Abstract
Microgrids (MGs) are the important entities of distribution systems and more distributed generations (DGs) need to be considered to achieve maximum benefits under the full potential of MGs. By considering the important role of power converters in MGs, problem formulation with model predictive control (MPC) of reconfigurable converter (VSC) is implemented for AC/DC microgrid. The uncertainties due to the loads and sources (RESs) are investigated. Active front end (AFE) rectifier regulates the DC voltage and power is controlled through direct power MPC (DPMPC) during grid connection. Model predictive voltage control (MPVC) regulates AC load voltage in islanded mode. Furthermore, the transition between grid-connected and standalone is thoroughly investigated. MATLAB/Simulink® software authenticates the model performance evaluation of the suggested scheme for different loads. The proposed scheme shows superior attributes with reduced THD.

Abstract
The voltage source converter (VSC) can be operated in bidirectional operational modes i.e. rectification and inversion, which signifies its reconfigurable characteristics. In inverter mode, it operates in both grid-tied and isolated operation modes. In this paper, a fractional-order sliding mode control (FOSMC) is proposed to drive the voltage source converter under reconfiguration. To realize the power system, in grid-tied mode the effect of voltage sag/swell at the point of common coupling (PCC), battery storage (BS) charging, and high voltage (HV) dc-link voltage are considered. Likewise, in isolated mode the voltage at the PCC, BS discharging, and HV dc-link voltage are considered as well. The Riemann-Liouville (RL) is used to design the proposed sliding surface and exponential reaching law is used to minimize the chattering phenomenon. The stability of the proposed controller is proved using the Lyapunov stability criteria. To validate the performance of the proposed strategy, the real-time simulation is accomplished by using the MATLAB/Simulink environment and results are compared with conventional proportional-integral (PI) control. The simulation results demonstrate the effectiveness of the proposed control in terms of robustness, fast-tracking, and rapid convergence as compared to PI control.

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