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Two-stage distributionally robust strategic offering in pool-based coupled electricity and gas market

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Listed:
  • Wang, Cheng
  • Sayed, Ahmed Rabee
  • Zhang, Han
  • Zhang, Xian
  • Ren, Jianpeng
  • Jia, Qiyue
  • Bi, Tianshu

Abstract

The intensified interactions between power and gas systems and the wide utilization of renewable energy introduce additional challenges in energy marketing and pricing mechanisms. Existing studies either neglect energy uncertainties in deterministic market-clearing models, use predetermined strategic offering prices in single-level models, or approximate gas dynamics in nonrealistic models. This paper proposes a bi-level two-stage distributionally robust electricity–gas market clearing (EG-MC) model considering energy uncertainties and strategic offering prices from energy producers. Strategic energy producers submit their offering prices in the upper-level problem to the EG-MC operator, who maximizes market profits under the realizations of renewable energy outputs while balancing the robustness and conservativeness of the day-ahead market decisions. The presence of gas dynamics in the two stages of the decision-making framework generates an intractable EG-MC problem. A novel triple-loop procedure, namely inner and outer columns & constraints generation and bilinear approximation algorithms, is proposed to sufficiently solve the formulated model. Finally, numerical analyses on an EG-MC model demonstrate the effectiveness of the distributionally robust strategic offers and the performances of the solution methodology.

Suggested Citation

  • Wang, Cheng & Sayed, Ahmed Rabee & Zhang, Han & Zhang, Xian & Ren, Jianpeng & Jia, Qiyue & Bi, Tianshu, 2023. "Two-stage distributionally robust strategic offering in pool-based coupled electricity and gas market," Energy, Elsevier, vol. 265(C).
  • Handle: RePEc:eee:energy:v:265:y:2023:i:c:s0360544222031747
    DOI: 10.1016/j.energy.2022.126288
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    References listed on IDEAS

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    1. Noorollahi, Younes & Golshanfard, Aminabbas & Hashemi-Dezaki, Hamed, 2022. "A scenario-based approach for optimal operation of energy hub under different schemes and structures," Energy, Elsevier, vol. 251(C).
    2. Wang, Jian & Xin, Hao & Xie, Ning & Wang, Yong, 2022. "Equilibrium models of coordinated electricity and natural gas markets with different coupling information exchanging channels," Energy, Elsevier, vol. 239(PA).
    3. Khojasteh, Meysam & Faria, Pedro & Lezama, Fernando & Vale, Zita, 2022. "Optimal strategy of electricity and natural gas aggregators in the energy and balance markets," Energy, Elsevier, vol. 257(C).
    4. Zhao, Baining & Qian, Tong & Tang, Wenhu & Liang, Qiheng, 2022. "A data-enhanced distributionally robust optimization method for economic dispatch of integrated electricity and natural gas systems with wind uncertainty," Energy, Elsevier, vol. 243(C).
    5. Francisco Facchinei & Christian Kanzow, 2010. "Generalized Nash Equilibrium Problems," Annals of Operations Research, Springer, vol. 175(1), pages 177-211, March.
    6. Sayed, Ahmed R. & Wang, Cheng & Bi, Tianshu, 2019. "Resilient operational strategies for power systems considering the interactions with natural gas systems," Applied Energy, Elsevier, vol. 241(C), pages 548-566.
    7. Sayed, Ahmed Rabee & Wang, Cheng & Chen, Sheng & Shang, Ce & Bi, Tianshu, 2021. "Distributionally robust day-ahead operation of power systems with two-stage gas contracting," Energy, Elsevier, vol. 231(C).
    8. Pang, Kang Ying & Liew, Peng Yen & Woon, Kok Sin & Ho, Wai Shin & Wan Alwi, Sharifah Rafidah & Klemeš, Jiří Jaromír, 2023. "Multi-period multi-objective optimisation model for multi-energy urban-industrial symbiosis with heat, cooling, power and hydrogen demands," Energy, Elsevier, vol. 262(PA).
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