Enhancing DC microgrids cluster performance with distributed event-triggered consensus protocols

Abstract

Microgrid (MG) clusters offer solutions to the challenges faced by individual MGs in extreme conditions but require precise coordination to manage generation-load imbalances effectively. This paper presents a hierarchical control strategy that combines time-based and event-based consensus protocols (ETC) in the overarching control layer. Traditional time-based protocols require constant sampling, leading to unnecessary communication and computational burdens. To address this, we introduce a mixed time-state dependent distributed event-triggered consensus protocol (MDETC), which reduces communication needs while maintaining MG performance. A set-time consensus algorithm is used at the secondary control level to synchronize currents and voltages quickly. Additionally, the integration of Particle Swarm Optimization (PSO) in primary control ensures efficient current distribution and voltage regulation among neighboring MGs. The study also explores automatic reconfiguration within the cluster to support Plug-N-Play functionality, ensuring seamless MG operation. The effectiveness of this control approach is demonstrated through MATLAB simulations of a four-DC MG cluster, showing improved efficiency in reducing triggering instances and achieving faster current and voltage stabilization under various conditions.

Keywords

• Dc microgrids
• Distributed control strategies
• Clustered microgrids
• Event triggered
• Droop control strategy