Filtration-based (FB) power/current allocation of battery-supercapacitor (SC) hybrid energy storage systems (HESSs) is the most common approach in DC microgrid (MG) applications. In this approach, a low-pass or a high-pass filter is utilized to decompose the input power/current of HESS into high-frequency and low-frequency components and then assign the high-frequency parts to SC. Moreover, to avoid the state of charge violation (SoC) of SC, this approach requires a rulebased supervisory controller which may result in the discontinuous operation of SC. This paper first provides a small-signal stability analysis to investigate the impact of an FB current allocation system on the dynamic stability of an islanded DC MG in which a grid-forming HESS supplies a constant power load (CPL). Then, it shows that the continuous operation of SC is essential if the grid-forming HESS is loaded by large CPLs. To address this issue, this paper proposes a model predictive control (MPC) strategy that works in tandem with a high-pass filter to perform the current assignment between the battery and SC. This approach automatically restores the SoC of SC after sudden load changes and limits its SoC variation in a predefined range, so that ensure the continuous operation of SC. As a result, the proposed FB-MPC method indirectly enables the MG's proportional-integral (PI) voltage controller to operate with higher gain values leading to better transient response and voltage quality. The performance of the proposed approach is then validated by simulating the system in MATLAB/Simulink. INDEX TERMS Filtration-based power/current allocation systems, battery/supercapacitor hybrid energy storage systems, model predictive control, stability analysis, state of charge recovery.
NOMENCLATUREA.
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 decisionmaking 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 nonlinear 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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.