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A Stackelberg game-based approach to transaction optimization for distributed integrated energy system

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  • Wang, Yongli
  • Liu, Zhen
  • Wang, Jingyan
  • Du, Boxin
  • Qin, Yumeng
  • Liu, Xiaoli
  • Liu, Lin

Abstract

Distributed integrated energy system (DIES) will become the main energy supply method for end-users, however, the volatility of renewable energy makes energy consumption more difficult. To address the problem, this paper proposed an optimization method of DIES energy transaction based on Stackelberg game. Firstly, the typical structure of DIES is studied and a energy transaction framework of electric-heat energy is proposed by introducing integrated energy operator(IEO); secondly, with IEO as the leader and DIES as the follower, considering the highest profit of IEO and the lowest cost and carbon emission of DIES as the objectives, and combining the operational constraints of different subjects, a one-master-multiple-slave Stackelberg game model is established; thirdly, the existence of Nash equilibrium of this game model is demonstrated, and a solution algorithm based on Particle swarm optimization nested Non-dominated Sorting Genetic Algorithm-II is proposed; Finally, to verify the validity of this model, two modes are designed and simulated, and the results show that the proposed method can improve the renewable energy consumption by 2.92%, reduce the DIES energy cost by 3.94%, and reduce the interactive power with the grid by 30.91%, while the sensitivity analysis shows that the method can better cope with energy price changes.

Suggested Citation

  • Wang, Yongli & Liu, Zhen & Wang, Jingyan & Du, Boxin & Qin, Yumeng & Liu, Xiaoli & Liu, Lin, 2023. "A Stackelberg game-based approach to transaction optimization for distributed integrated energy system," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223018698
    DOI: 10.1016/j.energy.2023.128475
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    References listed on IDEAS

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    1. Yu, Mengmeng & Hong, Seung Ho, 2017. "Incentive-based demand response considering hierarchical electricity market: A Stackelberg game approach," Applied Energy, Elsevier, vol. 203(C), pages 267-279.
    2. Yu, Mengmeng & Hong, Seung Ho, 2016. "Supply–demand balancing for power management in smart grid: A Stackelberg game approach," Applied Energy, Elsevier, vol. 164(C), pages 702-710.
    3. Huang, Qisheng & Xu, Yunjian & Courcoubetis, Costas, 2020. "Stackelberg competition between merchant and regulated storage investment in wholesale electricity markets," Applied Energy, Elsevier, vol. 264(C).
    4. Wei, F. & Jing, Z.X. & Wu, Peter Z. & Wu, Q.H., 2017. "A Stackelberg game approach for multiple energies trading in integrated energy systems," Applied Energy, Elsevier, vol. 200(C), pages 315-329.
    5. Huang, Yujing & Wang, Yudong & Liu, Nian, 2022. "A two-stage energy management for heat-electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization," Energy, Elsevier, vol. 244(PA).
    6. Wang, Haiyang & Zhang, Chenghui & Li, Ke & Liu, Shuai & Li, Shuzhen & Wang, Yu, 2021. "Distributed coordinative transaction of a community integrated energy system based on a tri-level game model," Applied Energy, Elsevier, vol. 295(C).
    7. Wang, Yongli & Li, Jiapu & Wang, Shuo & Yang, Jiale & Qi, Chengyuan & Guo, Hongzhen & Liu, Ximei & Zhang, Hongqing, 2020. "Operational optimization of wastewater reuse integrated energy system," Energy, Elsevier, vol. 200(C).
    8. Li, Yang & Wang, Bin & Yang, Zhen & Li, Jiazheng & Chen, Chen, 2022. "Hierarchical stochastic scheduling of multi-community integrated energy systems in uncertain environments via Stackelberg game," Applied Energy, Elsevier, vol. 308(C).
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    Cited by:

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    2. Wang, Yifeng & Jiang, Aihua & Wang, Rui & Tian, Junyang, 2024. "A canonical coalitional game model incorporating motivational psychology analysis for incentivizing stable direct energy trading in smart grid," Energy, Elsevier, vol. 289(C).

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