Hybrid Metaheuristic Secondary Distributed Control Technique for DC Microgrids

Abstract

Islanded DC microgrids are poised to become a crucial component in the advancement of smart energy systems. They achieve this by effectively and seamlessly integrating multiple renewable energy resources to meet specific load requirements through droop control, which ensures fair distribution of load current across the distributed energy resources (DERs). Employing droop control usually results in a DC bus voltage drop. This article introduces a secondary distributed control approach aimed at concurrently achieving current distribution among the DERs and regulating the voltage of the DC bus. The proposed secondary control approach eradicates voltage fluctuations and guarantees equitable current allocation by integrating voltage and current errors within the designed control loop. A novel hybrid particle swarm optimization–grey wolf optimization (HPSO-GWO) has been proposed, which assists in selecting the parameters of the distributed control technique, enabling the achievement of the proposed control objectives. Eigenvalue observation analysis has been utilized through the DC microgrid state-space model designed to assess the influence of the optimized distributed secondary control on the microgrid stability. A real-time testing system was constructed within MATLAB/Simulink® and deployed on Speedgoat™ real-time equipment to validate the operations of the proposed technique for practical applications. The results indicated that the proposed secondary control effectively enhances voltage recovery and ensures proper current distribution following various disturbances, thereby maintaining a continuous power supply. The outcomes also demonstrated the capabilities of the control approach in accomplishing the control objectives within the DC microgrid, characterized by minimal oscillations, overshoots/undershoots, and rapid time responses.