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Market Trading Model of Urban Energy Internet Based on Tripartite Game Theory

Author

Listed:
  • Jun Liu

    (Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

  • Jinchun Chen

    (Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

  • Chao Wang

    (Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

  • Zhang Chen

    (Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

  • Xinglei Liu

    (Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

As an important driving force to promote the energy revolution, the emergence of the energy internet has provided new ideas for the marketization and flexibility of multi-energy transactions. How to realize multi-energy joint trading is a key issue in the development of the energy market. An urban energy internet market trading model among energy suppliers, energy service providers and the large users in the urban area, based on tripartite game theory, is established in this paper. Considering the cost–income function of each market entity and the basic market trading mechanism, a new game-tree search method is proposed to solve the Nash equilibria for the game model. The Nash equilibria of the tripartite game can be obtained, and the market transaction status corresponding to the Nash equilibria is analyzed from the perspective of the market transactions. The multi-energy joint transaction and market equilibria can be easily implemented for the bids and offers of the multiple energy entities in the urban energy internet market.

Suggested Citation

  • Jun Liu & Jinchun Chen & Chao Wang & Zhang Chen & Xinglei Liu, 2020. "Market Trading Model of Urban Energy Internet Based on Tripartite Game Theory," Energies, MDPI, vol. 13(7), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1834-:d:343758
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    References listed on IDEAS

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    Cited by:

    1. 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).

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