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A multi-period unit commitment problem under a new hybrid uncertainty set for a renewable energy source

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  • Melamed, Michal
  • Ben-Tal, Aharon
  • Golany, Boaz

Abstract

Recently, there is a growing use of renewable energy in the electricity markets due to governmental subsidy aiming to comply with reduced greenhouse gas emission targets. Jointly with its highly volatile generation it greatly affects the operation planning of power plants, particularly, when addressing the unit commitment problem (UCP).

Suggested Citation

  • Melamed, Michal & Ben-Tal, Aharon & Golany, Boaz, 2018. "A multi-period unit commitment problem under a new hybrid uncertainty set for a renewable energy source," Renewable Energy, Elsevier, vol. 118(C), pages 909-917.
    • Handle: RePEc:eee:renene:v:118:y:2018:i:c:p:909-917
    DOI: 10.1016/j.renene.2016.05.095
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    References listed on IDEAS

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    1. Santiago Cerisola & Álvaro Baíllo & José M. Fernández-López & Andrés Ramos & Ralf Gollmer, 2009. "Stochastic Power Generation Unit Commitment in Electricity Markets: A Novel Formulation and a Comparison of Solution Methods," Operations Research, INFORMS, vol. 57(1), pages 32-46, February.
    2. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    3. Anthony Papavasiliou & Shmuel S. Oren, 2013. "Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network," Operations Research, INFORMS, vol. 61(3), pages 578-592, June.
    4. Matthias Nowak & Werner Römisch, 2000. "Stochastic Lagrangian Relaxation Applied to Power Scheduling in a Hydro-Thermal System under Uncertainty," Annals of Operations Research, Springer, vol. 100(1), pages 251-272, December.
    5. J. Benders, 2005. "Partitioning procedures for solving mixed-variables programming problems," Computational Management Science, Springer, vol. 2(1), pages 3-19, January.
    6. Aharon Ben-Tal & Boaz Golany & Arkadi Nemirovski & Jean-Philippe Vial, 2005. "Retailer-Supplier Flexible Commitments Contracts: A Robust Optimization Approach," Manufacturing & Service Operations Management, INFORMS, vol. 7(3), pages 248-271, February.
    7. Jorge Valenzuela & Mainak Mazumdar, 2003. "Commitment of Electric Power Generators Under Stochastic Market Prices," Operations Research, INFORMS, vol. 51(6), pages 880-893, December.
    8. PAPAVASILIOU, Anthony & OREN, Schmuel S., 2013. "Multiarea stochastic unit commitment for high wind penetration in a transmission constrained network," LIDAM Reprints CORE 2500, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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    Cited by:

    1. Zhang, Yachao & Huang, Zhanghao & Zheng, Feng & Zhou, Rongyu & Le, Jian & An, Xueli, 2020. "Cooperative optimization scheduling of the electricity-gas coupled system considering wind power uncertainty via a decomposition-coordination framework," Energy, Elsevier, vol. 194(C).
    2. Zhang, Yachao & Le, Jian & Zheng, Feng & Zhang, Yi & Liu, Kaipei, 2019. "Two-stage distributionally robust coordinated scheduling for gas-electricity integrated energy system considering wind power uncertainty and reserve capacity configuration," Renewable Energy, Elsevier, vol. 135(C), pages 122-135.
    3. Serhat Yüksel & Hasan Dinçer & Yurdagül Meral, 2019. "Financial Analysis of International Energy Trade: A Strategic Outlook for EU-15," Energies, MDPI, vol. 12(3), pages 1-22, January.
    4. Mirzaei, Mohammad Amin & Sadeghi-Yazdankhah, Ahmad & Mohammadi-Ivatloo, Behnam & Marzband, Mousa & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Integration of emerging resources in IGDT-based robust scheduling of combined power and natural gas systems considering flexible ramping products," Energy, Elsevier, vol. 189(C).
    5. Hongxia Liu & Huiling Wang & Zongtang Xie, 2019. "Wind utilization and carbon emissions equilibrium: Scheduling strategy for wind-thermal generation system," Energy & Environment, , vol. 30(6), pages 1111-1131, September.
    6. 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.
    7. Abdi, Hamdi, 2021. "Profit-based unit commitment problem: A review of models, methods, challenges, and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    8. Xiaokun Man & Hongyan Song & Huanhuan Li, 2023. "Estimating Hydropower Generation Flexibilities of a Hybrid Hydro–Wind Power System: From the Perspective of Multi-Time Scales," Energies, MDPI, vol. 16(13), pages 1-17, July.
    9. M. A. El-Shorbagy & A. A. Mousa & M. A. Farag, 2019. "An intelligent computing technique based on a dynamic-size subpopulations for unit commitment problem," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 911-944, September.
    10. Yang, Yuqi & Zhou, Jianzhong & Liu, Guangbiao & Mo, Li & Wang, Yongqiang & Jia, Benjun & He, Feifei, 2020. "Multi-plan formulation of hydropower generation considering uncertainty of wind power," Applied Energy, Elsevier, vol. 260(C).

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