This paper presents an implementation of a new robust control strategy based on an interval type-2 fuzzy logic controller (IT2-FLC) applied to the wind energy conversion system (WECS). The wind generator used was a variable speed wind turbine based on a doubly fed induction generator (DFIG). Fuzzy logic concepts have been applied with great success in many applications worldwide. So far, the vast majority of systems have used type-1 fuzzy logic controllers. However, T1-FLC cannot handle the high level of uncertainty in systems (complex and non-linear systems). The amount of uncertainty in a system could be reduced by using type-2 fuzzy logic since it offers better capabilities to handle linguistic uncertainties by modeling vagueness and unreliability of information. A new concept based on an interval type-2 fuzzy logic controller (IT-2 FLC) was developed because of its uncertainty management capabilities. Both these control strategies were designed and their performances compared for the purpose of showing the control most efficient in terms of reference tracking and robustness. We made a comparison between the performance of the type-1 fuzzy logic controller (T1-FLC) and interval type-2 fuzzy logic controller (IT2-FLC). The simulation results clearly manifest the height robustness of the interval type-2 fuzzy logic controller in comparison to the T1-FLC in terms of rise time, settling time, and overshoot value. The simulations were realized by MATLAB/Simulink software.

This paper proposes a new hybrid controller based MPPT. This one is composed of the Artificial Neural Network and Integral Feedback Linearization Controller (ANN-IFLC). The ANN is used to produce the reference of optimal voltage that corresponds to the maximal power. While the IFLC is designed to track the voltage reference. The integral action is added to ensure zero-static error. Then, a comparison between different existing Maximum Power Point Tracking (MPPT) techniques, which are divided between the classical algorithms and the hybrid controllers, is made. The classical algorithms, treated in this study, are the Perturb and Observe (P & O) and Incremental Conductance (INC). While the hybrid controllers are INC-BSC, P & O-BSC, ANN-ISMC, ANN-BSC, and ANN-IFLC. As can be noticed, these controllers present the combination between the nonlinear controllers and the Artificial Neural network (ANN) or the classical algorithms (P & O and INC). Effectively, the nonlinear controllers used are the Sliding Mode Controller (SMC), the Integral Sliding Mode Controller (ISMC), the Backstepping Controller (BSC) and the proposed IFL Controller. The proposed photovoltaic system consists of the photovoltaic module (Reference: S6M2G240), of the Boost converter and the resistive load. The MPPT techniques are tested using Matlab software. The results show that the hybrid controllers characterize by the tracking performances better than the classical methods. Moreover, the Artificial Neural Network predicts quickly and accurately the Maximum Power Point (MPP) under uniform meteorological conditions. Also, the PV voltage produced, using IFLC or ISMC, has fewer oscillations around its optimum thanks to the integral action added.

This paper proposes a robust fuzzy logic method based on the Takagi-Sugeno fuzzy controller model. In fact, this oneis designedin order tocontrol a Doubly-Fed Induction Generator (DFI-Generator) forthe variable wind speedturbine. On the one hand, the main aim of the proposed strategy isthereal-time tracking of optimal operating point, extracting the maximum output power, and controlling the pitch. This later is applied in order to limit the output power of the system to its nominal value. On the other hand, the proposed controller can extract the maximum of power under variable wind speed. While the existing methods deals with the case of the fixed wind speed. Thus, in this case, the controller can diverge and cause considerable drop of power, whenever the wind speed is changed.Moreover,the proposed control strategy canincrease the efficiency and improve the tracking performance of the system. The model is established based on the Parallel Distributed Compensationtechnique. The stability and tracking analysis properties are ensured by using the Lyapunov approach theory. In addition, the feedback gains of the strategy controller proposed are determined by Linear Matrix Inequalities. A numerical simulation is carried out under Matlab software for comparing the proposed Takagi-Sugeno fuzzy controller with the conventional PI controller. Effectively, these both controllers are applied to controlling the efficiency of the 3 MW DFI-Generator based on Wind Energy Conversion Systemin order to testtheir tracking performances and robustness against rapid changes of the reference signal and for testing the proposed controller strategy as well. Indeed, the simulation results prove the robustness of the proposed controller and show the drawbacks of PI controller, which makes high overshoot under the rapid changes of the reference that can reach 20Ain the worst cases. While, the proposed controller strategy tracks rapidly accurately and without any overshoot,the reference signal.

Wind energy becomes recognized as a resource for sustainable electrical power generation. However, the main challenge for this kind of energy development is to minimize the operation costs and maintenance operations in the wind harsh environment. These worries are justified by the incident high rates on offshore wind turbine systems. Wind energy turbines are characterized by a very difficult access for regular or emergency maintenance operations. This is why the development of fault tolerant system is a key feature. This paper deals with the use of a PM five phase wind turbine generator. With this kind of system, it is possible to maintain the power production even if an electrical fault appears in the power converter. This system is associated with an optimal strategy of torque/speed control using a vector control. This approach is evaluated in this study in the healthy and faulty operation modes.

In studies of the conversion of wind energy to variable speed, this article proposes a simplified method based on electronics to inject the energy produced in the public electricity network. To reduce the effects of harmonies resulting from commutations, an algorithm of control of active and reactive power is used, but the constraint of WECS is the slow speed of the synchronous permanent magnet generator (PMSG). The strategy of vectorial control on decoupling by singular perturbations was chosen for this work. In our study, the control of the speed and current of PMSG are discussed. Results of simulation are given to show the effectiveness and the performance of the system.

This paper proposes an accurate photovoltaic emulator using the Sepic converter controlled by a nonlinear controller. This emulator is able to reproduce the current/voltage characteristics as a function of weather conditions. In fact, the backstepping controller is designed to control the output current of the Sepic converter, while a modeled PV module is used to generate the reference of current. The modeling of the PV module is carried out by applying an analytic method, this method can identify the five unknown parameters, which are the series and parallel resistors $(R_{s},R_{sh})$, the ideality coefficient a, the reverse current I s0 and the photocurrent I ph0 . Also, by using this method, it is possible to obtain an accurate mathematical model of any PV module by just introducing the information given in the datasheet. So, using the mathematical model with the identified parameters, the proposed PV emulator can mimic perfectly the characteristics of any PV model. The performances of the proposed PV emulator were tested and validated under the Matlab/Simulink environment. Also, the proposed controller is implemented on the Raspberry Pi 3 board and evaluated using the processor-in-the-loop test technique. According to the results, the proposed PV emulator is accurate and gives characteristics similar to those shown in the datasheet.