The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Semidefinite programming for optimal power flow problems
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Citations
Cites
Primal-Dual Interior-Point Methods
Wright, S. J. (1997) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611971453 · Cited by 2,391
Structured semidefinite programs and semialgebraic geometry methods in robustness and optimization
Parrilo, P. A. (2000) · doi:10.7907/2k6y-ch43 · Cited by 1,802
Dommel, H., & Tinney, W. (1968) · IEEE Transactions on Power Apparatus and Systems · doi:10.1109/tpas.1968.292150 · Cited by 1,664
Cones of Matrices and Set-Functions and 0–1 Optimization
Lovász, L., & Schrijver, A. (1991) · SIAM Journal on Optimization · doi:10.1137/0801013 · Cited by 1,008
Optimal reactive dispatch through interior point methods
Granville, S. (1994) · IEEE Transactions on Power Systems · doi:10.1109/59.317548 · Cited by 876
Handbook of applied optimization
(2002) · Choice Reviews Online · doi:10.5860/choice.40-1593 · Cited by 867
Alizadeh, F., Haeberly, J.-P. A., & Overton, M. L. (1998) · SIAM Journal on Optimization · doi:10.1137/s1052623496304700 · Cited by 480
An interior point nonlinear programming for optimal power flow problems with a novel data structure
Wei, H., Sasaki, H., Kubokawa, J., & Yokoyama, R. (1998) · IEEE Transactions on Power Systems · doi:10.1109/59.708745 · Cited by 383
Self-citationSolving Large-Scale Sparse Semidefinite Programs for Combinatorial Optimization
Benson, S. J., Ye, Y., & Zhang, X. (2000) · SIAM Journal on Optimization · doi:10.1137/s1052623497328008 · Cited by 276
Fast linear iterations for distributed averaging
Xiao, L., & Boyd, S. (2004) · 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475) · doi:10.1109/cdc.2003.1272421 · Cited by 218
Cited by
Branch Flow Model: Relaxations and Convexification—Part I
Farivar, M., & Low, S. H. (2013) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2013.2255317 · Cited by 1,541
Convex Models of Distribution System Reconfiguration
Taylor, J. A., & Hover, F. S. (2012) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2012.2184307 · Cited by 444
Convex relaxations and linear approximation for optimal power flow in multiphase radial networks
Gan, L., & Low, S. H. (2014) · 2014 Power Systems Computation Conference · doi:10.1109/pscc.2014.7038399 · Cited by 416
Local flexibility markets: Literature review on concepts, models and clearing methods
Jin, X., Wu, Q., & Jia, H. (2020) · Applied Energy · doi:10.1016/j.apenergy.2019.114387 · Cited by 373
Toward Distributed Energy Services: Decentralizing Optimal Power Flow With Machine Learning
Dobbe, R., Sondermeijer, O., Fridovich-Keil, D., Arnold, D., Callaway, D., & Tomlin, C. (2020) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2019.2935711 · Cited by 120
Metadata
- Authors
- Bai, X., Wei, H., Fujisawa, K., & Wang, Y.
- Venue
- International Journal of Electrical Power & Energy Systems
- Publisher
- Elsevier BV
- Published
- 2008-07
- Volume
- 30
- Issue
- 6-7
- Pages
- 383-392
- ISSN
- 0142-0615 (ISSN-L)
- OpenAlex
- W2086664392
- Cited by
- 573
- References
- 18
- FWCI
- 3.59
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Bai, X., Wei, H., Fujisawa, K., & Wang, Y. (2008). Semidefinite programming for optimal power flow problems. International Journal of Electrical Power & Energy Systems. https://doi.org/10.1016/j.ijepes.2007.12.003
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.