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Two-stage energy scheduling framework for multi-microgrid system in market environment

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  • Jani, Ali
  • Jadid, Shahram

Abstract

This paper focuses on the day-ahead and real-time transactive energy markets in the multi-microgrid system. The main purpose is to obtain an optimal schedule for the energy management of microgrids in energy markets. The proposed approach is modeled in a time frame including offline and online classes using a bi-level optimization structure. The first stage considers the day-ahead scheduling of the multi-microgrid system using game theory, where a retail market is established for transactive energy exchange between the microgrids and the microgrid community on an hourly time scale. The second stage focuses on managing the fluctuations of renewables and electricity demand on a shorter time scale and forming a real-time market in the multi-microgrid. The purpose of the second stage implementation is real-time dispatch to minimize the imbalance cost of the microgrids and the microgrid community. The simulation results show that in a cooperative space between neighboring microgrids, the total operating cost is reduced by $61.26. Moreover, this cost reduction reaches $44.05 by moving the battery energy storage systems to the level of microgrids.

Suggested Citation

  • Jani, Ali & Jadid, Shahram, 2023. "Two-stage energy scheduling framework for multi-microgrid system in market environment," Applied Energy, Elsevier, vol. 336(C).
    • Handle: RePEc:eee:appene:v:336:y:2023:i:c:s0306261923000478
    DOI: 10.1016/j.apenergy.2023.120683
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    References listed on IDEAS

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    1. Hakimi, Seyed Mehdi & Hasankhani, Arezoo & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Stochastic planning of a multi-microgrid considering integration of renewable energy resources and real-time electricity market," Applied Energy, Elsevier, vol. 298(C).
    2. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    3. Kong, Xiangyu & Liu, Dehong & Wang, Chengshan & Sun, Fangyuan & Li, Shupeng, 2020. "Optimal operation strategy for interconnected microgrids in market environment considering uncertainty," Applied Energy, Elsevier, vol. 275(C).
    4. Zhang, Bingying & Li, Qiqiang & Wang, Luhao & Feng, Wei, 2018. "Robust optimization for energy transactions in multi-microgrids under uncertainty," Applied Energy, Elsevier, vol. 217(C), pages 346-360.
    5. Gao, Hongjun & Xu, Song & Liu, Youbo & Wang, Lingfeng & Xiang, Yingmeng & Liu, Junyong, 2020. "Decentralized optimal operation model for cooperative microgrids considering renewable energy uncertainties," Applied Energy, Elsevier, vol. 262(C).
    6. Chen, Weidong & Wang, Junnan & Yu, Guanyi & Chen, Jiajia & Hu, Yumeng, 2022. "Research on day-ahead transactions between multi-microgrid based on cooperative game model," Applied Energy, Elsevier, vol. 316(C).
    7. Mansour-Saatloo, Amin & Pezhmani, Yasin & Mirzaei, Mohammad Amin & Mohammadi-Ivatloo, Behnam & Zare, Kazem & Marzband, Mousa & Anvari-Moghaddam, Amjad, 2021. "Robust decentralized optimization of Multi-Microgrids integrated with Power-to-X technologies," Applied Energy, Elsevier, vol. 304(C).
    8. Yamashita, Daniela Yassuda & Vechiu, Ionel & Gaubert, Jean-Paul, 2020. "A review of hierarchical control for building microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 118(C).
    9. Liu, Yixin & Guo, Li & Wang, Chengshan, 2018. "A robust operation-based scheduling optimization for smart distribution networks with multi-microgrids," Applied Energy, Elsevier, vol. 228(C), pages 130-140.
    10. Jani, Ali & Karimi, Hamid & Jadid, Shahram, 2022. "Two-layer stochastic day-ahead and real-time energy management of networked microgrids considering integration of renewable energy resources," Applied Energy, Elsevier, vol. 323(C).
    11. Chang, Weiguang & Dong, Wei & Wang, Yubin & Yang, Qiang, 2022. "Two-stage coordinated operation framework for virtual power plant with aggregated multi-stakeholder microgrids in a deregulated electricity market," Renewable Energy, Elsevier, vol. 199(C), pages 943-956.
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