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The optimal power flow (OPF) problem is one of the most important optimization problems for the operation of the power grid.
On the implementation of a primal-dual interior point method
Sanjay Mehrotra · 1992
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Electric Circuit Analysis (3rd Ed.)
David E. Johnson, Johnny R. Johnson, John L. Hilburn, and Peter D. Scott · 1997
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System and method for economic dispatching of electrical power, April 15 1997
Jason M Cohen and Douglas B Page · 1997
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Multitask learning
Rich Caruana · 1997
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Improved interior point method for opf problems
James A Momoh and JZ Zhu · 1999
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Nonlinear decentralized control of large-scale power systems
Yi Guo, David J Hill, and Youyi Wang · 2000
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Transmission management in the deregulated environment
R. D. Christie, B. F. Wollenberg, and I. Wangensteen · 2000
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Efficient large-scale power grid analysis based on preconditioned krylov-subspace iterative methods
Tsung-Hao Chen and Charlie Chung-Ping Chen · 2001
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A parallel opf approach for large-scale power systems
Y Huang, T Kashiwagi, and S Morozumi · 2002
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Radial distribution load flow using conic programming
R. A. Jabr · 2006
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On the computation and application of multi-period security-constrained optimal power flow for real-time electricity market operations
Hongye Wang · 2007
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Dc power flow revisited
B. Stott, J. Jardim, and O. Alsac · 2009
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Optimal power flow (opf) in large-scale power grid simulation
Cong Liu, Jianhui Wang, and Jiaxin Ning · 2010
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Transfer learning
Lisa Torrey and Jude Shavlik · 2010
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Robust optimal power flow solution using trust region and interior-point methods
A. A. Sousa, G. L. Torres, and C. A. Cañizares · 2011
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How significant is a boxplot outlier?
Robert Dawson · 2011
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Real-time simulation of power grid disruption, July 25 2013
Steven J Fernandez, Mallikarjun Shankar, James J Nutaro, Yilu Liu, Aleksandar D Dimitrovski, Olufemi A Omitaomu, Christopher S Groer, Kyle L Spafford, and Ranga R Vatsavai · 2013
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Parallel distributed-memory simplex for large-scale stochastic lp problems
Miles Lubin, JA Julian Hall, Cosmin G Petra, and Mihai Anitescu · 2013
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Artificial neural network (ann) modeling of the pulsed heat load during iter cs magnet operation
L Savoldi Richard, R Bonifetto, Stefano Carli, A Froio, A Foussat, and R Zanino · 2014
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Real-time stability in power systems: techniques for early detection of the risk of blackout
Savu C Savulescu · 2014
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Real-time stochastic optimization of complex energy systems on high-performance computers
Cosmin G Petra, Olaf Schenk, and Mihai Anitescu · 2014
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Convex relaxation of optimal power flow—part ii: Exactness
Steven H. Low · 2014
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Structured nonconvex optimization of large-scale energy systems using pips-nlp
Cosmoflow: Using deep learning to learn the universe at scale
Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Kärnä, Diana Moise, Simon J Pennycook, et al · 2018
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Statistical learning for dc optimal power flow
Yeesian Ng, Sidhant Misra, Line A Roald, and Scott Backhaus · 2018
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Toward multiperiod ac-based contingency constrained optimal power flow at large scale
M. Schanen, F. Gilbert, C. G. Petra, and M. Anitescu · 2018
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Adaptive neural network-based approximation to accelerate eulerian fluid simulation
Wenqian Dong, Jie Liu, Zhen Xie, and Dong Li · 2019
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Scalable reinforcement-learning-based neural architecture search for cancer deep learning research
Prasanna Balaprakash, Romain Egele, Misha Salim, Stefan Wild, Venkatram Vishwanath, Fangfang Xia, Tom Brettin, and Rick Stevens · 2019
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N. Chiang, C. G. Petra, and V. M. Zavala · 2014
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cudnn: Efficient primitives for deep learning
Sharan Chetlur, Cliff Woolley, Philippe Vandermersch, Jonathan Cohen, John Tran, Bryan Catanzaro, and Evan Shelhamer · 2014
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Fast machine-learning online optimization of ultra-cold-atom experiments
P B. Wigley, P J. Everitt, Anton Hengel, John Bastian, M A. Sooriyabandara, Gordon McDonald, Kyle Hardman, C D. Quinlivan, Manju Perumbil, Carlos claiton Noschang kuhn, I R. Petersen, Andre Luiten, J Hope, N Robins, and Michael Hush · 2015
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Solving security constrained optimal power flow problems by a structure exploiting interior point method
Naiyuan Chiang and Andreas Grothey · 2015
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Neutrino Identification with a Convolutional Neural Network in the NOvA Detectors
Alexander Radovic · 2016
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Matpower 6.0 user’s manual
Ray D Zimmerman and Carlos E Murillo-Sánchez · 2016
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A knowledge-based framework for power flow and optimal power flow analyses
Alfredo Vaccaro and Claudio Canizares · 2016
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Highly-ccalable, physics-informed gans for learning solutions of stochastic pdes
Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David Barajas-Solano, Josh Romero, Valentin Churavy, Alexandre Tartakovsky, Michael Houston, Mr Prabhat, et al · 2019
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Tomogan: Low-dose x-ray tomography with generative adversarial networks
Zhengchun Liu, Tekin Bicer, Rajkumar Kettimuthu, Doga Gursoy, Francesco De Carlo, and Ian Foster · 2019
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Deep learning accelerated light source experiments
Zhengchun Liu, Tekin Bicer, Rajkumar Kettimuthu, and Ian Foster · 2019
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Machine learning for ac optimal power flow
Neel Guha, Zhecheng Wang, Matt Wytock, and Arun Majumdar · 2019
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Learning warm-start points for ac optimal power flow
Kyri Baker · 2019
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Learning optimal solutions for extremely fast ac optimal power flow
Ahmed Zamzam and Kyri Baker · 2019
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Learning for dc-opf: Classifying active sets using neural nets
Deepjyoti Deka and Sidhant Misra · 2019
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Deepopf: A deep neural network approach for security-constrained dc optimal power flow
Xiang Pan, Tianyu Zhao, and Minghua Chen · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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On a comparison of newton–raphson solvers for power flow problems
Baljinnyam Sereeter, Cornelis Vuik, and Cees Witteveen · 2019
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Linear power flow method improved with numerical analysis techniques applied to a very large network
Baljinnyam Sereeter, Werner van Westering, Cornelis Vuik, and Cees Witteveen · 2019
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86 pflops deep potential molecular dynamics simulation of 100 million atoms with ab initio accuracy
Denghui Lu, Han Wang, Mohan Chen, Jiduan Liu, Lin Lin, Roberto Car, Weile Jia, Linfeng Zhang, et al · 2020
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