graph neural network surrogates of the DC OPF
Sustainable Energy, Grids and Networks (SEGAN), 2023
Yadong Zhang
Pranav M. Karve
Sankaran Mahadevan
AI4CE
133
2
0
07 Nov 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
204
10
0
31 Mar 2023
Compact Optimization Learning for AC Optimal Power Flow
IEEE Transactions on Power Systems (IEEE Trans. Power Syst.), 2023
Seonho Park
Wenbo Chen
Terrence W.K. Mak
Pascal Van Hentenryck
275
36
0
21 Jan 2023
Machine Learning for Electricity Market Clearing
Laurent Pagnier
Robert Ferrando
Y. Dvorkin
Michael Chertkov
164
2
0
23 May 2022
Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI
Proceedings of the IEEE (Proc. IEEE), 2022
Le Xie
Xiangtian Zheng
Yannan Sun
Tong Huang
Tony Bruton
AI4CE
301
35
0
10 May 2022
Sampling Strategies for Static Powergrid Models
International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH), 2022
Stephan Balduin
Eric M. S. P. Veith
S. Lehnhoff
111
2
0
19 Apr 2022
Learning Optimization Proxies for Large-Scale Security-Constrained Economic Dispatch
Electric power systems research (EPSR), 2021
Wenbo Chen
Seonho Park
Mathieu Tanneau
Pascal Van Hentenryck
160
53
0
27 Dec 2021
Deep Reinforcement Learning for Optimal Power Flow with Renewables Using Graph Information
Jinhao Li
Ruichang Zhang
Hao Wang
Zhi Liu
Hongyang Lai
Yanru Zhang
278
8
0
22 Dec 2021
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
424
10
0
15 Dec 2021
Controlling Smart Inverters using Proxies: A Chance-Constrained DNN-based Approach
IEEE Transactions on Smart Grid (IEEE Trans. Smart Grid), 2021
Sarthak Gupta
V. Kekatos
Ming Jin
248
31
0
02 May 2021
Deep Active Learning for Solvability Prediction in Power Systems
Journal of Modern Power Systems and Clean Energy (JMPSCE), 2020
Yichen Zhang
Jianzhe Liu
F. Qiu
Tianqi Hong
Rui Yao
179
12
0
27 Jul 2020
1
Page 1 of 1
