A Novel Multilevel Control Algorithm for Co-operative Energy Management in Interconnected DC Microgrids

Due to limited energy resources, autonomous DC microgrids (DCMGs) often face challenges in meeting system demand. Interconnecting these MGs into a cluster enables optimal resource utilization, improving overall reliability and stability. However, coordinating power flow among interconnected MGs while maintaining optimal performance remains a significant challenge. Advancements in cloud computing offer a powerful solution for managing distributed energy resources (DERs) across vast geographic areas. This paper presents a modular cloud-edge architecture for cooperative management of DERs in autonomous DCMG clusters. The proposed hierarchical framework consists of a cloud-based central controller that optimizes resource allocation across the cluster, a MG-level edge controller that prioritizes load management, and a local controller that ensures power-sharing with central setpoints. This multi-tiered approach enhances operational efficiency and grid resilience by enabling fast, localized responses while leveraging cloud-based intelligence for strategic decision-making. Performance evaluations demonstrate that the proposed control strategy improves renewable energy utilization, reduces dependency on storage, and ensures a reliable power supply to connected loads.