Applied Aerodynamics of Wind Power Machines

Wilson, Robert E.; Lissaman, P. B. S.

doi:10.4324/9781315793245-89

Cited by 78 publications

(41 citation statements)

References 1 publication

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“…The BEM theory is, then, fully defined by applying the Glauert correction for high values of a (see Hansen 55 ) and can also be extended adding root losses, 31 estimating properly the aerodynamic coefficients, induction factors and angle of attack for each blade element. According to Burton et al, 31 Wilson and Lissaman 56 argue that the drag coefficient should not be included in the calculus of the normalized coefficients.…”

Section: Orcidmentioning

confidence: 99%

Optimal design of passive‐adaptive pendulum tuned mass damper for the global vibration control of offshore wind turbines

et al. 2020

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This paper presents an optimal design procedure for a pendulum tuned mass damper (PTMD) to mitigate the global structural vibrations of offshore wind turbines (OWTs) in the fore–aft and side–side directions. The procedure is tested to the design of a PTMD to be applied to the 5‐MW benchmark baseline monopile wind turbine proposed by the National Renewable Energy Lab (NREL). The computation of wind and wave spectra, as well as the evaluation of the hydrodynamic and aerodynamic loads, is conducted by using an in‐house built MATLAB® routine working together with an ANSYS® 3‐D finite element (FE) global model for evaluating the resultant peak displacement response at the OWT hub by a power spectral density (PSD) analysis. In order to validate the OWT FEM model, a result comparison is made with the NREL OpenFAST, finding good matches between the two codes. An in‐house built genetic algorithm (GA) toolbox, coded in MATLAB®, is then used to optimally design the parameters of a PTMD with a simplified 2‐degrees‐of‐freedom (2DOF) model. The chosen GA fitness function targets the minimization of the peak response of the primary structure as evaluated by the 2DOF model. The design parameters of the PTMD are the flexural rigidity and damping, the mass ratio and pendulum length. After the 3‐D FE model of the OWT without any control device has been validated, and the PTMD has been optimized by the simplified 2DOF model, the performances of the PTMD are examined on a 3‐D global FE OWT + PTMD model in ANSYS®.

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Section: Orcidmentioning

confidence: 99%

Optimal design of passive‐adaptive pendulum tuned mass damper for the global vibration control of offshore wind turbines

et al. 2020

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“…In this paper, the Vortex model is used to model the SBDWT because it is the most accurate model as mentioned earlier. In Reference 25, the torque of each SBDWT's blade is modeled and Equation (1) represents the mathematical model for the torque of each blade of wind turbine.

Q = ρπc R V_{\infty}^{2} {(1 - \frac{3 cX}{2 R} |italicsinθ|)}^{2} \sin^{2} θ

where Q i , ρ , c , R , V ∞ , X , and θ represent blade torque, fluid density, blade chord, rotor radius, wind velocity, tip speed ratio and blade rotation angle, respectively. In the three blades SBDWT, the angle between the blades is 120°.…”

Section: Modelingthe Vawt and Its Faultsmentioning

confidence: 99%

“…As mentioned earlier, the SBDWT is equipped with a pitch angle controller to overcome the starting torque. In Reference 25 the relationship between tip speed ratio and the pitch angle was mentioned. Equation (4) represents this relationship for the three blades SBDWT.

X = \frac{1}{italictanϕ + \frac{3 c}{2 R}}

where ϕ = α + γ , which α and γ represent the initial pitch angle and added or subtracted angle to pitch angle in pitch angle control, respectively.…”

Section: Modelingthe Vawt and Its Faultsmentioning

confidence: 99%

A novel flicker detection method for vertical axis wind turbine using two‐dimensional discrete wavelet transform

Doustmohammadi

Foroud

2020

Int Trans Electr Energ Syst

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Background Pattern recognition applications have increased dramatically over the past four decades. In power system, pattern recognition can be used in fields such as power quality. One of the important power quality aspects is flicker, which is caused by torque fluctuations in wind turbines. Aims In this paper, the various mechanical faults including single and double faults that cause flicker in vertical axis wind turbines (VAWTs) are modeled; then flicker caused by single and double faults are analyzed. Then, a novel method for pattern recognition is presented which results in more accuracy in flicker detection. Materials and Methods In this paper, features of voltage and current signals are extracted by the 2D‐DWT. The 2D‐DWT is capable of producing valuable features than the discrete wavelet transform (DWT) at a lower level of decomposition. The 2D‐DWT is even capable of compressing data that can be suitable for smart grids, which high volume data is one of their problems. In order to reduce the redundant data, dimension of features vector, and computational burden, a new method is presented for feature selection. The backbone of the presented feature selector is the used classifier in the corresponding pattern system; so it is compatible with the classifier. Results Results show the high accuracy of the proposed method in identifying the factors that cause flicker in VAWTs. Conclusion In this paper, it was shown that the features extracted from the current and voltage signal by the 2D‐DWT were superior to the features extracted from the only voltage signal by the DWT. Also, the advantage of the proposed feature selection over the Relieff method was shown.

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“…The mathematical model of the horizontal-axis wind turbine considered here is based on a stream tube discretization, which relies on momentum conservation in both the axial and tangential directions. The airfoil aerodynamic characteristics, the lift ( C L ) and drag ( C D ) coefficients, can be found in Wilson and Lissaman (1974). The thrust and torque acting on a blade element d r , at a distance r from the center of the rotor, are given by…”

Section: Mathematical Model Of the Horizontal-axis Wind Turbinementioning

confidence: 99%

“…The momentum models approximate the wind turbine effects using actuator surfaces and subdivide the flow domain in many stream tubes (see e.g. Islam et al, 2008; Torresi et al, 2013, 2016; Wilson and Lissaman, 1974). These models appear to be more suitable to describe the wind turbine dynamics for control applications.…”

Section: Introductionmentioning

confidence: 99%

Enhanced one-step-ahead adaptive control technique for wind systems

D’Ambrosio

2018

Wind Engineering

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This article proposes an enhanced version of the one-step-ahead control algorithm applied to a wind system. The wind system is considered as an isolate source of power and it is composed of a horizontal-axis wind turbine connected to an induction generator: consistent mathematical models for the horizontal-axis wind turbine and the induction generator will be introduced. Although the main strength of the one-step-ahead control technique is its adaptivity, nevertheless its convergence rate reduces very quickly. This aspect shows the primary algorithm weakness and is the reason for the proposed enhancement. Finally, the results of control problems will prove the reliability of the suggested enhanced control technique.

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Applied Aerodynamics of Wind Power Machines

Cited by 78 publications

References 1 publication

Optimal design of passive‐adaptive pendulum tuned mass damper for the global vibration control of offshore wind turbines

Optimal design of passive‐adaptive pendulum tuned mass damper for the global vibration control of offshore wind turbines

A novel flicker detection method for vertical axis wind turbine using two‐dimensional discrete wavelet transform

Enhanced one-step-ahead adaptive control technique for wind systems

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