A Comparative Analysis of Some Methods for Wind Turbine Maximum Power Point Tracking

Voloşencu, Constantin

doi:10.3390/math9192399

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…Several maximum power point (MPP) extraction techniques have been proposed in the literature [24][25][26][27][28][29][30]. It can be divided into indirect and direct MPPT methods [31,32].…”

Section: Introductionmentioning

confidence: 99%

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Dahmane,

Boulaoutaq,

Bouachrine

et al. 2023

Journal of Robotics and Control

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In the field of wind turbine performance optimization, many techniques are employed to track the maximum power point (MPPT), one of the most commonly used MPPT algorithms is the perturb and observe technique (PO) because of its ease of implementation. However, the main disadvantage of this method is the lack of accuracy due to fluctuations around the maximum power point. In contrast, MPPT control employing neural networks proved to be an effective solution, in terms of accuracy. The contribution of this work is to propose a hybrid maximum power point tracking control using two types of MPPT control: neural network control (NNC) and the perturbation and observe method (PO), thus the PO method can offer better performance. Furthermore, this study aims to provide a comparison of the hybrid method with each algorithm 𝑃𝑂 and NNC. At the resulting duty cycle of the 2 methods, we applied the combination operation. A DC-DC boost converter is subjected to the hybrid MPPT control. This converter is part of a wind energy conversion system employing a permanent magnet synchronous generator (PMSG). The chain is modeled using MATLAB/Simulink software. The effectiveness of the controller is tested at varying wind speeds. In terms of the Integral time absolute error (ITAE), using the PO technique, the ITAE is 9.72. But, if we apply the suggested technique, it is smaller at 4.55. The corresponding simulation results show that the proposed hybrid method performs best compared to the PO method. Simulation results ensure the performance of the proposed hybrid MPPT control.

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“…Several maximum power point (MPP) extraction techniques have been proposed in the literature [24][25][26][27][28][29][30]. It can be divided into indirect and direct MPPT methods [31,32].…”

Section: Introductionmentioning

confidence: 99%

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Dahmane,

Boulaoutaq,

Bouachrine

et al. 2023

Journal of Robotics and Control

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“…Concurrently, China's power system is undergoing a remarkable transformation towards a new energy paradigm, wherein new energy sources take center stage. Within this context, wind power, being one of the strategically developed renewable energy sources in China, has garnered special attention [2] .…”

Section: Introductionmentioning

confidence: 99%

Maximum Power Point Tracking Based on Wind Speed Prediction

Peng,

Wang,

Xie

et al. 2023

J. Phys.: Conf. Ser.

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A control method for MPPT (maximum power point tracking) based on wind speed prediction is proposed to address the issue of slow attainment of optimal speed values by wind turbines in variable wind speed conditions in the wind power system. Initially, the wind speed variation value is accurately estimated using the SSA-BP neural network based on historical wind speed data. Subsequently, the MPP (maximum power point) is calculated considering the optimal blade-tip speed ratio, thereby enhancing the tracking speed of the system. Simulation results demonstrate that this method enables real-time estimation of wind speed variation, improves wind energy utilization rate, and maximizes the utilization of wind energy.

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“…The tremendous technological developments recorded in recent years have played a major and important role in increasing wind power and making use of one of the most exploited renewable energies in the world, especially in advanced industrialized countries [1,2]. This development has been accompanied and contributed by many research teams in different countries around the world, where numerous articles have been published in important scientific journals [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

“…(2) increases the robustness and stability of the controlled system; (3) provides a simple and less complex method to be used to control complex systems; (4) improves the THD value of the rotor and stator currents; (5) improves the performance and effectiveness of the traditional DPC strategy; (6) simplifies the use of the slide mode control technique.…”

Section: Introductionmentioning

confidence: 99%

Direct Power Control Based on Modified Sliding Mode Controller for a Variable-Speed Multi-Rotor Wind Turbine System Using PWM Strategy

et al. 2022

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A robust and improved control scheme of a variable speed multi-rotor wind turbine (MRWT) system with a doubly fed asynchronous generator (DFAG) is displayed in this work. In order to improve the performances and effectiveness of the traditional direct power control (DPC) strategy of the DFAG, a new kind of sliding mode controller (SMC) called modified SMC (MSMC) is proposed. The most important advantage of the DPC-MSMC strategy is to reduce the power ripples and improve the quality of the currents provided to the grid. In addition, to control the rotor inverter, a pulse width modulation (PWM) technique is used. The proposed DPC-MSMC strategy was modeled and simulated using MATLAB/Simulink software. The simulation results showed that the ripples in stator currents, active and reactive powers and torque were considerably reduced for the proposed DPC-MSMC strategy compared to the traditional DPC. Additionally, the proposed DPC-MSMC method works excellently to reduce the total harmonic distortion (THD) of the stator current in the case of variable wind speed. On the other hand, a robustness test against parametric variations showed and confirmed the robustness of the proposed technique compared to the classical method.

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A Comparative Analysis of Some Methods for Wind Turbine Maximum Power Point Tracking

Cited by 7 publications

References 15 publications

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System

Maximum Power Point Tracking Based on Wind Speed Prediction

Direct Power Control Based on Modified Sliding Mode Controller for a Variable-Speed Multi-Rotor Wind Turbine System Using PWM Strategy

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