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A hybrid robust-stochastic approach to evaluate the profit of a multi-energy retailer in tri-layer energy markets

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  • Zare Oskouei, Morteza
  • Mirzaei, Mohammad Amin
  • Mohammadi-Ivatloo, Behnam
  • Shafiee, Mahmood
  • Marzband, Mousa
  • Anvari-Moghaddam, Amjad

Abstract

Nowadays, multi-energy consumers in the industrial sector have a significant contribution in exchange of different forms of energy such as electricity, heat, and natural gas. So, multi-energy consumers can provide excellent opportunities for market players to trade power in various energy markets. In this paper, a new entity called multi-energy retailer is introduced to simultaneously meet both flexible and non-flexible electrical, gas, and heat demands of multi-energy consumers, with a high level of supply reliability. The multi-energy retailer is equipped with cogeneration facilities and various storage technologies such as power-to-x storages to exploit the actual arbitrage opportunities in different layers of energy markets. The presented structure successfully models the behavior of multi-energy retailer entity and seeks to maximize its profit as well as increase the welfare level of the multi-energy consumers. The uncertainties associated with electricity market price and various demands of multi-energy consumers can affect the profit and optimal day-ahead scheduling of the multi-energy retailer. In order to accurately model such uncertainties, a hybrid robust-stochastic approach is utilized in this study. This approach helps the multi-energy retailer’s operator to evaluate the worst-case of the scheduling process for the entity. Finally, the profit of the multi-energy retailer entity is estimated in the presence of conversion facilities, demand response programs, and various uncertainties based on actual energy market data.

Suggested Citation

  • Zare Oskouei, Morteza & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Shafiee, Mahmood & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "A hybrid robust-stochastic approach to evaluate the profit of a multi-energy retailer in tri-layer energy markets," Energy, Elsevier, vol. 214(C).
    • Handle: RePEc:eee:energy:v:214:y:2021:i:c:s0360544220320557
    DOI: 10.1016/j.energy.2020.118948
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    7. Nasiri, Nima & Mansour Saatloo, Amin & Mirzaei, Mohammad Amin & Ravadanegh, Sajad Najafi & Zare, Kazem & Mohammadi-ivatloo, Behnam & Marzband, Mousa, 2023. "A robust bi-level optimization framework for participation of multi-energy service providers in integrated power and natural gas markets," Applied Energy, Elsevier, vol. 340(C).
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    9. Nasiri, Nima & Zeynali, Saeed & Ravadanegh, Sajad Najafi & Marzband, Mousa, 2021. "A hybrid robust-stochastic approach for strategic scheduling of a multi-energy system as a price-maker player in day-ahead wholesale market," Energy, Elsevier, vol. 235(C).
    10. Elsir, Mohamed & Al-Sumaiti, Ameena Saad & El Moursi, Mohamed Shawky & Al-Awami, Ali Taleb, 2023. "Coordinating the day-ahead operation scheduling for demand response and water desalination plants in smart grid," Applied Energy, Elsevier, vol. 335(C).
    11. Lin, Xiaojie & Lin, Xueru & Zhong, Wei & Zhou, Yi, 2024. "Multi-time scale dynamic operation optimization method for industrial park electricity-heat-gas integrated energy system considering demand elasticity," Energy, Elsevier, vol. 293(C).
    12. Li, Peng & Wang, Zixuan & Wang, Jiahao & Yang, Weihong & Guo, Tianyu & Yin, Yunxing, 2021. "Two-stage optimal operation of integrated energy system considering multiple uncertainties and integrated demand response," Energy, Elsevier, vol. 225(C).
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