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A market framework to exploit the multi-energy operating reserve of smart energy hubs in the integrated electricity-gas systems

Author

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  • Hou, Yanqiu
  • Bao, Minglei
  • Sang, Maosheng
  • Ding, Yi

Abstract

Faced with increasing uncertainties in the integrated electricity and gas system (IEGS), the multi-energy operating reserve(MOR), i.e., extra electric and gas reserve capacity, is becoming vitally important to guarantee the reliable operation of the system. Smart energy hubs(SEHs) located at the demand side of the IEGS can adjust their electricity and gas consumption through energy substitution, which has great potential to provide the MOR. Current studies mainly concentrate on the energy trading mechanism among different SEHs in the energy-only market, which may not effectively incentivize SEHs to provide MOR for system operation. Besides, due to the limited energy capacity, SEHs cannot directly participate in the wholesale reserve market along with other large-capacity resources, e.g., power plants and gas wells. To address these, a two-stage market framework is proposed for exploiting the multi-energy operating reserve of SEHs. In the first stage, the wholesale market is cleared considering the participation of large-capacity resources to determine the clearing results of MOR. Based on the results, an energy-loss-cost calculation model is developed to measure the value of the specific MOR level. By altering the reserve requirements, the values of different MOR levels can be accordingly calculated to formulate the multi-energy operating reserve demand surface(MOR-DS), which can quantify varying MOR values with different levels of the reserve. With the MOR-DS describing the price elasticity of the MOR, a distributed MOR clearing mechanism is developed in the second stage to determine the quantity and price of the reserve from SEHs. The clearing mechanism is constructed as a distributed optimization model considering optimal collaboration among different SEHs. Case studies verify that the proposed market framework can effectively stimulate SEHs to provide MOP through economic incentives, which can realize the reliability improvement of IEGS and the revenue increase of SEHs.

Suggested Citation

  • Hou, Yanqiu & Bao, Minglei & Sang, Maosheng & Ding, Yi, 2024. "A market framework to exploit the multi-energy operating reserve of smart energy hubs in the integrated electricity-gas systems," Applied Energy, Elsevier, vol. 357(C).
    • Handle: RePEc:eee:appene:v:357:y:2024:i:c:s0306261923016434
    DOI: 10.1016/j.apenergy.2023.122279
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    References listed on IDEAS

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    1. Zheng, Ling & Zhou, Bin & Cao, Yijia & Wing Or, Siu & Li, Yong & Wing Chan, Ka, 2022. "Hierarchical distributed multi-energy demand response for coordinated operation of building clusters," Applied Energy, Elsevier, vol. 308(C).
    2. B. S. He & H. Yang & S. L. Wang, 2000. "Alternating Direction Method with Self-Adaptive Penalty Parameters for Monotone Variational Inequalities," Journal of Optimization Theory and Applications, Springer, vol. 106(2), pages 337-356, August.
    3. Davatgaran, Vahid & Saniei, Mohsen & Mortazavi, Seyed Saeidollah, 2018. "Optimal bidding strategy for an energy hub in energy market," Energy, Elsevier, vol. 148(C), pages 482-493.
    4. Wu, Gang & Xiang, Yue & Liu, Junyong & Shen, Xiaodong & Cheng, Shikun & Hong, Bowen & Jawad, Shafqat, 2020. "Distributed energy-reserve Co-Optimization of electricity and natural gas systems with multi-type reserve resources," Energy, Elsevier, vol. 207(C).
    5. Liu, Fan & Bie, Zhaohong & Liu, Shiyu & Ding, Tao, 2017. "Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements," Applied Energy, Elsevier, vol. 188(C), pages 399-408.
    6. Bao, Minglei & Hui, Hengyu & Ding, Yi & Sun, Xiaocong & Zheng, Chenghang & Gao, Xiang, 2023. "An efficient framework for exploiting operational flexibility of load energy hubs in risk management of integrated electricity-gas systems," Applied Energy, Elsevier, vol. 338(C).
    7. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
    8. Liu, Peiyun & Ding, Tao & Zou, Zhixiang & Yang, Yongheng, 2019. "Integrated demand response for a load serving entity in multi-energy market considering network constraints," Applied Energy, Elsevier, vol. 250(C), pages 512-529.
    9. DE WOLF, Daniel & SMEERS, Yves, 2000. "The gas transmission problem solved by an extension of the simplex algorithm," LIDAM Reprints CORE 1489, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Daniel De Wolf & Yves Smeers, 2000. "The Gas Transmission Problem Solved by an Extension of the Simplex Algorithm," Management Science, INFORMS, vol. 46(11), pages 1454-1465, November.
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