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This paper presents an application of fractional control scheme named Tilt Integral Derivative (TID) to control a stand-alone hybrid energy system composed of a solar photovoltaic (PV) system and a battery bank (BB). A three-level NPC inverter is inserted in order to increase the efficiency of the energy injected into the AC load. Variation in solar radiation or AC load may cause power imbalance, which leads to variation in DC link voltage. As a solution, a buck-boost converter is connected between the DC link and the battery bank to ensures the transfer of energy in both directions. The parameters of TID controller were tuned using a powerful optimization technique known a Genetic Algorithm (GA) by minimizing the Mean Square Error (MSE) used as a performance index. The effectiveness of the proposed TID controller is demonstrated through a comparison with a conventional Proportional-Integral-Derivative (PID) controller, whose parameters are computed by the pidtool function of the Matlab/Simulink tool where the DC link voltage behavior is previously modeled by a capacitor transfer function. The obtained results show that the proposed TID controller provides a stable DC bus with low chattering, regardless of the rapid irradiation and load changes, when compared to a conventional PID controller.

In this paper, the application of the Particle Swarm Optimization (PSO) method to proportional integral regulators of two-stage photovoltaic power conversion systems is presented. The photovoltaic generator is connected to a boost converter controlled by Maximum Power Point Tracking (MPPT) fuzzy logic regulator. The three-phase three-level inverter constituting the second stage of studied cascade is controlled by the vector pulse width modulation strategy. To be able to synchronize the injected current and the grid voltage, a phase-locked loop is used. Three PI regulators are used to regulate the DC bus voltage as well as the grid currents obtained after transformation in rotating dq-reference frame. The parameters of the regulators used are determined by the particle swarm optimization method.

This paper focuses on the performance of a single-phase inverter coupled to the grid in terms of optimal photovoltaic transfer, using the concept of sliding-mode variable structure systems. Moreover, a fuzzy logic control technique optimized by genetic algorithm (GA) associated with a boost converter is used to extract the Maximum Power Point Tracking (MPPT).The validation of the results using Matlab/Simulink software is carried under different environmental and operating conditions to verify the satisfactory performance of the proposed control strategies.The original version of this article supplied to AIP Publishing contained an error in the author’s name. The name originally appeared as, Layachi Zaghba, but the correct name is Zaghba Layachi. An updated version of this article, with the author’s name corrected, was published on January 23, 2020.

This paper presents a new control scheme based on Fuzzy Logic Controller (FLC) of output three levels inverter voltages for photovoltaic conversion stand alone two stages cascade. The error between the root mean square value of output voltage and it to reference and the change of error constitute the two inputs of FLC. The error of modulation index represents the output of FLC. The boost converter is controlled by a FLC in order to extract the maximum power from PVG. In order to have a symmetrical and stable output voltage of our cascade, the input DC voltages must be of equal values. An algorithm for stabilizing these two voltages using the redundant configurations of the inverter vectors is introduced into the control loop. The simulation results show that the rms output voltage is inside the band of +/-10V and with low total harmonic distortion despite irradiation change.

This paper focuses on the performance of a single-phase inverter coupled to the grid in terms of optimal photovoltaic transfer, using the concept of sliding-mode variable structure systems. Moreover, a fuzzy logic control technique optimized by particle swarm algorithm (PSO) associated with a boost converter is used to extract the Maximum Power Point Tracking (MPPT).The validation of the results using Matlab/Simulink software is carried under different environmental and operating conditions to verify the satisfactory performance of the proposed control strategies.

The purpose of this paper is to develop a control and regulation method for the input DC voltages of a 5-level neutral point clamping (NPC) active power filter (APF). This APF is applied for the enhancement of medium-voltage network power quality by compensation of harmonic currents produced by an induction motor speed variator. In the first part, the authors present a topology of a 5-level NPC voltage source inverter and its simplified space vector pulse width modulation (SVPWM) control strategy. In the second part, the control strategy of the 5-level pulse width modulation current rectifier is presented. In the third part, to remedy to instability problem of the input DC voltages of the APF, the authors propose the feedback control of the 5-level rectifier associated with a simplified SVPWM with the redundant vectors method for the 5-level APF. After that, the sliding mode regulator used to control the APF is developed. The application of the proposed control algorithm offers the possibility of stabilizing the DC voltages of the APF. The stable DC bus supply associated with the sliding regulator of the APF allows the obtainment of low-harmonic content network currents with unity power factor. The instability problem associated with the use of the multilevel APF is solved. The obtained results are full of promise for the use of the multilevel APF in medium-voltage and high-power applications.