Abstract
In recent years, the power industry has witnessed substantial advancements driven by the increasing demand for clean and renewable energy. However, renewable energy integration into the grid presents significant technical and management challenges, such as the need for highvoltage power transmission, handling the variability of wind and solar energy, and ensuring grid stability through technological and market mechanism advancements. Energy storage technologies, particularly battery energy storage systems (BESS), play a crucial role in mitigating these challenges. BESSs help balance the intermittency of renewable energies, enhancing grid resilience and overall reliability. Among power conversion technologies, the modular multilevel converter (MMC) has emerged as an advanced option with notable advantages. It is an advanced voltage source converter applicable to a wide range of medium and high-voltage applications. Interfacing BESSs to the grid with MMCs is promising for creating adaptable, flexible and resilient grid architectures, offering benefits such as improved energy efficiency and flexibility.
Nevertheless, the use of MMC-BESSs to their full potential brings several technical challenges, including system complexity due to numerous components, control complexity involving manipulation of multiple power switches and diverse control algorithms, the need to eliminate circulating current to reduce power losses, achieving state-of-charge (SoC) balancing for optimal battery performance and grid stability, and ensuring robustness despite component variability.
This PhD research is driven by these challenges. Its objectives include modelling, advanced control strategy formulation with balancing technique, optimization, power loss and thermal management, and prototyping and testing. A comprehensive converter mathematical model was developed, and control strategies such as grid-connected power control, circulating current control, and SoC balancing control were proposed. In this PhD thesis, the newly introduced soft arm SoC balancing control method outperforms the hard arm SoC balancing control in SoC balancing. This leads to a more stable and efficient operation of the MMC-BESS, accompanied by a reduction in the total harmonic distortion of the output current. Design and optimization efforts focused on the arm inductor and control system, using techniques like multi-objective genetic algorithm and
particle swarm optimization. Thermal management involved analyzing semiconductor power losses and developing thermal models. Simulation results provided insights into the system's thermal behavior. Finally, the prototyping and validation of silicon carbide based MMC system with integrated BESS revealed that in both resistive-inductive load and grid-connected scenarios, the control system performed as expected in aspects such as (bidirectional grid) current regulation, elimination of the circulating current, and equalization of the battery module voltages.
Nevertheless, the use of MMC-BESSs to their full potential brings several technical challenges, including system complexity due to numerous components, control complexity involving manipulation of multiple power switches and diverse control algorithms, the need to eliminate circulating current to reduce power losses, achieving state-of-charge (SoC) balancing for optimal battery performance and grid stability, and ensuring robustness despite component variability.
This PhD research is driven by these challenges. Its objectives include modelling, advanced control strategy formulation with balancing technique, optimization, power loss and thermal management, and prototyping and testing. A comprehensive converter mathematical model was developed, and control strategies such as grid-connected power control, circulating current control, and SoC balancing control were proposed. In this PhD thesis, the newly introduced soft arm SoC balancing control method outperforms the hard arm SoC balancing control in SoC balancing. This leads to a more stable and efficient operation of the MMC-BESS, accompanied by a reduction in the total harmonic distortion of the output current. Design and optimization efforts focused on the arm inductor and control system, using techniques like multi-objective genetic algorithm and
particle swarm optimization. Thermal management involved analyzing semiconductor power losses and developing thermal models. Simulation results provided insights into the system's thermal behavior. Finally, the prototyping and validation of silicon carbide based MMC system with integrated BESS revealed that in both resistive-inductive load and grid-connected scenarios, the control system performed as expected in aspects such as (bidirectional grid) current regulation, elimination of the circulating current, and equalization of the battery module voltages.
| Original language | English |
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| Award date | 9 Apr 2025 |
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| Publication status | Published - 2025 |