Integral sliding mode control for DFIG based WECS with MPPT based on artificial neural network under a real wind profile

Wind speed variations affect the performance of the wind energy conversion systems (WECSs) negatively. This paper addressed an advanced law of the backstepping controller (ABC) for enhancing the integration of doubly fed induction generator (DFIG)-based grid-connected WECS under wind range of wind speed. This enhancement was achieved through three control schemes, which were blade pitch control, rotor-side control, and grid-side control. The blade pitch control was presented to adjust the wind turbine speed when the wind speed exceeds its rated value. In addition, the rotor and grid-side converter controllers were presented for improving the direct current link voltage profile and achieving maximum power point tracking (MPPT) under speed variations, respectively. To evaluate the effectiveness of the proposed ABC control, a comparison between PI and sliding-mode control (SMC) was presented, considering the parameters of a 1.5 MW DFIG wind turbine in the Assilah zone in Morocco. Moreover, some changes in the DFIG parameters were introduced to investigate the robustness of the proposed controller under parameter uncertainties. Simulation results showed the capability of the proposed ABC controller to enhance the performance of the DFIG-WECS based on variable speed and variable pitch turbine, at both below and above-rated speed, leading to an error around 10−3 (p.u), with an ATE = 0.4194 in the partial load region; in terms of blade pitch control, an error of 2.10−4 (p.u) was obtained, and the DC-link voltage profile showed a measured performance of 5 V and remarkable THD value reduction compared to other techniques, with a measured THD value of 2.03%, 1.67%, and 1.46% respectively, in hyposynchronous, hypersynchronous, and pitch activation modes of operation. All simulations were performed using MATLAB/SIMULINK based on real wind profiles in order to make an exhaustive analysis with realistic operating conditions and parameters.

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Nonlinear Control Strategies for Enhancing the Performance of DFIG-Based WECS under a Real Wind Profile

Developing precise and robust algorithms that can help in obtaining maximum power yield in a variable speed wind turbine is an important area of research in wind engineering. The present manuscript proposes a technique that utilizes a second-generation CRONE controller for the maximum power tracking technique (MPPT) to maximize power generation in a wind energy conversion system (WECS) based on a double-fed induction generator (DFIG). The authors propose this novel method because the classical controllers cannot provide adequate performance in terms of extracting the maximum energy from variable speed wind turbines when applying a real wind profile and they cannot guarantee the high stability of the WECS. Moreover, this novel controller sufficiently handles problems related to the control effort level. The performance of the second-generation CRONE method was mathematically modeled using MATLAB/Simulink and compared with four other types of MPPT control techniques, which include a proportional-integral linear controller (PI), nonlinear sliding mode controller (SMC), backstepping controller (BS), and fuzzy logic controller (FLC). Two different wind profiles, a step wind profile and a real wind profile, were considered for the comparative study. The response time, dynamic error percentage, and static error percentage were the quantitative parameters compared, and the qualitative parameters included set-point tracking and precision. This test demonstrated the superiority of the second-generation CRONE controller in terms of all of the compared parameters.

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Improving the Maximum Power Extraction from Wind Turbines Using a Second-Generation CRONE Controller

In this research paper, a nonlinear Backstepping controller has been proposed in order to improve the dynamic performance of a doubly fed induction generator (DFIG) based Wind Energy conversion System, connected to the grid through a back-to-back converter. Firstly, an overall modeling of proposed system has been presented. Thereafter, three control techniques namely backstepping (BSC), sliding mode (SMC) and field-oriented control (FOC) using a conventional PI regulator have been designed in order to control the stator active and reactive powers of the DFIG. In addition, the maximum power point tracking (MPPT) strategy has been investigated in this work with three mechanical speed controllers: BSC, SMC and PI controller with the aim of making a synthesis and a comparison between their performances to determine which of those three techniques is more efficient to extract the maximum power. Finally, a thorough comparison between the adopted techniques for the DFIG control has been established in terms of response time, rise time, total harmonic distortion THD (%) of the stator current, static errors and robustness. The effectiveness and robustness of each control approach has been implemented and tested under MATLAB/Simulink environment by using a 1.5 MW wind system model.

https://ijpeds.iaescore.com/index.php/IJPEDS/article/download/21241/13623

Performance improvement of the variable speed wind turbine driving a DFIG using nonlinear control strategies

