Skip to main content

Research Repository

Advanced Search

Model predictive control of consensus-based energy management system for DC microgrid

Ali, Syed Umaid; Waqar, Asad; Aamir, Muhammad; Qaisar, Saeed Mian; Iqbal, Jamshed


Syed Umaid Ali

Asad Waqar

Muhammad Aamir

Saeed Mian Qaisar


The increasing deployment and exploitation of distributed renewable energy source (DRES) units and battery energy storage systems (BESS) in DC microgrids lead to a promising research field currently. Individual DRES and BESS controllers can operate as grid-forming (GFM) or grid-feeding (GFE) units independently, depending on the microgrid operational requirements. In standalone mode, at least one controller should operate as a GFM unit. In grid-connected mode, all the controllers may operate as GFE units. This article proposes a consensus-based energy management system based upon Model Predictive Control (MPC) for DRES and BESS individual controllers to operate in both configurations (GFM or GFE). Energy management system determines the mode of power flow based on the amount of generated power, load power, solar irradiance, wind speed, rated power of every DG, and state of charge (SOC) of BESS. Based on selection of power flow mode, the role of DRES and BESS individual controllers to operate as GFM or GFE units, is decided. MPC hybrid cost function with auto-tuning weighing factors will enable DRES and BESS converters to switch between GFM and GFE. In this paper, a single hybrid cost function has been proposed for both GFM and GFE. The performance of the proposed energy management system has been validated on an EU low voltage benchmark DC microgrid by MATLAB/ SIMULINK simulation and also compared with Proportional Integral (PI) & Sliding Mode Control (SMC) technique. It has been noted that as compared to PI & SMC, MPC technique exhibits settling time of less than 1μsec and 5% overshoot.


Ali, S. U., Waqar, A., Aamir, M., Qaisar, S. M., & Iqbal, J. (2023). Model predictive control of consensus-based energy management system for DC microgrid. PLoS ONE, 18(1), Article e0278110.

Journal Article Type Article
Acceptance Date Nov 10, 2022
Online Publication Date Jan 20, 2023
Publication Date Jan 20, 2023
Deposit Date Nov 12, 2022
Publicly Available Date Jan 23, 2023
Journal PLoS ONE
Print ISSN 1932-6203
Electronic ISSN 1932-6203
Publisher Public Library of Science
Peer Reviewed Peer Reviewed
Volume 18
Issue 1
Article Number e0278110
Public URL


Published article (3.8 Mb)

Publisher Licence URL

Copyright Statement
Copyright: © 2023 Ali et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

You might also like

Downloadable Citations