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Coordination Strategy for Optimal Scheduling of Multiple Microgrids Based on Hierarchical System

Author

Listed:
  • Won-Poong Lee

    (Department of Electrical Engineering, Inha University, 100, Inha-ro, Nam-gu, Incheon 22212, Korea)

  • Jin-Young Choi

    (LG CNS, 28F, FKI Tower, 24, Yeoui-daero, Yeongdeungpo-gu, Seoul 07320, Korea)

  • Dong-Jun Won

    (Department of Electrical Engineering, Inha University, 100, Inha-ro, Nam-gu, Incheon 22212, Korea)

Abstract

Research on the operation of the multiple microgrid (MMG) has been increasing as the power system is operated through the microgrid. Some of the studies related to MMG have introduced various operation strategies by introducing concepts such as power sharing and power trading for power exchange between microgrids. In this paper, a strategy for obtaining optimal scheduling of MMG systems with power sharing through coordination among microgrids that have no cost function of generation units is proposed. There are microgrid-energy management systems (MG-EMSs) in the lower level that determine individual schedules for each microgrid in a hierarchical system. In the upper level, the microgrid of microgrids center (MoMC) implements the coordination among microgrids. In order to achieve the optimal operation of the entire system, MoMC calculates the amount of power sharing based on a predetermined limit value and allocates the command for coordination to each MG-EMS. MG-EMS changes the individual schedule based on the command. These processes are repeatedly performed, and when the change of the total cost becomes smaller than a specified size, the process is terminated and the schedule is determined. The advantages of the proposed algorithm are as follows. (1) It is a power sharing strategy of multiple microgrids considering multiple feeder structures as well as a single feeder structure for minimizing the operation cost of the entire system; (2) it is a power sharing strategy between microgrids that can be applied in a microgrid where only units that do not have a cost function exist; (3) since it is the optimization of the distributed form, the computation time decreases sharply compared with the one performed at the central center. The verification of the proposed algorithm was performed through MATLAB.

Suggested Citation

  • Won-Poong Lee & Jin-Young Choi & Dong-Jun Won, 2017. "Coordination Strategy for Optimal Scheduling of Multiple Microgrids Based on Hierarchical System," Energies, MDPI, vol. 10(9), pages 1-18, September.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1336-:d:110972
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    Citations

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    Cited by:

    1. Pan Wu & Wentao Huang & Nengling Tai & Zhoujun Ma & Xiaodong Zheng & Yong Zhang, 2019. "A Multi-Layer Coordinated Control Scheme to Improve the Operation Friendliness of Grid-Connected Multiple Microgrids," Energies, MDPI, vol. 12(2), pages 1-21, January.
    2. Maarten Wolsink, 2020. "Framing in Renewable Energy Policies: A Glossary," Energies, MDPI, vol. 13(11), pages 1-31, June.
    3. Jingfeng Chen & Ping Yang & Jiajun Peng & Yuqi Huang & Yaosheng Chen & Zhiji Zeng, 2018. "An Improved Multi-Timescale Coordinated Control Strategy for Stand-Alone Microgrid with Hybrid Energy Storage System," Energies, MDPI, vol. 11(8), pages 1-23, August.
    4. Meryem Hamidi & Abdelhadi Raihani & Omar Bouattane, 2023. "Sustainable Intelligent Energy Management System for Microgrid Using Multi-Agent Systems: A Case Study," Sustainability, MDPI, vol. 15(16), pages 1-19, August.
    5. Nawaz, Arshad & Zhou, Min & Wu, Jing & Long, Chengnian, 2022. "A comprehensive review on energy management, demand response, and coordination schemes utilization in multi-microgrids network," Applied Energy, Elsevier, vol. 323(C).
    6. Hong-Chao Gao & Joon-Ho Choi & Sang-Yun Yun & Seon-Ju Ahn, 2020. "A New Power Sharing Scheme of Multiple Microgrids and an Iterative Pairing-Based Scheduling Method," Energies, MDPI, vol. 13(7), pages 1-20, April.
    7. Li, Longxi & Cao, Xilin & Wang, Peng, 2021. "Optimal coordination strategy for multiple distributed energy systems considering supply, demand, and price uncertainties," Energy, Elsevier, vol. 227(C).
    8. Giuseppe Barone & Giovanni Brusco & Alessandro Burgio & Daniele Menniti & Anna Pinnarelli & Michele Motta & Nicola Sorrentino & Pasquale Vizza, 2018. "A Real-Life Application of a Smart User Network," Energies, MDPI, vol. 11(12), pages 1-23, December.

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