Prescribed Performance-Based Distributed Predefined Time Control for DC Microgrid Clusters

Abstract

Interconnecting DC microgrids (MGs) into a cluster enhances renewable energy utilization and improves power supply reliability by enabling power flow between them. Effective management of DC MG clusters requires a control system designed for rapid response to fluctuating renewable source behavior and load demands. Traditional control methods lack the ability to pre-specify desired system performance, including convergence time and transient/steady-state behavior. Therefore, this work explores a prescribed performance function-based predefined time (PPF-PDT) control for optimizing the power dispatch of interconnected DC MGs according to the user-assigned preplanned desired performance. This scheme comprises secondary and tertiary control layers to handle the optimal operation for individual MGs and interconnected MGs, respectively, using a dual-layer sparse cyber network. In each MG, the secondary control matches the incremental costs of all distributed generation units while stabilizing the MG’s average voltage to the assigned voltage level within an adjustable predefined settling time independent of initial states. Adopting PPF significantly enhances transient and steady-state behavior, ensuring the tracking errors remain within desired performance limits. Additionally, distributed tertiary controllers across multiple MGs adjust their voltage references to optimize the exchanged power among them within a user-assigned tunable settling time. A thorough Lyapunov analysis verifies the stability of the proposed control algorithm within the predefined time and confines the tracking errors within acceptable bounds. Extensive simulation and experimental studies confirm the feasibility of the control strategy under various conditions.