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Optimal risk-constrained participation of industrial cogeneration systems in the day-ahead energy markets

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  • Alipour, Manijeh
  • Zare, Kazem
  • Mohammadi-Ivatloo, Behnam

Abstract

This paper presents an optimal bidding strategy for industrial consumers with cogeneration facilities, power-only and heat-only units to participate in day-ahead electricity market. A information gap decision theory (IGDT) technique is implemented for determining the optimal bidding strategies considering market price uncertainty. IGDT evaluates the robustness/opportunity of optimal bidding strategy under market price uncertainty considering the consumer choice of taking risk-averse or risk-taking decisions. It is confirmed that the risk-averse or risk-taking decisions might affect the expected profit and bidding curve of the consumers.

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  • Alipour, Manijeh & Zare, Kazem & Mohammadi-Ivatloo, Behnam, 2016. "Optimal risk-constrained participation of industrial cogeneration systems in the day-ahead energy markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 421-432.
  • Handle: RePEc:eee:rensus:v:60:y:2016:i:c:p:421-432
    DOI: 10.1016/j.rser.2015.12.136
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    2. Majidi, M. & Mohammadi-Ivatloo, B. & Soroudi, A., 2019. "Application of information gap decision theory in practical energy problems: A comprehensive review," Applied Energy, Elsevier, vol. 249(C), pages 157-165.
    3. Kia, Mohsen & Setayesh Nazar, Mehrdad & Sepasian, Mohammad Sadegh & Heidari, Alireza & Siano, Pierluigi, 2017. "An efficient linear model for optimal day ahead scheduling of CHP units in active distribution networks considering load commitment programs," Energy, Elsevier, vol. 139(C), pages 798-817.
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    5. Liu, Ming & Wang, Shan & Zhao, Yongliang & Tang, Haiyu & Yan, Junjie, 2019. "Heat–power decoupling technologies for coal-fired CHP plants: Operation flexibility and thermodynamic performance," Energy, Elsevier, vol. 188(C).
    6. Hossein Shayeghi & Elnaz Shahryari & Mohammad Moradzadeh & Pierluigi Siano, 2019. "A Survey on Microgrid Energy Management Considering Flexible Energy Sources," Energies, MDPI, vol. 12(11), pages 1-26, June.
    7. Misaghian, M.S. & Saffari, M. & Kia, M. & Heidari, A. & Shafie-khah, M. & Catalão, J.P.S., 2018. "Tri-level optimization of industrial microgrids considering renewable energy sources, combined heat and power units, thermal and electrical storage systems," Energy, Elsevier, vol. 161(C), pages 396-411.
    8. Ussama Assad & Muhammad Arshad Shehzad Hassan & Umar Farooq & Asif Kabir & Muhammad Zeeshan Khan & S. Sabahat H. Bukhari & Zain ul Abidin Jaffri & Judit Oláh & József Popp, 2022. "Smart Grid, Demand Response and Optimization: A Critical Review of Computational Methods," Energies, MDPI, vol. 15(6), pages 1-36, March.
    9. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Yousefi, Hossein, 2017. "Energy hub: From a model to a concept – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1512-1527.
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    11. Kalavani, Farshad & Mohammadi-Ivatloo, Behnam & Zare, Kazem, 2019. "Optimal stochastic scheduling of cryogenic energy storage with wind power in the presence of a demand response program," Renewable Energy, Elsevier, vol. 130(C), pages 268-280.

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