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Optimal trading strategies for multi-energy microgrid cluster considering demand response under different trading modes: A comparison study

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  • Wu, Qiong
  • Xie, Zhun
  • Ren, Hongbo
  • Li, Qifen
  • Yang, Yongwen

Abstract

The linkage of neighboring multi-energy microgrids may overcome the disadvantage of one single microgrid since the surplus/deficient energy can meet internal balance and realize self-satisfaction. In order to realize successful cooperation of such a complicated energy system, optimal trading strategy and reasonable trading price among all entities are important. In this study, a bi-level optimization model combined of two trading modes is proposed under different scenarios: an intermediary agent-based trading mode where the intermediary agent acts as an intermediate operator, as well as a direct trading mode without intermediary agent. The Stackelberg game theory-based method and the supply/demand ratio method are used for price determination, respectively. In addition, the integrated demand response is also considered in this study. As an illustrative example, a comparative study is implemented in a neighboring energy cluster combing three park-level multi-energy microgrids. The results show that, compared with the situation that each multi-energy microgrid acts alone, a cluster obviously increases total benefits, which may contribute to the development of tailored policy instruments. In addition, although direct trading among multi-energy microgrids enjoys higher benefits, its self-sufficient ability is lower than the situation considering intermediary agent, which may help policymakers to predict the merits and demerits associated with different energy trading modes among multi-energy microgrids in a more accurate way.

Suggested Citation

  • Wu, Qiong & Xie, Zhun & Ren, Hongbo & Li, Qifen & Yang, Yongwen, 2022. "Optimal trading strategies for multi-energy microgrid cluster considering demand response under different trading modes: A comparison study," Energy, Elsevier, vol. 254(PC).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pc:s0360544222013512
    DOI: 10.1016/j.energy.2022.124448
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    2. Liu, Xinglei & Liu, Jun & Ren, Kezheng & Liu, Xiaoming & Liu, Jiacheng, 2022. "An integrated fuzzy multi-energy transaction evaluation approach for energy internet markets considering judgement credibility and variable rough precision," Energy, Elsevier, vol. 261(PB).
    3. Shi, Mengshu & Huang, Yuansheng & Lin, Hongyu, 2023. "Research on power to hydrogen optimization and profit distribution of microgrid cluster considering shared hydrogen storage," Energy, Elsevier, vol. 264(C).
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    6. Fang, Xiaolun & Dong, Wei & Wang, Yubin & Yang, Qiang, 2022. "Multiple time-scale energy management strategy for a hydrogen-based multi-energy microgrid," Applied Energy, Elsevier, vol. 328(C).

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