The parametric variation of nonlinear systems remains a significant drawback of automatic system controllers. The Proportional–Integral(PI) and Proportional–Integral–Derivative (PID) are the most commonly used controllers in industrial control systems. However, with the evolution of these systems, such controllers have become insufficient to compete with the complexity of the systems. This problem can be solved with the help of artificial intelligence, and especially with the use of optimization algorithms, which allow for variable gains in PID controllers that adapt to parametric variation. This article presents an analytical and experimental study of the Direct Torque Control (DTC) of a Doubly-Fed Induction Motor (DFIM). The speed adaptation of the DFIM is achieved using a PID controller, which is characterized by overshoots in the speed and ripples in the electromagnetic torque. The Genetic Algorithm (GA) within the DTC shows very good robustness in speed and torque by reducing torque ripples and suppressing overshoots. The simulation of the GA-DTC hybrid control in MATLAB/Simulink confirms the improvement offered by this strategy. The validation and implementation of this strategy on the dSPACE DS1104 board are in good agreement with the simulation results and theoretical analysis.

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A New Robust Direct Torque Control Based on a Genetic Algorithm for a Doubly-Fed Induction Motor:Experimental Validation

The control algorithms to optimize power extraction in wind energy conversion systems are often designed by making some approximations and taking standard parameter values into consideration. This approach has proven inefficient as parameter variations and disturbances often degrade the robustness and power quality of the system. This paper proposes a simple-to-implement adaptive techniques to upgrade the efficiency and power quality of the system. Simulation results obtained on a 1.5 MW Doubly Fed Induction Generator (DFIG) are given and comparison is made against the performance of a PI-controller.

Optimization of DFIG Wind Turbine Power Quality Through Adaptive Fuzzy Control

The design of a control technique of doubly-fed induction generator (DFIG) for providing a high quality of energy, without harmonics accumulation, to the electrical grid is a real challenge because of the nonlinearity of the wind energy conversion system (WECS). In this paper, an improved robust command has been developed and then tested in order to control the rotor side converter (RSC) of the WECS. The main contribution of this research work is to optimize the extraction of the wind energy in the real circumstances and to push the DFIG working properly, with the highest performance and robustness, in the different operation modes. Therefore, the dynamic model of the turbine has been presented in this research paper, also the hybrid Direct Power Control-Backstepping (DPC-BS) command is highlighted. Matlab/Simulink simulations analysis, with the real parameters of the turbine and the real wind profile of Dakhla-Morocco city, confirm the high accuracy, the high performance and the robustness of the proposed method, which based on the the combination between the Direct Power Control (DPC) and the Backstepping controller. Moreover, the obtained results prove, despite the variable wind speed, the validation of the developed command with a total harmonic distortion THD ~0.33% and a null overshoot for the grid currents with a frequency of 50 Hz, which gives the possibility of injection into the electrical grid.

Improved Hybrid Control Strategy of the Doubly-Fed Induction Generator Under a Real Wind Profile

The conception of a control strategy of Doubly-Fed Induction Generator (DFIG) for providing a high quality of energy, without harmonic accumulations, to the electric network is a real challenge because of the no-linearity of the system and the variable wind speed. In this work, two commands based on two technics have been developed and then tested in order to control the system and the grid powers, respectively. Note that the main purpose of the control laws is to optimize the extraction of the wind energy in a real context and to push the DFIG working properly with the best performance in both static and dynamic modes. Therefore, the dynamic model turbine has been presented in this paper, also the FOC (Field Oriented Control) and the adaptive Backstepping commands are highlighted. Matlab/Simulink simulations analysis, with real parameters of the turbine and real wind profile of Dakhla-Morocco city, confirm the high accuracy of the adaptive Backstepping command, based on the Lyapunov stability technique, with a total harmonic distortion THD ~0.16%.

Mourad Yessef

Papers

Nonlinear Control Strategies for Enhancing the Performance of DFIG-Based WECS under a Real Wind Profile

Optimization of DFIG Wind Turbine Power Quality Through Adaptive Fuzzy Control

Improving the Maximum Power Extraction from Wind Turbines Using a Second-Generation CRONE Controller

Improved Hybrid Control Strategy of the Doubly-Fed Induction Generator Under a Real Wind Profile

Evaluation of Adaptive Backstepping Control Applied to DFIG Wind System Used on the Real Wind Profile of the Dakhla-Morocco City