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An Optimal Scheduling Method for Multi-Energy Hub Systems Using Game Theory

Author

Listed:
  • Yu Huang

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Weiting Zhang

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Kai Yang

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Weizhen Hou

    (Department of Automation, North China Electric Power University, Baoding 071003, China)

  • Yiran Huang

    (Department of Engineering Electronics and Communication Engineering, North China Electric Power University, Baoding 071003, China)

Abstract

The optimal scheduling of multi-energy hub systems plays an important role in the safety, stability, and economic operation of the system. However, due to the strong uncertainty of renewable energy access, serious coupling, and the interaction among energy hubs of multi-energy hub systems, it is difficult for the traditional optimal scheduling method to solve these problems. Therefore, game theory was used to solve the optimal scheduling problem of multi-energy hub systems. According to the internal connection mode and energy conversion relationship of energy hubs, along with the competitive and cooperative relationship between multi-energy hubs, the game theoretic optimal scheduling model of the multi-energy hub system was established. Then, two cases and 50 groups of wind speed series were used to test the robustness of the proposed method. Simulation results show that the total power injection is −16,805.8, 104.1847, and −865.561 and the natural gas injection is 46,046.81, 27,727.65, and 63,039.54 in spring/autumn, summer, and winter, respectively, which is consistent with the characteristics of the four seasons. Furthermore, the optimal scheduling method using game theory has a strong robustness in multi-energy hub systems.

Suggested Citation

  • Yu Huang & Weiting Zhang & Kai Yang & Weizhen Hou & Yiran Huang, 2019. "An Optimal Scheduling Method for Multi-Energy Hub Systems Using Game Theory," Energies, MDPI, vol. 12(12), pages 1-20, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:12:p:2270-:d:239591
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    References listed on IDEAS

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    Cited by:

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    2. Mohammad Hemmati & Mehdi Abapour & Behnam Mohammadi-Ivatloo & Amjad Anvari-Moghaddam, 2020. "Optimal Operation of Integrated Electrical and Natural Gas Networks with a Focus on Distributed Energy Hub Systems," Sustainability, MDPI, vol. 12(20), pages 1-22, October.
    3. Sobhani, Seyed Omid & Sheykhha, Siamak & Madlener, Reinhard, 2020. "An integrated two-level demand-side management game applied to smart energy hubs with storage," Energy, Elsevier, vol. 206(C).
    4. Nima Mirzaei Alavijeh & David Steen & Zack Norwood & Le Anh Tuan & Christos Agathokleous, 2020. "Cost-Effectiveness of Carbon Emission Abatement Strategies for a Local Multi-Energy System—A Case Study of Chalmers University of Technology Campus," Energies, MDPI, vol. 13(7), pages 1-23, April.
    5. Alaa Farah & Hamdy Hassan & Alaaeldin M. Abdelshafy & Abdelfatah M. Mohamed, 2020. "Optimal Scheduling of Hybrid Multi-Carrier System Feeding Electrical/Thermal Load Based on Particle Swarm Algorithm," Sustainability, MDPI, vol. 12(11), pages 1-21, June.

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