Abdesselam Bouiri

The main objective of this article is to adapt an independent power supply system to optimize the energy production of a wind turbine and thus eliminate power outages on the electrical grid when supplying power to the rotor of a doubly-fed induction generator (DFIG). This system uses a permanent magnet synchronous generator (PMSG) to supply power to the DFIG rotor and offers robust control, comparing PI and sliding mode control methods as a function of varying reference parameters. We begin by presenting the dynamic model of the wind turbine connected to the various generators, followed by the electrical model of the PMSG and DFIG with the control strategy. Next, we explain the theory and mathematical equation of the AC/DC rectifier and the DC/AC inverter. Then, we present the PI controller and the sliding mode control method. Finally, simulation results comparing the PI and sliding mode control methods illustrate and demonstrate the performance and feasibility of this system.

Objective: The objective of this paper is to adapt the Zebra Optimization Algorithm (ZOA) to track the Global Maximum Power Point (GMPP) of a PV system when subjected to partial shading conditions. Theoretical Framework: Photovoltaic (PV) systems are increasingly being used due to their clean nature and low maintenance cost. However, solar cells exhibit a nonlinear relationship between current and voltage, which necessitates the use of Maximum Power Point Tracking (MPPT) algorithms to ensure the system operates at its full potential. Bypass diodes are integrated into PV modules to protect solar cells from damage during partial shading, but this leads to a distorted multi-peak Power-Voltage (P-V) curve. This distortion presents a challenge for algorithms to distinguish between Global Maximum Power Point (GMPP) and Local Maximum Power Points (LMPPs). Method: The Zebra Optimization Algorithm (ZOA) is applied to track the GMPP of a PV system under partial shading conditions. Simulations were conducted using the MATLAB/Simulink platform to evaluate the algorithm’s performance. The focus was on ensuring fast and accurate tracking of the GMPPT under rapid changes in solar irradiance levels. Results and Discussion: Simulation results demonstrated that the ZOA-based MPPT algorithm effectively tracked the GMPPT of the PV system, even under rapid variations in solar irradiance. The algorithm proved its accuracy and speed in distinguishing the GMPP from LMPPs, addressing the challenges posed by the distorted P-V curve. Research Implications: The successful application of the ZOA for tracking the GMPP in partial shading conditions offers a significant improvement for PV systems. This can lead to enhanced efficiency in energy production and more reliable performance in real-world scenarios, where shading and other environmental factors frequently affect solar panels. Originality/Value: This study introduces the adaptation of the Zebra Optimization Algorithm (ZOA) in MPPT for PV systems, addressing the issue of distinguishing between GMPP and LMPPs under partial shading. The approach demonstrates both innovation and practical value in improving the efficiency of PV systems in challenging environmental conditions.

The purpose of this paper is the elimination of interruptions of electrical energy produced by a multi-source production system, so we have assured the feed of DFIG rotor in a wind system by different energy sources (photovoltaic generator, battery group) and switchover between them by auxiliary contacts controlled by a supervisor via a power control algorithm. For the photovoltaic generator, a controller for tracking the maximum power point is designed using direct search approach perturb observe method. For the battery group, the installation of a number of the capacitor battery elements in series and in parallel will be kept the power necessary to supply the DFIG rotor. For the wind system, it contains the power generated by DFIG is controlled by sliding mode system. With regard to switching between electrical energy sources, our proposed system relies on an algorithm to compare the energies produced by each generator with the energy required to feed the DFIG rotor and the energies consumed in the system, where the energy source with high production energy and available is exploited to feed the system and charge the batteries. Simulations were performed to confirm the reliability and efficacy of the system proposed.

In order to control the output power of wind application (WA) based on doubly fed induction generator (DFIG). The simple control (SC) strategy based on approaches via flux orientation and neglecting resistance (FOANR) to decoupled axes is the most common used in many previous studies, However this strategy FOANR present a linear synthesis, mainly to control DFIG simple model sensitive to internal and external disturbances, This research paper contribute to developed a robust new full control (FC) strategy based on substitution method (SM) to solving nonlinear coupled axes without FOANR to control nonlinear DFIG model, we use a proportional-integral (PI) controller by the most efficient method: indirect with double loop on each axis to control powers generated by DFIG and stator current directly, we check its performance and efficient compared to the same controller based on flux FOANR against DFIG nonlinear model.