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Optimal power flow (OPF) is one of the most important optimization problems in the energy industry.
“Optimal power flow by enhanced genetic algorithm,”
A. G. Bakirtzis, P. N. Biskas, C. E. Zoumas, and V. Petridis, · 2002
Earlier work this paper cites.
“A power flow method suitable for solving OPF problems using genetic algorithms,”
M. Todorovksi and D. Rajicic, · 2003
Earlier work this paper cites.
“Convexity of the set of feasible injections and revenue adequacy in FTR markets,”
B. C. Lesieutre and I. A. Hiskens, · 2005
Earlier work this paper cites.
“A modified particle swarm optimization algorithm and its application in optimal power flow problem,”
C.-R. Wang, H.-J. Yan, Z.-Q. Huang, J.-W. Zhang, and C.-J. Sun, · 2005
Earlier work this paper cites.
“On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming,”
A. Wächter and L. T. Biegler, · 2006
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“Applications of computational intelligence techniques for solving the revived optimal power flow problem,”
M. R. AlRashidi and M. E. El-Hawary, · 2009
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“MATPOWER: Steady-state operations, planning, and analysis tools for power systems research and education,”
R. D. Zimmerman, C. E. Murillo-Sánchez, and R. J. Thomas, · 2011
Earlier work this paper cites.
“History of optimal power flow and formulations,”
M. B. Cain, R. P. O’Neill, and A. Castillo, · 2012
Earlier work this paper cites.
“Computational performance of solution techniques applied to the ACOPF,”
A. Castillo and R. P. O’Neill, · 2013
Earlier work this paper cites.
“Discrete signal processing on graphs,”
A. Sandryhaila and J. M. F. Moura, · 2013
Cited alongside, same era.
“The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains,”
D. I Shuman, S. K. Narang, P. Frossard, A. Ortega, and P. Vandergheynst, · 2013
Cited alongside, same era.
“Spectral networks and deep locally connected networks on graphs,”
J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun, · 2014
Cited alongside, same era.
“Convex relaxations of optimal power flow problems: An illustrative example,”
D. K. Molzahn and I. A. Hiskens, · 2016
Cited alongside, same era.
“Convolutional neural networks on graphs with fast localized spectral filtering,”
M. Defferrard, X. Bresson, and P. Vandergheynst, · 2016
Cited alongside, same era.
“Optimal graph-filter design and applications to distributed linear network operators,”
“Strong NP-hardness of AC power flows feasibility,”
D. Bienstock and A. Verma, · 2019
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“Towards distributed energy services: Decentralizing optimal power flow with machine learning,”
R. Dobbe, O. Sondermeijer, D. Fridovich-Keil, D. Arnold, D. Callaway, and C. Tomlin, · 2019
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“Regression-based inverter control for decentralized optimal power flow and voltage regulation,”
O. Sondermeijer, R. Dobbe, D. Arnold, C. Tomlin, and T. Keviczky, · 2019
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“Machine learning for AC optimal power flow,”
N. Guha, Z. Wang, and A. Majumdar, · 2019
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“Convolutional neural network architectures for signals supported on graphs,”
F. Gama, A. G. Marques, G. Leus, and A. Ribeiro, · 2019
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S. Segarra, A. G. Marques, and A. Ribeiro, · 2017
Cited alongside, same era.
“Lecture notes on optimal power flow OPF,”
S. Chatzivasileiadis, · 2018
Cited alongside, same era.
“Pandapower: An open-source python tool for convenient modeling, analysis, and optimization of electric power systems,”
L. Thurner, A. Scheidler, F. Schäfer, J. Menke, J. Dollichon, F. Meier, S. Meinecke, and M. Braun, · 2018
Cited alongside, same era.
“Graph signal processing: Overview, challenges and applications,”
A. Ortega, P. Frossard, J. Kovačević, J. M. F. Moura, and P. Vandergheynst, · 2018
Cited alongside, same era.
G. Lan and Z. Zhou, · 2019
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“Stability properties of graph neural networks,”
F. Gama, J. Bruna, and A. Ribeiro, · 2019
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“Optimal wireless resource allocation with random edge graph neural networks,”
M. Eisen and A. Ribeiro, · 2019
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“Learning decentralized controllers for robot swarms with graph neural networks,”
E. Tolstaya, F. Gama, J. Paulos, G. Pappas, V. Kumar, and A. Ribeiro, · 2019
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