Distributed Quantized Control for Multiple DC Microgrids via Asymmetric Sampling Under Bandwidth Constraints

With the growing digitalization and networking of microgrids, limited bandwidth has become a critical constraint in practical implementation. This paper investigates the problem of distributed control for multiple DC microgrids under bandwidth constraints and proposes a novel control strategy based on dynamic quantization and asymmetric sampling mechanism. The dynamic quantization dynamically adjusts the quantization resolution, enabling efficient communication with as few as 1 bit per transmission, minimizing the required data volume. Meanwhile, the asymmetric sampling allows heterogeneous sampling rates for different generators, substantially decreasing the communication frequency. Unlike event-triggered methods, this strategy avoids the reliance on continuous monitoring devices, thereby enhancing practically feasibility. The proposed controller effectively achieves voltage regulation and current sharing among all distributed generators, while enabling power sharing across multiple microgrids under low-bandwidth conditions. Finally, the effectiveness is validated through RT-LAB, demonstrating a 64.43% reduction in bandwidth compared with the baseline event-triggered controller, while improving conventional bounded error to zero steady-state error.