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A novel distributed optimal power sharing method for radial dc microgrids with different distributed energy sources

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  • Asad, R.
  • Kazemi, A.

Abstract

DC microgrids will be an important part of the future electrical power systems, i.e., smart grids. Similar to the other power systems, one of the important issues of dc microgrids is the fulfillment of the optimal power sharing. In this paper, a practical, modular, robust, highly reliable, autonomous, distributed, optimal power sharing method, namely the ODCPS (optimal dc power sharing) method, is proposed for radial dc microgrids with different numbers of distributed energy sources. The presented power sharing method inherently considers the power loss in its optimization process. Furthermore, the ODCPS method necessitates the least telecommunication. Here, to determine the proper amounts of the parameters of the proposed power sharing method, a novel technique calculating the nodal prices in radial dc microgrids is also presented. Although the success of the ODCPS method is demonstrated through the analytical analyses carried out in this paper, finally, the remarkable performance of the proposed power sharing method is described by the simulation results too.

Suggested Citation

  • Asad, R. & Kazemi, A., 2014. "A novel distributed optimal power sharing method for radial dc microgrids with different distributed energy sources," Energy, Elsevier, vol. 72(C), pages 291-299.
    • Handle: RePEc:eee:energy:v:72:y:2014:i:c:p:291-299
    DOI: 10.1016/j.energy.2014.05.036
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    Cited by:

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    2. Akter, M.N. & Mahmud, M.A. & Haque, M.E. & Oo, Amanullah M.T., 2020. "An optimal distributed energy management scheme for solving transactive energy sharing problems in residential microgrids," Applied Energy, Elsevier, vol. 270(C).
    3. Maria Fotopoulou & Dimitrios Rakopoulos & Dimitrios Trigkas & Fotis Stergiopoulos & Orestis Blanas & Spyros Voutetakis, 2021. "State of the Art of Low and Medium Voltage Direct Current (DC) Microgrids," Energies, MDPI, vol. 14(18), pages 1-27, September.
    4. Burgio, Alessandro & Menniti, Daniele & Sorrentino, Nicola & Pinnarelli, Anna & Motta, Michele, 2018. "A compact nanogrid for home applications with a behaviour-tree-based central controller," Applied Energy, Elsevier, vol. 225(C), pages 14-26.
    5. Monadi, Mehdi & Zamani, M. Amin & Koch-Ciobotaru, Cosmin & Candela, Jose Ignacio & Rodriguez, Pedro, 2016. "A communication-assisted protection scheme for direct-current distribution networks," Energy, Elsevier, vol. 109(C), pages 578-591.
    6. Kitson, J. & Williamson, S.J. & Harper, P.W. & McMahon, C.A. & Rosenberg, G. & Tierney, M.J. & Bell, K. & Gautam, B., 2018. "Modelling of an expandable, reconfigurable, renewable DC microgrid for off-grid communities," Energy, Elsevier, vol. 160(C), pages 142-153.
    7. Kang, Wenfa & Chen, Minyou & Lai, Wei & Luo, Yanyu, 2021. "Distributed real-time power management for virtual energy storage systems using dynamic price," Energy, Elsevier, vol. 216(C).
    8. Burmester, Daniel & Rayudu, Ramesh & Seah, Winston & Akinyele, Daniel, 2017. "A review of nanogrid topologies and technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 760-775.
    9. Li, Jianwei & Xiong, Rui & Yang, Qingqing & Liang, Fei & Zhang, Min & Yuan, Weijia, 2017. "Design/test of a hybrid energy storage system for primary frequency control using a dynamic droop method in an isolated microgrid power system," Applied Energy, Elsevier, vol. 201(C), pages 257-269.
    10. Li, Jianwei & Yang, Qingqing & Robinson, Francis. & Liang, Fei & Zhang, Min & Yuan, Weijia, 2017. "Design and test of a new droop control algorithm for a SMES/battery hybrid energy storage system," Energy, Elsevier, vol. 118(C), pages 1110-1122.
    11. Wang, Jianxiao & Zhong, Haiwang & Xia, Qing & Kang, Chongqing, 2017. "Optimal transmission conversion from alternating current to high voltage direct current transmission systems for limiting short circuit currents," Energy, Elsevier, vol. 118(C), pages 545-555.

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