Virtual capacitor-based robust composite controller for stability enhancement in DC microgrids with wind, PV and battery integration

This paper presents a novel composite control strategy aimed at enhancing large-signal stability in DC microgrids, tackling challenges such as low inertia. The controller integrates global non-singular fast terminal sliding mode control with a backstepping technique (BGNFTSMC) to address issues like chattering, singularity and finite-time convergence. The microgrid comprises a solar PV system, a permanent magnet synchronous generator-based wind turbine, a battery storage unit and DC loads, with reference values generated by artificial neural networks. The primary objective of the controller is to stabilise the DC-bus voltage while ensuring optimal power flow regulation. To mitigate the low inertia issue, a virtual capacitor is incorporated into the design. Furthermore, a fuzzy logic-based energy management system optimises battery endurance by managing the state of the charge and adapting to operations for reliable power distribution. The closed-loop stability of the system is rigorously analysed using the Lyapunov stability theory, ensuring finite-time convergence of tracking errors. MATLAB/Simulink simulations highlight the BGNFTSMC's superior performance, achieving up to 100% overshoot reduction and over 91% improvement in settling time compared to existing controllers. The adaptive neuro-fuzzy inference system-optimised BGNFTSMC eliminates overshoot and improves stability with a 29.76% faster settling time. The proposed BGNFTSMC controller also demonstrates excellent robustness in handling transient deviations caused by load and power fluctuations. Real-time processor-in-the-loop (RT-PiL) experiments validate the controller's reliability. Despite MATLAB/Simulink showing improvements, including overshoot reductions of 15.789%, 21.875%, and 30.303% compared to RT-PiL, the RT-PiL platform maintains acceptable performance. This analysis underscores the BGNFTSMC's practical reliability.