This article presents a new cascaded control strategy to control the power flow in a renewable-energy-based microgrid operating in grid-connected mode. The microgrid model is composed of an AC utility grid interfaced with a multi-functional grid interactive converter (MF-GIC) acting as a grid-forming converter, a photovoltaic (PV) power-generation system acting as grid-feeding distributed generation unit, and various sensitive/non-sensitive customer loads. The proposed control strategy consists of a fractional order PI (FO-PI) controller to smoothly regulate the power flow between the utility grid, distributed generation unit, and the customers. The proposed controller exploits the advantages of FO (Fractional Order) calculus in improving the steady-state and dynamic performance of the renewable-energy-based microgrid under various operating conditions and during system uncertainties. To tune the control parameters of the proposed controller, a recently developed evaporation-rate-based water-cycle algorithm (ERWCA) is utilized. The performance of the proposed control strategy is tested under various operating conditions to show its efficacy over the conventional controller. The result shows that the proposed controller is effective and robust in maintaining all the system parameters within limits under all operating conditions, including system uncertainties.

In this paper, an advanced electrothermal simulation strategy is applied to a 3.3 kV silicon carbide MOSFET power module. The approach is based on a full circuital representation of the module, where use is made of the thermal equivalent of the Ohm’s law. The individual transistors are described with subcircuits, while the dynamic power-temperature feedback is accounted for through an equivalent thermal network enriched with controlled sources enabling nonlinear thermal effects. A synchronous step-up DC-DC converter and a single-phase inverter, both incorporating the aforementioned power module, are simulated. Good accuracy was ensured by considering electromagnetic effects due to parasitics, which were experimentally extracted in a preliminary stage. Low CPU times are needed, and no convergence issues are encountered in spite of the high switching frequencies. The impact of some key parameters is effortlessly quantified. The analysis witnesses the efficiency and versatility of the approach, and suggests its adoption for design, analysis, and synthesis of high-frequency power converters in wide-band-gap semiconductor technology.

The conversion and control for the utilization of power generated from energy sources can be performed using a power electronic converter system. The voltage source inverter (VSI) is one of the commonly used converter topologies, being controlled by a switching control algorithm for power conversion. Finite set-model predictive control (FS-MPC) is a modern switching control algorithm and has received significant attention due to its predictive nature. In this paper, the implementation of FS-MPC is presented for the load-side current control of a three-phase VSI system using an integrated platform of MATLAB/Simulink and Xilinx system generator (XSG). The XSG provides the functionality of digital design and intuitive implementation of field-programmable gate array (FPGA) controlled systems. The additional functionality of hardware-in-the-loop (HIL) co-simulation using FPGA is used for the testing and validation of controller performance. The controller performance is validated through three platforms: MATLAB/Simulink, XSG and HIL co-simulation using ZedBoard Zynq evaluation and development FPGA kit.

In this paper, finite-set model-predictive control (FS-MPC) is inducted for a motor drive system. The dynamic response and multiple constraint handling nature of FS-MPC are the major factors that stand out among the controller family. However, for real-time implementation, the computational burden of FS-MPC is a primary concern. Due to the parallel processing nature and discrete nature of the hardware platform, the field-programmable gate array (FPGA) can be an alternative solution for the real-time implementation of the controller algorithm. The FPGA is capable of handling the computational requirements for FS-MPC implementation; however, the system development involves multiple steps that lead to a time-consuming debugging process. Moreover, specific hardware coding skill makes it more complex, corresponding to an increase in system complexity, which leads to a tedious task for the system development. This paper presents a FPGA-based implementation of the predictive current control of a permanent magnet synchronous motor (PMSM). FS-MPC of the PMSM drive system is designed and implemented using the digital model integration approach provided by the Xilinx system generator (XSG) and VIVADO platform. The step change in the load disturbance as well as the reference speed is considered for the analysis of the controller for the motor drive system. Moreover, the steady state error and harmonic distortion in the motor current is considered for an in-depth analysis of the system performance corresponding to different sampling frequencies.

Three-phase two-level voltage source converters are used for distribution static compensator (DSTATCOM) applications and can be replaced by a multilevel inverter. In this paper, an LCL filter interfaced cascaded H-bridge multilevel inverter-based (CHBMLI) DSTATCOM is simulated and its performance is analyzed considering the system parameters. The analysis considers factors including the switching frequency, modulation index, and filter parameters of a DSTATCOM system. The LCL filter design and analysis for the low switching frequency operation of CHBMLI is proposed in this paper. Phase shift pulse-width modulation is used for the generation of switching signals. The reference current is generated using synchronous reference frame theory (SRFT) for reactive power and harmonic compensations. The simulation model of the CHBMLI-based DSTATCOM system is developed in MATLAB Simulink. The results are demonstrated for a linear/non-linear load under unbalanced conditions, considering the voltage sag and swell in the system due to a disturbance in the load.