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A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach

Author

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  • Tengfei Ma

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China
    Electric Power Research Institute of China, Haidian District, Beijing 100085, China)

  • Junyong Wu

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Liangliang Hao

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Huaguang Yan

    (Electric Power Research Institute of China, Haidian District, Beijing 100085, China)

  • Dezhi Li

    (Electric Power Research Institute of China, Haidian District, Beijing 100085, China)

Abstract

This paper proposes a real-time pricing scheme for the demand response management between one energy provider and multiple energy hub operators. A promising energy trading scenario has been designed for the near future integrated energy system. The Stackelberg game approach was employed to capture the interactions between the energy provider (leader) and energy consumers (follower). A distributed algorithm was proposed to derive the Stackelberg equilibrium, then, the best strategies for the energy provider and each energy hub operator were explored in order to maximize their benefits. Simulation results showed that the proposed method can balance the energy supply and demand, improve the payoffs for all players, as well as smooth the aggregated load profiles of all energy consumers.

Suggested Citation

  • Tengfei Ma & Junyong Wu & Liangliang Hao & Huaguang Yan & Dezhi Li, 2018. "A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach," Energies, MDPI, vol. 11(10), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2858-:d:177397
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    References listed on IDEAS

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    3. Li, Songrui & Zhang, Lihui & Nie, Lei & Wang, Jianing, 2022. "Trading strategy and benefit optimization of load aggregators in integrated energy systems considering integrated demand response: A hierarchical Stackelberg game," Energy, Elsevier, vol. 249(C).
    4. Tomas Baležentis & Dalia Štreimikienė, 2019. "Sustainability in the Electricity Sector through Advanced Technologies: Energy Mix Transition and Smart Grid Technology in China," Energies, MDPI, vol. 12(6), pages 1-21, March.
    5. Qi Zhang & Shaohua Zhang & Xian Wang & Xue Li & Lei Wu, 2020. "Conditional-Robust-Profit-Based Optimization Model for Electricity Retailers with Shiftable Demand," Energies, MDPI, vol. 13(6), pages 1-19, March.
    6. Lang Zhao & Yuan Zeng & Zhidong Wang & Yizheng Li & Dong Peng & Yao Wang & Xueying Wang, 2023. "Robust Optimal Scheduling of Integrated Energy Systems Considering the Uncertainty of Power Supply and Load in the Power Market," Energies, MDPI, vol. 16(14), pages 1-14, July.
    7. Renato Ferrero & Mario Collotta & Maria Victoria Bueno-Delgado & Hsing-Chung Chen, 2020. "Smart Management Energy Systems in Industry 4.0," Energies, MDPI, vol. 13(2), pages 1-3, January.
    8. Wang, Haiyang & Zhang, Chenghui & Li, Ke & Liu, Shuai & Li, Shuzhen & Wang, Yu, 2021. "Distributed coordinative transaction of a community integrated energy system based on a tri-level game model," Applied Energy, Elsevier, vol. 295(C).
    9. Shijun Chen & Huwei Chen & Shanhe Jiang, 2019. "Optimal Decision-Making to Charge Electric Vehicles in Heterogeneous Networks: Stackelberg Game Approach," Energies, MDPI, vol. 12(2), pages 1-20, January.
    10. Antonio Pepiciello & Alfredo Vaccaro & Mario Mañana, 2019. "Robust Optimization of Energy Hubs Operation Based on Extended Affine Arithmetic," Energies, MDPI, vol. 12(12), pages 1-15, June.
    11. Nicholas Moehle & Enzo Busseti & Stephen Boyd & Matt Wytock, 2019. "Dynamic Energy Management," Papers 1903.06230, arXiv.org.
    12. Aviad Navon & Gefen Ben Yosef & Ram Machlev & Shmuel Shapira & Nilanjan Roy Chowdhury & Juri Belikov & Ariel Orda & Yoash Levron, 2020. "Applications of Game Theory to Design and Operation of Modern Power Systems: A Comprehensive Review," Energies, MDPI, vol. 13(15), pages 1-35, August.
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    14. Jiang, Yanni & Zhou, Kaile & Lu, Xinhui & Yang, Shanlin, 2020. "Electricity trading pricing among prosumers with game theory-based model in energy blockchain environment," Applied Energy, Elsevier, vol. 271(C).

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