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Energy Trading and Pricing in Microgrids with Uncertain Energy Supply: A Three-Stage Hierarchical Game Approach

Author

Listed:
  • Kai Ma

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Shubing Hu

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Jie Yang

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
    Current address: Hebei Avenue 438, Qinhuangdao 066004, China)

  • Chunxia Dou

    (School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China)

  • Josep M. Guerrero

    (Department of Energy Technology, Aalborg University, Aalborg 9100, Denmark)

Abstract

This paper studies an energy trading and pricing problem for microgrids with uncertain energy supply. The energy provider with the renewable energy (RE) generation (wind power) determines the energy purchase from the electricity markets and the pricing strategy for consumers to maximize its profit, and then the consumers determine their energy demands to maximize their payoffs. The hierarchical game is established between the energy provider and the consumers. The energy provider is the leader and the consumers are the followers in the hierarchical game. We consider two types of consumers according to their response to the price, i.e., the price-taking consumers and the price-anticipating consumers. We derive the equilibrium point of the hierarchical game through the backward induction method. Comparing the two types of consumers, we study the influence of the types of consumers on the equilibrium point. In particular, the uncertainty of the energy supply from the energy provider is considered. Simulation results show that the energy provider can obtain more profit using the proposed decision-making scheme.

Suggested Citation

  • Kai Ma & Shubing Hu & Jie Yang & Chunxia Dou & Josep M. Guerrero, 2017. "Energy Trading and Pricing in Microgrids with Uncertain Energy Supply: A Three-Stage Hierarchical Game Approach," Energies, MDPI, vol. 10(5), pages 1-16, May.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:5:p:670-:d:98233
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    References listed on IDEAS

    as
    1. Nie, S. & Huang, Charley Z. & Huang, G.H. & Li, Y.P. & Chen, J.P. & Fan, Y.R. & Cheng, G.H., 2016. "Planning renewable energy in electric power system for sustainable development under uncertainty – A case study of Beijing," Applied Energy, Elsevier, vol. 162(C), pages 772-786.
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    Cited by:

    1. Pedro Faria, 2019. "Distributed Energy Resources Management," Energies, MDPI, vol. 12(3), pages 1-3, February.
    2. Matthias Pilz & Luluwah Al-Fagih, 2020. "A Dynamic Game Approach for Demand-Side Management: Scheduling Energy Storage with Forecasting Errors," Dynamic Games and Applications, Springer, vol. 10(4), pages 897-929, December.
    3. Mangirdas Morkunas & Gintaras Cernius & Gintare Giriuniene, 2019. "Assessing Business Risks of Natural Gas Trading Companies: Evidence from GET Baltic," Energies, MDPI, vol. 12(14), pages 1-14, July.

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