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Hierarchical Multi-Communities Energy Sharing Management with Electric Vehicle Integration

Author

Listed:
  • Ruengwit Khwanrit

    (School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi 923-1292, Ishikawa, Japan
    School of Information, Computer, and Communication Technology (ICT), Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang 12120, Pathum Thani, Thailand)

  • Saher Javaid

    (School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi 923-1292, Ishikawa, Japan)

  • Yuto Lim

    (School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi 923-1292, Ishikawa, Japan)

  • Chalie Charoenlarpnopparut

    (School of Information, Computer, and Communication Technology (ICT), Sirindhorn International Institute of Technology, Thammasat University, Khlong Luang 12120, Pathum Thani, Thailand)

  • Yasuo Tan

    (School of Information Science, Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi 923-1292, Ishikawa, Japan)

Abstract

The widespread adoption of Electric Vehicles (EVs) in the smart grid is transforming the traditional grid into a more complex system. EVs have the ability to both charge and discharge, acting as loads that draw high power and sources that inject energy back into the grid. Consequently, energy sharing and management within smart grid communities integrated with EVs have become interesting aspects to study in order to efficiently utilize this energy. However, most existing research focuses solely on energy sharing within single communities, utilizing homogeneous energy profiles and neglecting the potential of heterogeneous energy across multiple communities. EVs also possess the capability to travel to different places and communities, where they can engage in energy sharing with areas that have varying load profiles and prices. In this work, a novel three-level energy sharing management approach is proposed for a multiple community system integrating movable energy storage such as EVs. This model involves three main entities: the Utility Company (UC), Community Energy Aggregator (CEA), and EVs. The energy sharing problem is formulated as a Stackelberg game, with all entities striving to maximize their utility through optimal strategies, including pricing, energy demand, or supply. The proposed model is validated through comparison with typical human charging behavior, as well as single- and multiple-community two-level game models. The findings reveal that the proposed model successfully optimizes pricing and energy strategies, significantly lowering the peak-to-average ratio and smoothing the overall energy profile.

Suggested Citation

  • Ruengwit Khwanrit & Saher Javaid & Yuto Lim & Chalie Charoenlarpnopparut & Yasuo Tan, 2025. "Hierarchical Multi-Communities Energy Sharing Management with Electric Vehicle Integration," Energies, MDPI, vol. 18(2), pages 1-26, January.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:2:p:393-:d:1569436
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    References listed on IDEAS

    as
    1. Ruengwit Khwanrit & Saher Javaid & Yuto Lim & Chalie Charoenlarpnopparut & Yasuo Tan, 2024. "Optimal Vehicle-to-Grid Strategies for Energy Sharing Management Using Electric School Buses," Energies, MDPI, vol. 17(16), pages 1-25, August.
    2. Bruno Canizes & João Soares & Zita Vale & Juan M. Corchado, 2019. "Optimal Distribution Grid Operation Using DLMP-Based Pricing for Electric Vehicle Charging Infrastructure in a Smart City," Energies, MDPI, vol. 12(4), pages 1-40, February.
    3. Zhang, Chenghua & Wu, Jianzhong & Zhou, Yue & Cheng, Meng & Long, Chao, 2018. "Peer-to-Peer energy trading in a Microgrid," Applied Energy, Elsevier, vol. 220(C), pages 1-12.
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