In this paper, a comparative study based

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in this paper, an enhanced control scheme is proposed to improve the performances of a three-phase shunt active power filter. The objective is to compensate for current harmonics and reactive power in three-phase power distribution grid. The proposed control scheme is inserted in the active filter in order to regulate the DC link capacitor voltage. This control scheme is based on the combination of a fuzzy logic controller and an ADALINE network (Adaptive FLC). The ADALINE is used to filter the measured DC voltage; an error is than calculated and with its derivative are injected in a fuzzy controller. The output of this controller is used to generate the compensating currents that are injected in the power distribution grid. The controller's outputs are combined with calculated reference currents. These are obtained for each phase with an ADALINE network which yields to a precise decomposition of the measured currents. Based on Fourier series, this neural approach provides in real time each individual harmonic component of the measured currents without any additional reference frame transforms. Simulation tests show that the proposed approach is able to significantly reduce the fluctuations of the DC voltage. The results also show that the proposed control approach can compensate for highly distorted line currents in a better way than with more traditional techniques.

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This research article proposes the optimization of a grid-connected photovoltaic system based on the PV emulator (PVE), the Boost converter, and a single-phase full-bridge inverter. The main objective is to track and extract the highest amount of power from the PV system working under variable solar irradiation while reducing losses and time response in each stage of the converter. As none, the main flaw of the classical maximum power point tracking algorithm (MPPT) is its performance. The control law design is based on a PI controller in the PVE, a meta heuristic whale optimization algorithm (WOA) in the MPPT, and a reduced switching finite set model predictive control (RS-FS-MPC) for the single-phase full-bridge inverter. The proposed control techniques inherit the property of robustness and successfully deal with the nonlinear behavior of the system. The performance validation and effectiveness of the proposed control techniques is supported by MATLAB/SIMULINK simulations and is also verified experimentally on various systems carried out under varying solar irradiation.