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An Optimization Strategy for EV-Integrated Microgrids Considering Peer-to-Peer Transactions

Author

Listed:
  • Sen Tian

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Qian Xiao

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China
    State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China)

  • Tianxiang Li

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Yu Jin

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Yunfei Mu

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Hongjie Jia

    (Key Laboratory of Smart Grid of Ministry of Education, Tianjin University, Tianjin 300072, China)

  • Wenhua Li

    (State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China)

  • Remus Teodorescu

    (Department of Energy Technology, Aalborg University, 9220 Aalborg, Denmark)

  • Josep M. Guerrero

    (Department of Electronic Engineering, Technical University of Catalonia, 08019 Barcelona, Spain)

Abstract

The scale of electric vehicles (EVs) in microgrids is growing prominently. However, the stochasticity of EV charging behavior poses formidable obstacles to exploring their dispatch potential. To solve this issue, an optimization strategy for EV-integrated microgrids considering peer-to-peer (P2P) transactions has been proposed in this paper. This research strategy contributes to the sustainable development of microgrids under large-scale EV integration. Firstly, a novel cooperative operation framework considering P2P transactions is established, in which the impact factors of EV charging are regarded to simulate its stochasticity and the energy trading process of the EV-integrated microgrid participating in P2P transactions is defined. Secondly, cost models for the EV-integrated microgrid are established. Thirdly, a three-stage optimization strategy is proposed to simplify the solving process. It transforms the scheduling problem into three solvable subproblems and restructures them with Lagrangian relaxation. Finally, case studies demonstrate that the proposed strategy optimizes EV load distribution, reduces the overall operational cost of the EV-integrated microgrid, and enhances the economic efficiency of each microgrid participating in P2P transactions.

Suggested Citation

  • Sen Tian & Qian Xiao & Tianxiang Li & Yu Jin & Yunfei Mu & Hongjie Jia & Wenhua Li & Remus Teodorescu & Josep M. Guerrero, 2024. "An Optimization Strategy for EV-Integrated Microgrids Considering Peer-to-Peer Transactions," Sustainability, MDPI, vol. 16(20), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:20:p:8955-:d:1499905
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    References listed on IDEAS

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    1. Zhao, Yang & Jiang, Ziyue & Chen, Xinyu & Liu, Peng & Peng, Tianduo & Shu, Zhan, 2023. "Toward environmental sustainability: data-driven analysis of energy use patterns and load profiles for urban electric vehicle fleets," Energy, Elsevier, vol. 285(C).
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    Cited by:

    1. Liu, Zhi-Feng & Liu, You-Yuan & Jia, Hong-Jie & Jin, Xiao-Long & Liu, Tong-Hui & Wu, Yu-Ze, 2025. "Bi-level energy co-optimization of regional integrated energy system with electric vehicle to generalized-energy conversion framework and flexible hydrogen-blended gas strategy," Applied Energy, Elsevier, vol. 390(C).

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