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This paper proposes a novel H-bridge based hybrid multilevel inverter consists of small number of switching devices and output of H-bridge multilevel by switching the solar PV voltage sources in series and parallel. The proposed H-bridge multilevel inverter reduces number of switching devices which reduces the power consumption and size of the gate driver circuits. The proposed inverter gives more number of output voltages which reduces total harmonic distortion of the output voltage waveform. The hybrid modulation method is used to control H-bridge multilevel inverter. The proposed inverter is validated through simulation results are validated by using MATLAB/SIMULINK.

This article discusses metaheuristic algorithms for optimizing controller gains for dynamic voltage restorers (DVRs) that use an impedance control strategy to compensate for unbalance in source voltages, voltage harmonics, and sag/swell in source voltages. The gains of the proportional‐integral (PI) controllers become critical for proper DVR load voltage extraction. Various techniques for optimization, such as whale optimization technique, gray wolf optimization technique, particle swarm optimization technique, and ant lion optimization technique, are used to obtain DC and AC PI controller gains for DVR. The impedance control strategy employs simple calculations to determine the resistance and reactance of a polluted source voltage, without the use of frame conversions as in synchronous reference theory, instantaneous reference power theory, and so on. The quick calculations of the impedance control scheme improve the power quality and dynamics. The Metaheuristic algorithms are used to calculate the number of iterations required to achieve the best possible controller gains, which further helps to improve power quality and dynamics. Among these optimization techniques, the antlion optimization technique provides fast convergence and the best possible controller gain values to improve the dynamics of the dc‐link voltage of voltage source converter and terminal voltage, thereby improving power quality. The proposed antlion optimization technique‐based DVR model is simulated in MATLAB R2019, and the results are validated with RT‐LAB.

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This study proposes a control algorithm based on synchronous reference frame theory with unit templates instead of a phase locked loop for grid-connected photovoltaic (PV) solar system, comprising solar PV panels, DC-DC converter, controller for maximum power point tracking, resistance capacitance ripple filter, insulated-gate bipolar transistor based controller, interfacing inductor, linear and nonlinear loads. The dynamic performance of the grid connected solar system depends on the effect operation of the control algorithm, comprising two proportional-integral controllers. These controllers estimate the reference solar-grid currents, which in turn generate pulses for the three-leg voltage source converter. The grey wolf optimization algorithm is used to optimize the controller gains of the proportional-integral controllers, resulting in excellent performance compared to that of existing optimization algorithms. The compensation for neutral current is provided by a star-delta transformer (non-isolated), and the proposed solar PV grid system provides zero voltage regulation and eliminates harmonics, in addition to load balancing. Maximum power extraction from the solar panel is achieved using the incremental conductance algorithm for the DC-DC converter supplying solar power to the DC bus capacitor, which in turn supplies this power to the grid with improved dynamics and quality. The solar system along with the control algorithm and controller is modeled using Simulink in Matlab 2019.