Fetching the paper…
Reading the bibliography…
To address computational challenges associated with power flow nonconvexities, significant research efforts over the last decade have developed convex relaxations and approximations of optimal power flow (OPF) problems.
1908
Earlier work this paper cites.
R. A. Jabr, “Radial distribution load flow using conic programming,” IEEE Transactions on Power Systems , vol. 21, no. 3, pp. 1458–1459, 2006
2006
Earlier work this paper cites.
A. Wächter and L. T. Biegler, “On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming,” Mathematical Programming , vol. 106, no. 1, pp. 25–57, 2006
2006
Earlier work this paper cites.
J. Lavaei and S. H. Low, “Zero duality gap in optimal power flow problem,” IEEE Transactions on Power Systems , vol. 27, no. 1, pp. 92–107, 2011
2011
Earlier work this paper cites.
W. A. Bukhsh, A. Grothey, K. I. McKinnon, and P. A. Trodden, “Local solutions of the optimal power flow problem,” IEEE Transactions on Power Systems , vol. 28, no. 4, pp. 4780–4788, 2013
2013
Earlier work this paper cites.
C. Barrows, S. Blumsack, and P. Hines, “Correcting optimal transmission switching for AC power flows,” in 47th Hawaii International Conference on System Sciences , January 2014, pp. 2374–2379
2014
Earlier work this paper cites.
C. Coffrin and P. Van Hentenryck, “A linear-programming approximation of AC power flows,” INFORMS Journal on Computing , vol. 26, no. 4, pp. 718–734, 2014
2014
Earlier work this paper cites.
S. H. Low, “Convex relaxation of optimal power flow–Part II: Exactness,” IEEE Transactions on Control of Network Systems , vol. 1, no. 2, pp. 177–189, 2014
2014
Earlier work this paper cites.
R. Madani, S. Sojoudi, and J. Lavaei, “Convex relaxation for optimal power flow problem: Mesh networks,” IEEE Transactions on Power Systems , vol. 30, no. 1, pp. 199–211, 2014
2014
Earlier work this paper cites.
C. Coffrin, H. L. Hijazi, and P. Van Hentenryck, “The QC relaxation: A theoretical and computational study on optimal power flow,” IEEE Transactions on Power Systems , vol. 31, no. 4, pp. 3008–3018, 2015
2015
Cited alongside, same era.
D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” in 3rd International Conference for Learning Representations (ICLR) , 2015
2015
Cited alongside, same era.
D. K. Molzahn, “Computing the feasible spaces of optimal power flow problems,” IEEE Transactions on Power Systems , vol. 32, no. 6, pp. 4752–4763, 2017
2017
Cited alongside, same era.
A. Venzke, L. Halilbasic, U. Markovic, G. Hug, and S. Chatzivasileiadis, “Convex relaxations of chance constrained AC optimal power flow,” IEEE Transactions on Power Systems , vol. 33, no. 3, pp. 2829–2841, May 2018
2018
Cited alongside, same era.
A. Venzke, S. Chatzivasileiadis, and D. K. Molzahn, “Inexact convex relaxations for AC optimal power flow: Towards AC feasibility,” Electric Power Systems Research , vol. 187, p. 106480, 2020
2020
Later among the works it cites.
A. S. Zamzam and K. Baker, “Learning optimal solutions for extremely fast AC optimal power flow,” in IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) , 2020
2020
Later among the works it cites.
X. Fang, Z. Yang, J. Yu, and Y. Wang, “AC feasibility restoration in market clearing: Problem formulation and improvement,” IEEE Transactions on Industrial Informatics , vol. 18, no. 11, pp. 7597–7607, 2021
2021
Later among the works it cites.
L. A. Roald, D. Pozo, A. Papavasiliou, D. K. Molzahn, J. Kazempour, and A. Conejo, “Power systems optimization under uncertainty: A review of methods and applications,” to appear in
2022
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
C. Coffrin, R. Bent, K. Sundar, Y. Ng, and M. Lubin, “PowerModels.jl: An open-source framework for exploring power flow formulations,” in 20th Power Systems Computation Conference (PSCC) , 2018
2018
Cited alongside, same era.
D. Bienstock and A. Verma, “Strong NP-hardness of AC power flows feasibility,” Operations Research Letters , vol. 47, no. 6, pp. 494–501, 2019
2019
Cited alongside, same era.
D. K. Molzahn and I. A. Hiskens, “A survey of relaxations and approximations of the power flow equations,” Foundations and Trends in Electric Energy Systems , vol. 4, no. 1-2, pp. 1–221, 2019
2019
Cited alongside, same era.
Z. Tian and W. Wu, “Recover feasible solutions for SOCP relaxation of optimal power flow problems in mesh networks,” IET Generation, Transmission & Distribution , vol. 13, no. 7, pp. 1078–1087, 2019
2019
Cited alongside, same era.
K. Bestuzheva, H. Hijazi, and C. Coffrin, “Convex relaxations for quadratic on/off constraints and applications to optimal transmission switching,” INFORMS Journal on Computing , vol. 32, no. 3, pp. 682–696, 2020
2020
Cited alongside, same era.
M. Chatzos, T. W. K. Mak, and P. Van Hentenryck, “Spatial network decomposition for fast and scalable AC-OPF learning,” IEEE Transactions on Power Systems , vol. 37, no. 4, pp. 2601–2612, 2022
2022
Closest in time.
A. Kody, S. Chevalier, S. Chatzivasileiadis, and D. K. Molzahn, “Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment,” Electric Power Systems Research , vol. 212, p. 108282, 2022, presented at the 22nd Power Systems Computation Conference (PSCC 2022)
2022
Closest in time.
MOSEK ApS, Mosek Julia Packages , 2022
2022
Closest in time.
X. Pan, M. Chen, T. Zhao, and S. H. Low, “DeepOPF: A feasibility-optimized deep neural network approach for AC optimal power flow problems,” to appear in
2023
Closest in time.