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Power management techniques for grid-connected DC microgrids: A comparative evaluation

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  • dos Santos Neto, Pedro J.
  • Barros, Tárcio A.S.
  • Silveira, Joao P.C.
  • Ruppert Filho, Ernesto
  • Vasquez, Juan C.
  • Guerrero, Josep M.

Abstract

DC microgrids are pointed out as a good alternative in distribution systems with integration of renewable energy sources. However, the management of the power flow in the DC microgrid is still an issue under investigation by the scientific community. This article presents a qualitative comparison analysis of power management systems (PMS) for grid-connected DC microgrids. The studied DC microgrid is a basic structure formed by the AC utility grid, a battery energy storage system (BESS), a distributed generator, and the customer loads. Due to the lack of control structures specifically designed to manage grid-connected DC microgrids, a master–slave and an enhanced droop control are proposed as power management techniques. These methods are compared with the conventional droop control, an adaptive droop control based on the battery bank state-of-charge, and a hierarchical control with voltage regulation adapted to operate as PMS. The autonomy of the energy storage system, necessity of communication line, presence of voltage deviation, and inclusion of a battery management system are the most relevant PMS characteristics under analysis. The contribution of this study is a deep comparative evaluation of the PMS control techniques; considering the impact over the DC link voltage, the power flow, and the BESS state-of-charge. Moreover, the performance of each method is evaluated for a distributed generation based on solar and wind renewable energy sources. The experimental results show that the proposed master–slave technique leads to a smooth transition of the power flow inside the DC microgrid, which returns a better performance when compared to the traditional methods. On the other hand, the enhanced droop strategy is a viable alternative to be used when the communication link between power electronic converters is not desired.

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  • dos Santos Neto, Pedro J. & Barros, Tárcio A.S. & Silveira, Joao P.C. & Ruppert Filho, Ernesto & Vasquez, Juan C. & Guerrero, Josep M., 2020. "Power management techniques for grid-connected DC microgrids: A comparative evaluation," Applied Energy, Elsevier, vol. 269(C).
    • Handle: RePEc:eee:appene:v:269:y:2020:i:c:s0306261920305699
    DOI: 10.1016/j.apenergy.2020.115057
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    16. Alberto Arellanes & Ciro Nuñez & Nancy Visairo & Andres A. Valdez-Fernandez, 2022. "An Improvement of Holistic Control Tuning for Reducing Energy Consumption in Seamless Transitions for a BESS Grid-Connected Converter," Energies, MDPI, vol. 15(21), pages 1-23, October.
    17. Xiong, Hualin & Xu, Beibei & Kheav, Kimleng & Luo, Xingqi & Zhang, Xingjin & Patelli, Edoardo & Guo, Pengcheng & Chen, Diyi, 2021. "Multiscale power fluctuation evaluation of a hydro-wind-photovoltaic system," Renewable Energy, Elsevier, vol. 175(C), pages 153-166.
    18. Norouzi, Mohammadali & Aghaei, Jamshid & Pirouzi, Sasan & Niknam, Taher & Fotuhi-Firuzabad, Mahmud & Shafie-khah, Miadreza, 2021. "Hybrid stochastic/robust flexible and reliable scheduling of secure networked microgrids with electric springs and electric vehicles," Applied Energy, Elsevier, vol. 300(C).
    19. Ferahtia, Seydali & Rezk, Hegazy & Abdelkareem, Mohammad Ali & Olabi, A.G., 2022. "Optimal techno-economic energy management strategy for building’s microgrids based bald eagle search optimization algorithm," Applied Energy, Elsevier, vol. 306(PB).
    20. Ensheng Zhao & Yang Han & Hao Zeng & Luqiao Li & Ping Yang & Congling Wang & Amr S. Zalhaf, 2022. "Accurate Peer-to-Peer Hierarchical Control Method for Hybrid DC Microgrid Clusters," Energies, MDPI, vol. 16(1), pages 1-27, December.

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