The spectrum of wind speed fluctuations encountered by a rotating blade of a wind energy conversion system

Connell, J.R.

doi:10.1016/0038-092x(82)90072-x

Cited by 65 publications

(46 citation statements)

References 2 publications

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“…Obtaining high-frequency point measurements over a sufficiently wide area, which would enable the spatial coherence to be measured and the model to be verified, is inherently challenging in a fast-flowing tidal stream. One would expect however, given the relatively good agreement that was observed between the measured and the von Kármán spectra, that the analytical form of the rotational sampled spectrum in the study of Connell [23] would permit sensible predictions of the dominant frequencies.…”

Section: Discussionmentioning

confidence: 99%

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Characteristics of the turbulence in the flow at a tidal stream power site

Milne

Sharma

Flay

et al. 2013

Phil. Trans. R. Soc. A.

105

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This paper analyses a set of velocity time histories which were obtained at a fixed point in the bottom boundary layer of a tidal stream, 5 m from the seabed, and where the mean flow reached 2.5 m s −1 . Considering two complete tidal cycles near spring tide, the streamwise turbulence intensity during nonslack flow was found to be approximately 12-13%, varying slightly between flood and ebb tides. The ratio of the streamwise turbulence intensity to that of the transverse and vertical intensities is typically 1 : 0.75 : 0.56, respectively. Velocity autospectra computed near maximum flood tidal flow conditions exhibit an f −2/3 inertial subrange and conform reasonably well to atmospheric turbulence spectral models. Local isotropy is observed between the streamwise and transverse spectra at reduced frequencies of f > 0.5. The streamwise integral time scales and length scales of turbulence at maximum flow are approximately 6 s and 11-14 m, respectively, and exhibit a relatively large degree of scatter. They are also typically much greater in magnitude than the transverse and vertical components. The findings are intended to increase the levels of confidence within the tidal energy industry of the characteristics of the higher frequency components of the onset flow, and subsequently lead to more realistic performance and loading predictions.

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Section: Discussionmentioning

confidence: 99%

“…Connell [23] has derived an analytical expression for the turbulent velocity spectrum for a point on a rotating blade from the von Kármán turbulence spectrum and corresponding coherence functions. The model was employed in Milne et al [17] to explore the implications of rotational sampled turbulence on a typical tidal turbine.…”

Section: Discussionmentioning

confidence: 99%

Characteristics of the turbulence in the flow at a tidal stream power site

Milne

Sharma

Flay

et al. 2013

Phil. Trans. R. Soc. A.

105

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“…It would be desirable to demonstrate that the rotational spectrum (Connell 1981) that applies at a point on a wind turbine blade, under specified conditions of mean wind speed, stability, and surface roughness, can be calculated by formula, at least as well as can be done for the Eulerian, or non-moving point, spectrum. This should hold for the normal, radial and tangential components of ",!ind relative to the disk of rotatation.…”

Section: Verification With Observed Variance and Length Scalesmentioning

confidence: 99%

Verification of theoretically computed spectra for a point rotating in a vertical plane

Powell

Connell

1987

Solar Energy

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()Banelle I~ b DISCLAI MERThis repo rt was p repared as an acco un t of work spo nsore d by an agency o f the Uni ted States Govern ment. Neither the Un ited States Gove rnm en t nor any age ncy th ereo f, nor an y of thei r employees, mak es any w ar ra n ty, ex press or im p lied , o r assu mes any legal liab i lity or respo nsib i li ty for the accuracy, comp letene ss, or usefu lness of any infor ma ti o n, appa ratu s, pro d uct , or process disc losed , or re p resents t hat its use wo u ld no t infri nge pri vately ow ned right s. A theoretical model is modified and tested that produces the power spectrum of the alongwind component of turbulence as experienced by a point rotating in a vertical plane perpendicular to the mean wind direction. The ability to generate such a power spectrum, independent of measurement, is important in wi nd turbine design and testing. The radius of the circle of rotation, its height above the ground, and the rate of rotation are typical for those for a MOO-OA wind turbine. Verification of this model is attempted by comparing two sets of variances that correspond to individual harmonic bands of spectra of turbulence in the rotational frame. One set of variances is calculated by integrating the theoretically generated rotational spectra; the other is calculated by integrating rotational spectra from real data analysis. The theoretical spectrum is generated by Fourier transformation of an autocorrelation function taken from von Karman and modified for the rotational frame. The autocorrelation is based on dimensionless parameters, each of which incorporates both atmospheric and wind turbine parameters. The real data time series are formed by sampling around the circle of anemometers of the Vertical Plane Array at the former ~100-0A site at Clayton, New Mexico.Three time series were selected from data taken in a previous study; the time series represent slightly unstable, definitely unstable, and stable atmospheric conditions. All series were analyzed for 8.5-min periods of data. The first series was also analyzed for a 17-min data period.The theoretical model verifies at all frequencies from 1P to 5P with the 8.5-min runs except for the stable case. In all cases the ratios of variance in a harmonic band from the model to the corresponding variance from real data analysis decrease as the harmonic number increases. Since both sets of variances show decreasi ng magnitude with i ncreasi ng harmonic number (from 1P, 2P, ... 5P), variances from the model show a more rapid decrease of energy with harmonic than do the variances from real data analysis. For the slightly unstable case these ratios ran from 1.38 at 1P to 0.83 at 5P. However, the iii decrease of this ratio with frequency could result from noise in the observed data as well as from known and unknown limitations of the theoretical model.The necessary input parameters for the model include the variance as well as both the longitudinal and lateral length scales of u-component turbulence.(The empirical specification of two length ...

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“…Connell [23] suggests that the spectrum obtained from a probe rotating through a turbulent field differs from that obtained with a stationary probe due to transfer of energy from mid to higher frequencies resulting in a dip at the mid frequencies, and the accumulation of energy at frequencies higher than the 1P frequency. The effect is strongest at higher tip-speed ratios, and larger ratios of the blade length and eddy integral length scale.…”

Section: Non-steady Wind Turbine Responses To Atmospheric Boundary Lamentioning

confidence: 99%