Improved Power Management of Standalone DC Microgrid With Hybrid Energy Storage System Using a Fixed Switching Frequency Model Predictive Control
Due to their high efficiency and simplicity, DC microgrids (MGs) are becoming increasingly popular. However, controlling DC MGs is a complex duty, where voltage control and power management are particularly challenging tasks. This paper presents a fixed switching frequency model predictive control (...
Saved in:
| Published in: | International journal of circuit theory and applications |
|---|---|
| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
29.06.2025
|
| ISSN: | 0098-9886, 1097-007X |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Due to their high efficiency and simplicity, DC microgrids (MGs) are becoming increasingly popular. However, controlling DC MGs is a complex duty, where voltage control and power management are particularly challenging tasks. This paper presents a fixed switching frequency model predictive control (FSF‐MPC) along with a modified rule‐based power management algorithm (PMA) proposed for small‐scale photovoltaic (PV) DC MG with hybrid energy storage system (HESS). State of charge (SoC) monitoring for both the battery and supercapacitors (SCs) ensures optimized power sharing and rapid charge–discharge capabilities. Based on reference powers generated by the PMA, the proposed control strategy determines the optimal duty cycle for each power converter, as well as regulating the DC‐bus voltage. Simulation and experimental results are used to verify system efficacy by testing different operation modes. The FSF‐MPC significantly enhances the system's performance compared to conventional control techniques, improving peak overshoot, settling time, and steady‐state error. |
|---|---|
| ISSN: | 0098-9886 1097-007X |
| DOI: | 10.1002/cta.70039 |