Adaptive control and management of multiple nano-grids in an islanded dc microgrid system

Abstract

This paper presents an adaptive control framework for the flexible and effective management and control of clustered DC nano-grids (NGs) in an islanded DC microgrid system. It is assumed that each NG contains a photovoltaic (PV) system, a battery energy storage system (BESS), local loads, and a gateway (GW) module. Each NG has a hierarchical control system consisting of a decision-making module and low-level controllers. The decision-making module ensures various desirable features including plug-and-play operation of NGs, maximum utilization of PV power generations, and avoiding state of charge (SoC) violation of batteries. Moreover, an adaptive model predictive control (AMPC) strategy is proposed to regulate the voltage of the NG local DC buses in the presence of non-linear loads. This approach improves the performance of the NG voltage control system and reduces the current ripples of BESSs, thereby enhancing the lifetime of the batteries. In addition, a smart switching consensus-based control strategy is designed that provides flexible power sharing among the NGs to balance the SoC of BESSs in which the BESSs altogether imitate the behaviour of a single cloud energy storage system (ESS). Finally, the performance of the proposed control system is verified by simulating the DC microgrid in MATLAB/Simulink.