| Issue |
EPJ Web Conf.
Volume 330, 2025
The 5th International Conference on Electrical Sciences and Technologies in the Maghreb (CISTEM 2024)
|
|
|---|---|---|
| Article Number | 02004 | |
| Number of page(s) | 5 | |
| Section | Advanced Control for Electric Machines and Drives | |
| DOI | https://doi.org/10.1051/epjconf/202533002004 | |
| Published online | 30 June 2025 | |
https://doi.org/10.1051/epjconf/202533002004
Grid Active Power Support Using Green DC Microgrid Based on Super Twisting Control Algorithm
1 High National School of Arts and Crafts (ENSAM), Mohammed V University in Rabat, Rabat, Morocco
2 High National School for Computer Science and Systems Analysis (ENSIAS), Mohammed V University in Rabat, Rabat, Morocco
* e-mail: ouassima_elqouarti@um5.ac.ma
Published online: 30 June 2025
In the context of DC microgrids, the grid-tied PV system boost converter control is of great interest. It forms one of the coupling joint between the utility grid and the DC source. Conventionally, it is controlled using proportional integral controller, however, it is interesting to consider robust controllers, which are known to provide good performances despite systems disturbances and/or uncertainties. In this paper, we investigate the second order sliding mode controller, particularly the super-twisting algorithm in order to give active power support to the grid, while the three-phase inverter is controlled to ensure adequate power sharing, DC voltage regulation and unity power factor. Simulation results endorse the validity of the proposed algorithm along with the adopted power management strategy. Two control modes are being highlighted; the MPPT mode, and P-control mode, under constant DC load and varying irradiation profile.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.