Assessment of optimum tip speed ratio in wind turbines using artificial neural networks

Yurdusev, Mehmet Ali; Ata, Raşit; Çetin, Numan Sabit

doi:10.1016/j.energy.2005.09.007

Cited by 75 publications

(42 citation statements)

References 8 publications

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“… Tip losses  Wake effects  Drive train efficiency losses  Blade shape simplification losses Therefore, the maximum theoretical efficiency has yet to be achieved [9]. Over the centuries many types of design have emerged, and some of the more distinguishable are listed in Table 2.…”

Section: Practical Efficiencymentioning

confidence: 99%

Wind Turbine Blade Design

2012

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A detailed review of the current state-of-art for wind turbine blade design is presented, including theoretical maximum efficiency, propulsion, practical efficiency, HAWT blade design, and blade loads. The review provides a complete picture of wind turbine blade design and shows the dominance of modern turbines almost exclusive use of horizontal axis rotors. The aerodynamic design principles for a modern wind turbine blade are detailed, including blade plan shape/quantity, aerofoil selection and optimal attack angles. A detailed review of design loads on wind turbine blades is offered, describing aerodynamic, gravitational, centrifugal, gyroscopic and operational conditions.

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Section: Practical Efficiencymentioning

confidence: 99%

Wind Turbine Blade Design

2012

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“…In case of small scale wind turbine, tip speed ratio range 4 to 10 is recomended to maintain. According to the emperical relation between coefficient of performance and tip speed ratio, introduced by Cetin [14], the designed tip speed ratio was selected. The proposed wind turbine fundamental design parameters and operating conditions are given in Table 1.…”

Section: Rotor Parametersmentioning

confidence: 99%

Theoretical Analysis of Ignition in Diesel Engines

Alshahrani¹

2017

JPEE

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The present work is based on the comparative study between "Blade-ElementMomentum" (BEM) analysis and "Computational-Fluid-Dynamics" (CFD) analysis of small-scale horizontal axis wind turbine blade. In this study, the pitch is considered as fixed and rotor speed is variable. Firstly, the aerodynamic characteristics of three different specialized airfoils were analyzed to get optimum design parameters of wind turbine blade. Then BEM was performed with the application of the open source wind turbine design and performance computation software Q-Blade v0.6. After that, CFD simulation was done by Ansys CFX software. Here, k-ω "Shear-Stress-Transport" (SST) model was conducted for three-dimensional visualization of turbine performance. However, the best coefficient of performance was observed at 6˚ angle of attack. At this angle of attack, in the case of BEM, the highest coefficient of performance was 0.47 whereby CFD analysis, it was 0.43. Both studies showed good performance prediction which was a positive step to accelerate the continuous revolution in wind energy sector.

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“…In [34], [38] and [39] neural networks are used to assess the TSR, in [40] growing neural gas learning method is used to improve MPPT controller, while in [41] and [42] TSR method based on fuzzy logic is presented.…”

Section: Tip Speed Ratio (Tsr)mentioning

confidence: 99%