Improved Backstepping Control of a DFIG based Wind Energy Conversion System using Ant Lion Optimizer Algorithm

Zeghdi, Zoubir; Barazane, L.; Bekakra, Youcef; Larabi, Abdelkader

doi:10.3311/ppee.18716

Cited by 15 publications

(5 citation statements)

References 42 publications

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“…Its object is to reach the zero error convergence, hence, stabilization and equilibration of the system so that the outputs track a reference set point. For this, the active and reactive power of the DFIG is regulated to use the BSC, where the BSC design is based on the FOC with the technique will be applied in the direct and quadratic axes [21,22].…”

Section: Dfig Vector Control and Modeling: W R = W S − W = Gw Smentioning

confidence: 99%

A High Robust Optimal Nonlinear Control with MPPT Speed for Wind Energy Conversion System (WECS) Based on Doubly Fed Induction Generator (DFIG)

Mebkhouta,

Golea,

Boumaraf

et al. 2023

Period. Polytech. Elec. Eng. Comp. Sci.

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As part of efforts to improve wind energy production using a doubly fed induction generator (DFIG), this paper presents modeling with power maximization through control of speed (MPPT) and control of stator active and reactive power for doubly fed induction generator. The quality of the generated energy and the performance of wind energy conversion systems (WECS) based on DFIG are affected by uncertainties and external disturbances. Therefore, the system requires high-performance control under the nonlinearity influence and the applied external disturbances. This work provides a new contribution and approach that combines nonlinear control (Backstepping) and optimal control (LQR). Backstepping control has been applied to give a good performance using nonlinear strategy and stability condition, but its main drawback is that it is relatively robust for sudden changes in wind speed or any external disturbances as well as it is sensitive against the uncertainties, which may lead to a chattering and an instability as well as overshoot or undershoot. To overcome the problems mentioned above the optimal control (LQR) has been applied to address this drawback in nonlinear control. Furthermore, it, the hybrid approach of Backstepping and LQR control resulting a robust control under the hardest scenarios during the wind system operating as well as provides a good performance in terms of chattering, stability and other performance characteristics which help to produce a high-quality energy. Overall, integrating LQR control with Backstepping can lead to a more powerful, flexible, and efficient control system with improved performance and reduced computational complexity.

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Section: Dfig Vector Control and Modeling: W R = W S − W = Gw Smentioning

confidence: 99%

A High Robust Optimal Nonlinear Control with MPPT Speed for Wind Energy Conversion System (WECS) Based on Doubly Fed Induction Generator (DFIG)

Mebkhouta,

Golea,

Boumaraf

et al. 2023

Period. Polytech. Elec. Eng. Comp. Sci.

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“…Techniques THD (%) [37] Field-oriented control with PI controllers 0.77 Super twisting algorithm (STA) 0.28 [38] Fuzzy DTC strategy 2.40 [39] Fractional-order sliding mode control 1.31 [40] Integral SMC technique 9.71 Multi-resonant-based sliding mode controller (MRSMC) 3.14 [41] Backstepping control 2.19 [6] Field-oriented control 3.7 [12] DPC control with PI controllers 0.46 DPC control with terminal synergetic controllers 0.25 [42] Direct torque control with second-order continuous SMC technique 0.78 [28] DPC control with integral-proportional controllers 0.43 [9] DFOC control with PI controllers 1.45 DFOC control with synergetic-SMC technique 0.50 Table 6. Cont.…”

Section: Referencesmentioning

confidence: 99%

Simplified Super Twisting Sliding Mode Approaches of the Double-Powered Induction Generator-Based Multi-Rotor Wind Turbine System

et al. 2022

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This work proposes a new indirect filed-oriented control (IFOC) scheme for double-powered induction generators (DPIGs) in multi-rotor wind turbine systems (MRWTS). The IFOC strategy is characterized by its simplicity, ease of use, and fast dynamic speed. However, there are drawbacks to this method. Among its disadvantages is the presence of ripples in the level of torque, active power, and current. In addition, the total harmonic distortion (THD) value of the electric current is higher compared to the direct torque control method. In order to overcome these shortcomings and in terms of improving the effectiveness and performance of this method, a new algorithm is proposed for the super twisting algorithm (STA). In this work, a new STA method called simplified STA (SSTA) algorithm is proposed and applied to the traditional IFOC strategy in order to reduce the ripples of torque, current, and active power. On the other hand, the inverter of the DPIG is controlled by using a five-level fuzzy simplified space vector modulation (FSSVM) technique to obtain a signal at the inverter output of a fixed frequency. The results obtained from this proposed IFOC-SSTA method with FSSVM strategy are compared with the classical IFOC method which uses the classical controller based on a proportional-integral (PI) controller. The proposed method is achieved using the Matlab/Simulink software, where a generator with a large capacity of 1.5 megawatts is used. The generator is placed in a multi-rotor electric power generation system. On the other hand, the two methods are compared in terms of ripple ratio, dynamic response, durability, and total harmonic distortion (THD) value of the electric current. Through the results obtained from this work, the proposed method based on SSTA provided better results in terms of ripple ratio, response dynamic, and even THD value compared to the classical method, and this shows the robustness of the proposed method in improving the performance and efficiency of the generator in the multi-rotor wind system.

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“…The mathematical-model of the DFIG in the (𝑑 − 𝑞) frame is presented in the following equations. The stator and the rotor voltages are given by the following equations [19][20][21]:…”

Section: Modelling Of Dfigmentioning

confidence: 99%

Archives of Electrical Engineering

2022

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The paper proposes a new robust fuzzy gain adaptation of the sliding mode (SMC) power control strategy for the wind energy conversion system (WECS), based on a doubly fed induction generator (DFIG), to maximize the power extracted from the wind turbine (WT). The sliding mode controller can deal with any wind speed, ingrained nonlinearities in the system, external disturbances and model uncertainties, yet the chattering phenomenon that characterizes classical SMC can be destructive. This problem is suitably lessened by adopting adaptive fuzzy-SMC. For this proposed approach, the adaptive switching gains are adjusted by a supervisory fuzzy logic system, so the chattering impact is avoided. Moreover, the vector control of the DFIG as well as the presented one have been used to achieve the control of reactive and active power of the WECS to make the wind turbine adaptable to diverse constraints. Several numerical simulations are performed to assess the performance

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Improved Backstepping Control of a DFIG based Wind Energy Conversion System using Ant Lion Optimizer Algorithm

Cited by 15 publications

References 42 publications

A High Robust Optimal Nonlinear Control with MPPT Speed for Wind Energy Conversion System (WECS) Based on Doubly Fed Induction Generator (DFIG)

A High Robust Optimal Nonlinear Control with MPPT Speed for Wind Energy Conversion System (WECS) Based on Doubly Fed Induction Generator (DFIG)

Simplified Super Twisting Sliding Mode Approaches of the Double-Powered Induction Generator-Based Multi-Rotor Wind Turbine System

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