Adaptive Mixed Time-state Dependent Distributed Event-triggered Consensus Protocol of a DC Microgrids Cluster

Abstract

This paper presents a novel Adaptive Mixed Time-State Dependent Distributed Event-Triggered Consensus Protocol (AMDETC) aimed at achieving less communication requirements among microgrids (MGs) within a cluster. Also, an adaptive fixed-time consensus algorithm (AFTA), enhanced by a saturation function, is incorporated into the secondary control layer to improve currents convergence rates within the cluster. Additionally, the Grey Wolf Optimizer (GWO) technique is utilized to fine-tune the parameters of proportional–integral (PI) controllers at the secondary control level, thus bolstering the cluster’s resilience to disturbances. The results demonstrate the proposed control strategy’s superiority over current control schemes, particularly in terms of realizing 100% accuracy of triggering instances and achieving rapid currents convergence within 0.02s along with swift voltage recovery under various operational conditions. A simulation involving a cluster of four DC MGs is executed in the MATLAB environment to validate the effectiveness of the proposed control approach against existing control techniques. Moreover, OPAL-RT is employed to validate this technique in a real-life scenario.