A novel VAWT passive flow control numerical and experimental investigations: Guided Vane Airfoil Wind Turbine

Aboelezz, Ahmed; Ghali, Hani A.; Elbayomi, Gamal; Madboli, Mohamed

doi:10.1016/j.oceaneng.2022.111704

Cited by 26 publications

(4 citation statements)

References 27 publications

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“…It was decided to adopt a constant neuro-increasing ratio (r = 10). If the findings of the three neurons are reported as N1, N2, and N3, the relative error ( ε ) between them is defined in (Aboelezz et al 2022) as Equation ( 2) specifies the order of solution convergence (SC) based on the three neurons' numbers.…”

Section: Experiments Results and Artificial Neural Network Modellingmentioning

confidence: 99%

Electric vehicle battery charging framework using artificial intelligence modeling of a small wind turbine based on experimental characterization

Aboelezz

Makeen

Ghali

et al. 2022

Clean Techn Environ Policy

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The objective of this paper is to develop a generic electric vehicle battery charging framework using wind energy as the direct energy source. A robust model for a small vertical axis wind turbine based on an artificial neural network algorithm is used for predicting its performance over a wide range of operating conditions. The proposed framework can be implemented at any location worldwide where full prediction of the wind signature is perfectly obtained. In this paper, a small vertical axis wind turbine has been experimentally characterized at different operating conditions, where measured data, output power, and torque have been used to build the model. Once the model has been developed, the model is inserted into the MATLAB/Simulink software tool to predict the charging performance of a battery for an electric vehicle. An rpm controller has been used to achieve the maximum generated power from the wind turbine across the day with various wind speeds. Hence, the generated power is fed to the EV battery charger to implement the constant current constant voltage charging protocol. The charging current reached the desired value in a settling time of 4.5 s, whatever the intermittency of the wind energy. The proposed application of wind energy to EV provides sufficient constant power supported by the utility grid. Graphical Abstract

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Section: Experiments Results and Artificial Neural Network Modellingmentioning

confidence: 99%

Electric vehicle battery charging framework using artificial intelligence modeling of a small wind turbine based on experimental characterization

Aboelezz

Makeen

Ghali

et al. 2022

Clean Techn Environ Policy

Self Cite

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“…This phenomenon can be diminished by the method of flow control, which can be either activeby injection of fluid at the surface of the blade, or passivewhich results from varying the blade shape to take flow separation into account. Multiple solutions have been analysed regarding active [37,38]and passive flow control [39], either by creating cavities inside the blades [40], much like the novel VAWT geometry studied in this paper, or by mounting vortex generators on the extrados [41].The trapped vortex cavity offers the advantage of flow separation occurring inside of the cavity and reattach towards the end of the cavity. This leads to significantly diminish the wake area and constraining the vorticity region to the cavity, resulting in higher lift-todrag ratio [42,43].…”

Section: Introductionmentioning

confidence: 99%

High-precision numerical investigation of a VAWT starting process

MĂLĂEL,

STRĂTILĂ

2023

Preprint

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For both conventional and renewable energy conversion processes, computational fluid dynamics (CFD) has been used to address more energy-related challenges in recent decades. Using CFD to investigate vertical-axis wind turbines has become more common in recent years. The main goals of this application have been to more accurately predict the turbine's performance and to comprehend the complicated nature of the complex turbulent flow. The Vertical Axis Wind Turbine (VAWT) simulation for energy-generating applications has several intricate components. One of them is being aware of the chaotic flow that occurs during the first stages of the starting process, which influences overall effectiveness. In this article, the performance of the wind turbine was increased by using a passive flow control approach. The numerical research was carried out using Large Eddy Simulation for four alternative tip speed ratios in both cases, the classic and the optimized, equipped with a vortex trap on the exterior of the blades. The power and torque coefficient variations, as well as the velocity magnitude contours, show that the starting process may begin with a significant improvement in efficiency when flow control is used.

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“…Optimization of the airfoil distribution, chord and thickness distribution, or twist angle can play a major role in a wind turbine's performance. Flow control methods can be useful as well, slots, slats, or other turbulence-generating surfaces can improve the aerodynamics of a wind turbine [20][21][22].…”

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confidence: 99%

Wind Turbine Blade Dynamics Simulation under the Effect of Atmospheric Turbulence

Ismaiel

2022

Emerg Sci J

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Wind energy is one of the fastest growing sources of renewable energy because of its cleanliness and sustainability. Due to the turbulent nature of wind, a wind turbine experiences severe dynamic loading and faces the danger of fatigue failure. In addition, severe blade deflections imply failure by tower strikes. For this reason, the study of blade deflections under different turbulence conditions is of high importance. In this work, a wind turbine’s blade is simulated under different turbulent conditions. Four different wind fields are generated with a mean wind velocity of 12 m/s and turbulence intensities of 1, 10, 25, and 50%. The blade deflections are calculated in the out-of-plane and in-plane directions as a time-marching series with different blade azimuth positions. The higher the turbulence intensity, the severer the fluctuations of the deflections around its mean value. For the 50% turbulence intensity, the standard deviation of the out-of-plane deflection is 600% larger than that of the 1% turbulence intensity case. The maximum deflections increase significantly as well. A maximum of 3.78 m of out-of-plane tip deflection leads to the danger of a tower strike. And a positive tip deflection of 0.07 m in the in-plane direction indicates that the blade goes against its natural behavior and against the inertial loads while rotating. Continuous monitoring of wind conditions is a must, to put the turbine on brake in cases of gusts and severe turbulence. In areas of high turbulence, downwind turbines can provide a better alternative to allow blade deflections without the danger of tower strikes. Doi: 10.28991/ESJ-2023-07-01-012 Full Text: PDF

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A novel VAWT passive flow control numerical and experimental investigations: Guided Vane Airfoil Wind Turbine

Cited by 26 publications

References 27 publications

Electric vehicle battery charging framework using artificial intelligence modeling of a small wind turbine based on experimental characterization

Electric vehicle battery charging framework using artificial intelligence modeling of a small wind turbine based on experimental characterization

High-precision numerical investigation of a VAWT starting process

Wind Turbine Blade Dynamics Simulation under the Effect of Atmospheric Turbulence

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