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How can the dynamic game be integrated into blockchain-based distributed energy resources multi-agent transactions for decision-making?

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  • Wang, Hao-ran
  • Feng, Tian-tian
  • Xiong, Wei

Abstract

Distributed energy resources not only change the energy supply modes but also have great potential in energy transformation. There are some problems in distributed energy trading, such as high transaction frequency, small transaction volume, high operation cost, lack of information supervision and so on. The openness, transparency, tamper-proof and automatic execution of smart contracts of blockchain technology are consistent with the transaction demand of distributed energy. Therefore, this paper proposes a multi-agent transaction model of distributed energy based on blockchain. First, the peer to peer transaction mode and transaction process are analysed. Second, a multi-agent dynamic Stackelberg game is launched. It takes distributed generation owners, energy storage companies and a grid corporation as leaders to conduct power bidding. Third, with consumers as followers, the time of use tariff bidding strategy was solved. The obtained results reveal that distributed energy resources are essential in the energy supply of carbon neutrality, which also determines the complementary relationship between a grid corporation and distributed generation owners. The two agents work together to exert effectiveness for the new power system. There is a large space for energy storage companies to improve, and consumers show a trend of off-peak power consumption.

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  • Wang, Hao-ran & Feng, Tian-tian & Xiong, Wei, 2022. "How can the dynamic game be integrated into blockchain-based distributed energy resources multi-agent transactions for decision-making?," Energy, Elsevier, vol. 254(PB).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pb:s036054422201221x
    DOI: 10.1016/j.energy.2022.124318
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    2. Zhou, Yuekuan & Lund, Peter D., 2023. "Peer-to-peer energy sharing and trading of renewable energy in smart communities ─ trading pricing models, decision-making and agent-based collaboration," Renewable Energy, Elsevier, vol. 207(C), pages 177-193.
    3. Bio Gassi, Karim & Baysal, Mustafa, 2023. "Improving real-time energy decision-making model with an actor-critic agent in modern microgrids with energy storage devices," Energy, Elsevier, vol. 263(PE).
    4. Feng, Yuanhao & Feng, Donghan & Zhou, Yun & Xu, Shaolun, 2024. "Generation side strategy and user side cost based on equilibrium analysis of the power market under the reliability option," Energy, Elsevier, vol. 287(C).

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