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Supervised Learning for Optimal Power Flow as a Real-Time Proxy
IEEE PES Innovative Smart Grid Technologies Conference (ISGT), 2016
20 December 2016
Raphaël Canyasse
Gal Dalal
Shie Mannor
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Papers citing
"Supervised Learning for Optimal Power Flow as a Real-Time Proxy"
8 / 8 papers shown
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
147
9
0
31 Mar 2023
Machine Learning for Improved Gas Network Models in Coordinated Energy Systems
Adriano Arrigo
Mihály Dolányi
K. Bruninx
J. Toubeau
112
0
0
26 Sep 2022
Bucketized Active Sampling for Learning ACOPF
Electric power systems research (EPSR), 2022
Michael Klamkin
Mathieu Tanneau
Terrence W.K. Mak
Pascal Van Hentenryck
210
5
0
16 Aug 2022
Neural Predictive Control for the Optimization of Smart Grid Flexibility Schedules
S. D. Jongh
Sina Steinle
Anna Hlawatsch
F. Mueller
M. Suriyah
T. Leibfried
101
2
0
19 Aug 2021
A Meta-Learning Approach to the Optimal Power Flow Problem Under Topology Reconfigurations
Yexiang Chen
Ieee Subhash Lakshminarayana Senior Member
Carsten Maple
Ieee H. Vincent Poor Fellow
AI4CE
161
7
0
21 Dec 2020
Evaluating Machine Learning Models for the Fast Identification of Contingency Cases
Florian Schaefer
J. Menke
M. Braun
109
4
0
21 Aug 2020
Neural Networks for Encoding Dynamic Security-Constrained Optimal Power Flow
Daniel Timon Viola
Andreas Venzke
George S. Misyris
Spyros Chatzivasileiadis
431
43
0
17 Mar 2020
Machine Learning for AC Optimal Power Flow
Neel Guha
Zhecheng Wang
Matt Wytock
Arun Majumdar
AI4CE
131
75
0
19 Oct 2019
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