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Multi-game optimization operation strategy for integrated energy system considering spatiotemporal correlation of renewable energy

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  • Xu, Xun
  • Shao, Zhenguo
  • Chen, Feixiong
  • Cheng, Guoyang

Abstract

With the increasing diversity of market entities in the integrated energy system (IES), the interests of multiple entities become complex and variable, leading to disorganized competition among entities in the trading market. Therefore, this paper presents an optimal operation strategy for IES employing a multi-game with tri-level transactions. Firstly, a tri-level IES framework is established with the energy production provider alliance, energy sales agent, and energy user agents as the main entities. Secondly, to handle the uncertainty of renewable energy, a MD-K2 dynamic bayesian network method describing the spatiotemporal correlation of wind and photovoltaic is proposed, and generates probabilistic scenarios. Then, a tri-level multi-game optimization operation model is constructed considering multi-dimensional transactions and demand responses, and is proved to achieve the game equilibrium. Finally, the tri-level model is converted into bi-level mixed-integer linear programming (BMILP) problem, which is solved by a bisection-based distributed iterative algorithm. The simulation results indicate that the optimization strategy improves the interests of tri-level entities and promotes fair distribution of cooperative benefits among alliance members.

Suggested Citation

  • Xu, Xun & Shao, Zhenguo & Chen, Feixiong & Cheng, Guoyang, 2024. "Multi-game optimization operation strategy for integrated energy system considering spatiotemporal correlation of renewable energy," Energy, Elsevier, vol. 303(C).
    • Handle: RePEc:eee:energy:v:303:y:2024:i:c:s0360544224015470
    DOI: 10.1016/j.energy.2024.131774
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