Polynomial time algorithms and extended formulations for unit commitment problems
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DOI: 10.1080/24725854.2017.1397303
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Cited by:
- Jianqiu Huang & Kai Pan & Yongpei Guan, 2021. "Multistage Stochastic Power Generation Scheduling Co-Optimizing Energy and Ancillary Services," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 352-369, January.
- Skolfield, J. Kyle & Escobedo, Adolfo R., 2022. "Operations research in optimal power flow: A guide to recent and emerging methodologies and applications," European Journal of Operational Research, Elsevier, vol. 300(2), pages 387-404.
- Kai Pan & Ming Zhao & Chung-Lun Li & Feng Qiu, 2022. "A Polyhedral Study on Fuel-Constrained Unit Commitment," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 3309-3324, November.
- Bernard Knueven & James Ostrowski & Jean-Paul Watson, 2020. "On Mixed-Integer Programming Formulations for the Unit Commitment Problem," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 857-876, October.
- Heng Yang & Ziliang Jin & Jianhua Wang & Yong Zhao & Hejia Wang & Weihua Xiao, 2019. "Data-Driven Stochastic Scheduling for Energy Integrated Systems," Energies, MDPI, vol. 12(12), pages 1-21, June.
- Farhan Hyder & Bing Yan & Mikhail Bragin & Peter Luh, 2024. "Convex Hull Pricing for Unit Commitment: Survey, Insights, and Discussions," Energies, MDPI, vol. 17(19), pages 1-20, September.
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