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Game-theoretic multi-energy trading framework for strategic biogas-solar renewable energy provider with heterogeneous consumers

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  • Hua, Zhihao
  • Li, Jiayong
  • Zhou, Bin
  • Or, Siu Wing
  • Chan, Ka Wing
  • Meng, Yunfan

Abstract

This paper proposes a game-theoretic multi-energy trading framework for a biogas-solar renewable energy provider with heterogeneous consumers to promote the efficient utilization of local renewable energy resources. Within the proposed framework, the multi-energy provider utilizes biogas-solar complementarities to enhance the operational flexibility for electricity, biogas, and heat energy supplies, and consumers are enabled to actively participate in demand response under different multi-energy prices from the provider and UCs. A multi-energy pricing model is then proposed based on the Stackelberg game to interactively and dynamically determine the internal trading prices for optimal multi-energy trading between the provider and consumers. Furthermore, a bi-level optimization method is formulated to solve the Stackelberg game-based multi-energy trading problem to maximize the provider's profit at the upper level and the welfare of each consumer at the lower level. Case studies show that the provider's profit is improved by 33.7% using the proposed scheme compared with the benchmark scheme, and meanwhile the average welfare of consumers for consuming biogas and electricity are approximately 3.0 and 1.4 times greater than those using the benchmark scheme.

Suggested Citation

  • Hua, Zhihao & Li, Jiayong & Zhou, Bin & Or, Siu Wing & Chan, Ka Wing & Meng, Yunfan, 2022. "Game-theoretic multi-energy trading framework for strategic biogas-solar renewable energy provider with heterogeneous consumers," Energy, Elsevier, vol. 260(C).
  • Handle: RePEc:eee:energy:v:260:y:2022:i:c:s0360544222019156
    DOI: 10.1016/j.energy.2022.125018
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    2. Wu, Qian & Song, Qiankun & He, Xing & Chen, Guo & Huang, Tingwen, 2024. "Distributed peer-to-peer energy trading framework with manufacturing assembly process and uncertain renewable energy plants in multi-industrial micro-grids," Energy, Elsevier, vol. 302(C).
    3. Chen, Yuzhu & Guo, Weimin & Du, Na & Yang, Kun & Wang, Jiangjiang, 2024. "Master slave game-based optimization of an off-grid combined cooling and power system coupled with solar thermal and photovoltaics considering carbon cost allocation," Renewable Energy, Elsevier, vol. 229(C).
    4. Yan, Haoran & Hou, Hongjuan & Deng, Min & Si, Lengge & Wang, Xi & Hu, Eric & Zhou, Rhonin, 2024. "Stackelberg game theory based model to guide users’ energy use behavior, with the consideration of flexible resources and consumer psychology, for an integrated energy system," Energy, Elsevier, vol. 288(C).
    5. 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).
    6. Yang, Yulong & Zhao, Yang & Yan, Gangui & Mu, Gang & Chen, Zhe, 2024. "Real time aggregation control of P2H loads in a virtual power plant based on a multi-period stackelberg game," Energy, Elsevier, vol. 303(C).

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