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A New Power Sharing Scheme of Multiple Microgrids and an Iterative Pairing-Based Scheduling Method

Author

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  • Hong-Chao Gao

    (State Key Lab of Power Systems, Department of Electrical Engineering, Tsinghua University, Beijing 100084, China)

  • Joon-Ho Choi

    (Department of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, Korea)

  • Sang-Yun Yun

    (Department of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, Korea)

  • Seon-Ju Ahn

    (Department of Electrical Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju 61186, Korea)

Abstract

As the numbers of microgrids (MGs) and prosumers are increasing, many research efforts are proposing various power sharing schemes for multiple MGs (MMGs). Power sharing between MMGs can reduce the investment and operating costs of MGs. However, since MGs exchange power through distribution lines, this may have an adverse effect on the utility, such as an increase in peak demand, and cause local overcurrent issues. Therefore, this paper proposes a power sharing scheme that is beneficial to both MGs and the utility. This research assumes that in an MG, the energy storage system (ESS) is the major controllable resource. In the proposed power sharing scheme, an MG that sends power should discharge at least as much power from the ESS as the power it sends to other MGs, in order to actually decrease the total system demand. With these assumptions, methods for determining the power sharing schedule are proposed. Firstly, a mixed integer linear programming (MILP)-based centralized approach is proposed. Although this can provide the optimal power sharing solution, in practice, this method is very difficult to apply, due to the large calculation burden. To overcome the significant calculation burden of the centralized optimization method, a new method for determining the power sharing schedule is proposed. In this approach, the amount of power sharing is assumed to be a multiple of a unit amount, and the final power sharing schedule is determined by iteratively finding the best MG pair that exchange this unit amount. Simulation with a five MG scenario is used to test the proposed power sharing scheme and the scheduling algorithm in terms of a reduction in the operating cost of MGs, the peak demand of utility, and the calculation burden. In addition, the interrelationship between power sharing and the system loss is analyzed when MGs exchange power through the utility network.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:7:p:1605-:d:339890
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    References listed on IDEAS

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    1. 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.
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    3. Frederik Plewnia, 2019. "The Energy System and the Sharing Economy: Interfaces and Overlaps and What to Learn from Them," Energies, MDPI, vol. 12(3), pages 1-17, January.
    4. Boram Kim & Sunghwan Bae & Hongseok Kim, 2017. "Optimal Energy Scheduling and Transaction Mechanism for Multiple Microgrids," Energies, MDPI, vol. 10(4), pages 1-17, April.
    5. Tadahiro Taniguchi & Koki Kawasaki & Yoshiro Fukui & Tomohiro Takata & Shiro Yano, 2015. "Automated Linear Function Submission-Based Double Auction as Bottom-up Real-Time Pricing in a Regional Prosumers’ Electricity Network," Energies, MDPI, vol. 8(7), pages 1-26, July.
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    7. Hong-Chao Gao & Joon-Ho Choi & Sang-Yun Yun & Hak-Ju Lee & Seon-Ju Ahn, 2018. "Optimal Scheduling and Real-Time Control Schemes of Battery Energy Storage System for Microgrids Considering Contract Demand and Forecast Uncertainty," Energies, MDPI, vol. 11(6), pages 1-15, May.
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    Cited by:

    1. Maarten Wolsink, 2020. "Framing in Renewable Energy Policies: A Glossary," Energies, MDPI, vol. 13(11), pages 1-31, June.

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