Small-signal Stability Analysis of DC Microgrids

The conventional cascaded control strategies using proportional-integral- derivative controller often result in high settling times, considerable oscillations, poor voltage regulation, and low bandwidth. This leads to unsatisfactory performance in systems where multiple input variables are each subject to high levels of temporal variability, such as in DC microgrids (MGs) with renewable sources of generation. To overcome these challenges, an average current mode (ACM)-based cascaded control approach is proposed for DC MGs to maintain small-signal stability. An analytical small-signal equivalent model of the cascaded ACM control is developed to examine the impact of control parameter variations on system dynamics. Stability is assessed of DC MG to evaluate the effectiveness of the designed controller, while a sensitivity analysis identifies critical parameters affecting system performance. The effectiveness of the proposed control scheme is demonstrated through MATLAB/Simulink simulations of a power converter model, which specifically addresses small-signal disturbances such as load changes, generation variations, and battery charging and discharging cycles. Results demonstrate that the ACM-based control scheme provides superior robustness against small-signal disturbances, minimising settling time, and eliminating oscillations. Additionally, it offers improved power quality, bandwidth and voltage regulation compared to conventional methods under both normal operating conditions and in response to small-signal perturbations.