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A Stackelberg game approach for energy sharing management of a microgrid providing flexibility to entities

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  • Erol, Özge
  • Başaran Filik, Ümmühan

Abstract

This paper focuses on the energy sharing management of a microgrid including photovoltaic - wind turbine prosumers with energy storage systems, and plug-in electric vehicle charging stations. Motivated by a single-leader multi-follower Stackelberg game approach, the microgrid operator (MGO) is taken as a leader, and prosumers and charging stations act as followers. In similar approaches, buyer and seller roles owned by the prosumers are determined according to their forecasted production and consumption values at the beginning of each time interval, and these roles do not change depending on the obtained final prices for the relevant time interval. In addition, prosumers do not have decision parameters, which they can determine in line with their preferences, in their utility functions. These points significantly limit the prosumers in terms of flexibility, and accordingly, the main aim of this study is to make contributions to these issues. In the proposed Stackelberg game approach, the roles of prosumers can dynamically change as buyers or sellers in response to the pricing policy of the MGO for each time interval. Also, prosumers can take more active roles in the microgrid by shaping their energy consumption strategies with their specified decision parameters. To present the effectiveness of the proposed method, a real-like microgrid simulation is given. The simulation results show that the total profit of the MGO based on the end-game prices has reached approximately twice the total profit based on the utility grid prices. While providing such a significant increase in profit of the MGO, the proposed method reduces the dependency of the microgrid on the utility grid considering the flexibility of the prosumers.

Suggested Citation

  • Erol, Özge & Başaran Filik, Ümmühan, 2022. "A Stackelberg game approach for energy sharing management of a microgrid providing flexibility to entities," Applied Energy, Elsevier, vol. 316(C).
  • Handle: RePEc:eee:appene:v:316:y:2022:i:c:s0306261922003634
    DOI: 10.1016/j.apenergy.2022.118944
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    References listed on IDEAS

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    Cited by:

    1. Yanyue Wang & Guohua Fang & Zhenni Wang, 2022. "The Benefit Realization Mechanism of Pumped Storage Power Plants Based on Multi-Dimensional Regulation and Leader-Follower Decision-Making," Energies, MDPI, vol. 15(16), pages 1-15, August.
    2. Wang, Tonghe & Hua, Haochen & Shi, Tianying & Wang, Rui & Sun, Yizhong & Naidoo, Pathmanathan, 2024. "A bi-level dispatch optimization of multi-microgrid considering green electricity consumption willingness under renewable portfolio standard policy," Applied Energy, Elsevier, vol. 356(C).
    3. Filipe Bandeiras & Álvaro Gomes & Mário Gomes & Paulo Coelho, 2023. "Application and Challenges of Coalitional Game Theory in Power Systems for Sustainable Energy Trading Communities," Energies, MDPI, vol. 16(24), pages 1-42, December.
    4. Wenshuai Bai & Dian Wang & Zhongquan Miao & Xiaorong Sun & Jiabin Yu & Jiping Xu & Yuqing Pan, 2023. "The Design and Application of Microgrid Supervisory System for Commercial Buildings Considering Dynamic Converter Efficiency," Sustainability, MDPI, vol. 15(8), pages 1-21, April.
    5. Zhang, Kaoshe & Gao, Congchong & Zhang, Gang & Xie, Tuo & Li, Hua, 2024. "Electricity and heat sharing strategy of regional comprehensive energy multi-microgrid based on double-layer game," Energy, Elsevier, vol. 293(C).
    6. Li, Zhengmao & Wu, Lei & Xu, Yan & Wang, Luhao & Yang, Nan, 2023. "Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids," Applied Energy, Elsevier, vol. 331(C).
    7. Ting, Zhang & Yunna, Wu, 2024. "Collaborative allocation model and balanced interaction strategy of multi flexible resources in the new power system based on Stackelberg game theory," Renewable Energy, Elsevier, vol. 220(C).

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