Leader follower second order voltage control with disturbance observer for DC microgrids.

This paper proposes an advanced secondary voltage control framework for a renewable- and electric-vehicle (EV)-integrated DC microgrid using a leader-follower multi-agent consensus architecture. To coordinate power sharing among heterogeneous battery energy storage systems (BESS), a second-order distributed voltage control strategy is developed, wherein battery voltage dynamics are modeled as second-order agents to enhance transient performance and convergence characteristics. Unlike conventional approaches that rely on random or heuristic leader assignment, this work introduces a theoretically grounded cost-index-based leader selection criterion, derived from an analytical Riccati formulation using battery ampere-hour (Ah) ratings. The proposed criterion enables the selection of an optimal battery leader that minimizes quadratic energy cost and battery stress, thereby reducing control effort and improving overall system efficiency. Following optimal leader identification, the paper addresses the challenge of continuous disturbances and uncertainties arising from heterogeneous loads, renewable intermittency, EV charging demand, and communication imperfections. To this end, a novel disturbance-observer-based heterogeneous consensus control scheme is integrated into the secondary control layer. The proposed second-order disturbance observer enables accurate estimation and compensation of unknown current and power disturbances acting on follower agents, ensuring robust voltage regulation and coordinated power sharing under dynamic operating conditions. The developed control framework is fully distributed, requires only sparse low-bandwidth communication among neighboring agents, and preserves system stability under battery disconnection/reconnection, plug-and-play operation, communication delays, and link failures. Comprehensive MATLAB/Simulink case studies on a four-bus DC microgrid comprising photovoltaic sources, wind generation, heterogeneous batteries, DC loads, and EV charging stations validate the effectiveness of the proposed approach. Simulation results demonstrate significantly reduced DC bus voltage deviation, faster convergence, improved state-of-charge (SoC) balancing, and lower power mismatch compared with conventional droop control, homogeneous consensus control, existing leader-follower strategies, and sliding-mode-based distributed controllers. The proposed method thus offers a robust, scalable, and energy-efficient secondary voltage control solution for next-generation DC microgrids with high renewable and EV penetration.