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Coordinated Energy Management of MMC-Based DC Microgrids using Particle Swarm Optimization

Authors

  • Rana Saeed Ahmad

    Department of Electrical Engineering, Bahria University Karachi Campus, Pakistan
    Author

  • Haroon Rasheed

    Department of Electrical Engineering, Bahria University Karachi Campus, Pakistan
    Author

DOI:

https://doi.org/10.22581/muet1982.0587

Keywords:

Modular Multilevel Converter, DC Microgrid, Particle Swarm Optimization, Energy Management, Power Loss Minimization, Converter Coordination

Abstract

The increased adoption of renewable energy sources in DC microgrids has improved the sustainability and has also posed some challenges associated with the effective coordination of converters and minimization of power losses. Uncoordinated operation of the Modular Multilevel Converters (MMCs) can result in higher conduction and switching losses especially those in high-voltage DC applications. The overall goal of this paper is to work out an integrated energy management system that reduces the overall converter losses and provides equal work of MMC-based DC microgrids. A Particle Swarm Optimization (PSO)-based approach is suggested to meet this goal by optimal distribution of converter output currents and submodule utilization ratio within the operating limits set in steady-state operation. An equivalent resistance converter loss model, which includes a constant loss element, constant loss elements and factors of module utilization are created and integrated into the optimization problem. The suggested framework is run in MATLAB and tested in an experimental circuit of a DC micro-grid including grid, photovoltaic, and battery-interfaced MMCs. It has been shown in simulation that the PSO algorithm converges rapidly and total system losses are reduced by about 2.28 kW over the conventional uncoordinated operation, but does not decrease the DC bus power balance or violate operational limits. The findings verify that converter-aware optimization has the potential of a great contribution towards energy efficiency and coordination of MMC-based DC microgrids, and forms a computationally-efficient basis on which to build future extensions to adaptive and decentralized approaches to control.

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References

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Published

2026-07-01

Issue

Vol. 45 No. 3 (2026): July Issue

Section

Articles

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Copyright (c) 2026 Mehran University Research Journal of Engineering and Technology

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How to Cite

Coordinated Energy Management of MMC-Based DC Microgrids using Particle Swarm Optimization. (2026). Mehran University Research Journal of Engineering and Technology, 45(3), 64-77. https://doi.org/10.22581/muet1982.0587

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