Modeling and Control of a Modular Multilevel Converter Based on a Battery Energy Storage System with Soft Arm State-of-Charge Balancing Control
Abstract
:1. Introduction
2. MMC-BESS Modeling and Analysis
2.1. MMC-BESS Configuration
2.2. MMC-BESS Modeling and Analysis
2.2.1. MMC-BESS System Modeling
2.2.2. MMC-BESS SoC Balancing Analysis
3. MMC-BESS Control Strategy
3.1. Grid-Connected Power Control
3.2. Circulating Current Control
3.3. SoC Balancing Control
4. Results and Analysis
5. Conclusions
- Compared to HASBC, SASBC provides better performance in balancing the SoC between and within the arms. In this case, under the control of HASBC, the arm SoCs of the phase A upper arm and lower arm are not able to be equalized before 100 s, and it takes 66 s to reduce the delta SoC to 0.05% with reference to the average arm SoC. In contrast, all the arm SoCs in the three phases/six arms can be balanced fast, and it takes 5.1 s to fall into the 0.05% zone under the control of SASBC. Besides, individual SoCs of phase A under the control of HASBC are split into two groups and exhibit a protracted convergence exceeding 100 s toward zero, requiring 62.5 s to reach the 0.05% deviation range. However, they are forced to converge at zero rapidly and only take 6.5 s to reach the margin of 0.05% under the SASBC.
- The MMC-BESS power fluctuates between phases, arms, and individual submodules to balance the SoC of batteries, and after the accomplishment of the SoC equalization, the power is equally distributed and the circulating current is well eliminated.
- The MMC-BESS can operate in both charging and discharging modes, and the THD of the output current is reduced from 6.80% to 1.13% after SoC balancing is achieved.
- The robustness test shows the control system’s effective performance in handling component variations.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A. Derivation of Equations
Appendix A.1. Equation (30)
Appendix A.2. Equation (31)
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Parameters | Values |
---|---|
No. of submodules per arm | 6 |
Nominal voltage of battery banks | 1000 V |
RMS grid phase-to-phase voltage | 2000 V |
Grid frequency | 50 Hz |
Carrier frequency | 1 kHz |
Nominal power level | ±1 MW |
Submodule capacitance | |
Arm inductance | 10 mH |
SoCs | Hard Arm SoC Balancing Control | Soft Arm SoC Balancing Control |
---|---|---|
Arm SoC balancing | Split s (66 s ()) | Balanced (5.1 s ()) |
Phase A individual SoC | Split s () | Balanced () |
Phase B individual SoC | Balanced | Balanced |
Phase C individual SoC | Balanced | Balanced |
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Wang, Y.; Chakraborty, S.; Geury, T.; Hegazy, O. Modeling and Control of a Modular Multilevel Converter Based on a Battery Energy Storage System with Soft Arm State-of-Charge Balancing Control. Energies 2024, 17, 740. https://doi.org/10.3390/en17030740
Wang Y, Chakraborty S, Geury T, Hegazy O. Modeling and Control of a Modular Multilevel Converter Based on a Battery Energy Storage System with Soft Arm State-of-Charge Balancing Control. Energies. 2024; 17(3):740. https://doi.org/10.3390/en17030740
Chicago/Turabian StyleWang, Yang, Sajib Chakraborty, Thomas Geury, and Omar Hegazy. 2024. "Modeling and Control of a Modular Multilevel Converter Based on a Battery Energy Storage System with Soft Arm State-of-Charge Balancing Control" Energies 17, no. 3: 740. https://doi.org/10.3390/en17030740
APA StyleWang, Y., Chakraborty, S., Geury, T., & Hegazy, O. (2024). Modeling and Control of a Modular Multilevel Converter Based on a Battery Energy Storage System with Soft Arm State-of-Charge Balancing Control. Energies, 17(3), 740. https://doi.org/10.3390/en17030740