Abdel Ghani Aissaoui

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.

This study focuses on the implementation of Quantitative Feedback Theory (QFT) for the robust speed control of a Switched Reluctance Motor (SRM). QFT, introduced by Isaac Horowitz, represents a frequency-domain robust control design methodology that systematically addresses plant uncertainties and external disturbances within a predefined performance framework. Unlike traditional control strategies that are typically based on a nominal plant model, QFT explicitly considers an uncertainty set of plant models, enabling the controller to guarantee robustness and stability across all possible system variations. The proposed QFT-based control design for the SRM effectively enhances the dynamic response, disturbance rejection capability, and robust stability margins. Comparative simulation and experimental results demonstrate that the QFT controller achieves superior speed regulation, faster transient response, and greater robustness against parameter variations and load disturbances, when compared with the conventional Proportional–Integral (PI) control strategy.

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.

This study aims to propose a robust hybrid sliding mode artificial neural network control (SM-ANN) scheme for controlling the stator power (active/reactive) of a doubly fed induction generator (DFIG)-based direct drive vertical axis wind turbine (VAWT) power system under a real-world scenario wind speed that will be installed in the Adrar region (Saharan zone) of Algeria. The SM-ANN scheme will control the stator power of the direct drive VAWT power. The chattering phenomenon is the most significant disadvantage associated with sliding mode control (SMC). In order to find a solution to this issue, the artificial neural network (ANN) method was applied to pick the appealing part of the SMC. MATLAB/Simulink is used to do an evaluation, after which the SM-ANN controller being suggested is compared to both traditional sliding mode (SM) and proportional-integral (PI) controllers. The results of the simulation demonstrated that the recommended SM-ANN controller has good performance in terms of enhancing the quality of energy that is delivered to the power network. This is in comparison to the traditional SM and PI controllers, which both have a long history of use. Notwithstanding the fact that there is DFIG parameter fluctuation present.

This paper proposes a method of sliding mode control (SMC) approach for excitation control in a single generator-infinite bus power system. Conventional power system stabilizer (C-PSS) design becomes a complicated problem in presence of internal and external disturbances to the excitation of a power system. Improving the stability of the power system has become a priority objective. The aim of this work is to ensure maximum damping of the electromechanical oscillations of the Single Machine Infinity Bus System (SMIB) by the power stabilizers based on the sliding mode control technique. The effectiveness of the proposed approach is demonstrated through computer simulations on two different cases of operating conditions. The performance of the proposed approach is evaluated in terms of damping power system oscillations. The obtained results show the high performance of the proposed controller to improve the stability of the power system compared to the C-PSS and found to be impressive.

This paper presents a study of modelling and control of doubly fed induction generator for use on wind power system, the object is controlling and keeping decoupling between active and reactive power of DFIG, through to applied the DTC control at the torque and flux loop in order to achieve a better quality of energy and to make the system insensitive to disturbances

In this paper, a hybrid power system is proposed to eliminate any interruption caused to absence of power supply network by the Fusion between the wind source and the photovoltaic source to create a hybrid system with internal power supply autonomy. The hybrid power system includes a solar and wind source whose wind energy conversion system is based on a doubly fed induction generator. The photovoltaic conversion system extracts the maximum power from the sun. A part of this power is used to supply the rotor of a doubly fed induction generator; the rest is injected in the grid. The connection between the two conversion systems is made by means of static converters (chopper/inverter). In the photovoltaic conversion chain, a controller for tracking the maximum power point is designed using the direct search approach the Perturb and observe method. The wind energy conversion system contains a doubly fed asynchronous generator with a control system of generated powers by the technique of the fuzzy logic. The simulation was done to prove the validity of the strategy and of the control method used for the control of the power generated by the hybrid system.

This paper presents the robust control H-infinity (H _∞ ) of active power and reactive power of doubly fed induction generator (DFIG) for used on wind energy system. The study consists in presenting in brief the DFIG model and the main tools of H _∞ theory for designing a robust controller of active and reactive power, which achieved a satisfying robustness in dynamic performances, then it is applied to the control of DFIG. The simulation results prove that the application of H _∞ controller for active power and reactive power, given the high robustness in dynamic performance. however, the electrical and mechanical parameters uncertainty is large.

The objective of this article is to model and analyze wind turbine system' performance using Petri nets. Unit's degradation states were modeled and incorporated in the global system. Besides, preventive and corrective maintenance activities were added. Results were given using Monte Carlo simulation on the Petri nets (PN). This study shows the efficiency of using PN to model and analyze power system performance.