Turbulence Correction for Power Curves

Kaiser, Kenneth F.; Langreder, Wiebke; Hohlen, H.; Højstrup, Jørgen

doi:10.1007/978-3-540-33866-6_28

Cited by 55 publications

(50 citation statements)

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“…Both methods require that the power curve for 0% turbulence intensity (0%-TI power curve) is retrieved from the measurements obtained with turbulence intensity which was not 0%. In the method discussed in (Kaiser et al, 2003), the 10 minute mean power for a given TI is based on the 0% TI power curve and its second derivative that changes sign according to the bend of the power curve. Albers (2010) went a step further as his method is based on the fact that the 10 minute average of the power is not linearly related to the mean wind speed but to the wind speed distribution during the considered 10 minute and the shape of the power curve.…”

Section: Scatter Due To Turbulencementioning

confidence: 99%

Accounting for the speed shear in wind turbine power performance measurement

Wagner¹,

Courtney²,

Gottschall³

et al. 2011

Wind Energy

147

109

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Abstract:The power curve of a wind turbine is the primary characteristic of the machine as it is the basis of the warranty for it power production. The current IEC standard for power performance measurement only requires the measurement of the wind speed at hub height and the air density to characterise the wind field in front of the turbine. However, with the growing size of the turbine rotors during the last years, the effect of the variations of the wind speed within the swept rotor area, and therefore of the power output, cannot be ignored any longer. Primary effects on the power performance are from the vertical wind shear and the turbulence intensity. The work presented in this thesis consists of the description and the investigation of a simple method to account for the wind speed shear in the power performance measurement. Ignoring this effect was shown to result in a power curve dependant on the shear condition, therefore on the season and the site. It was then proposed to use an equivalent wind speed accounting for the whole speed profile in front of the turbine. The method was first tested with aerodynamic simulations of a multi-megawatt wind turbine which demonstrated the decrease of the scatter in the power curve. A power curve defined in terms of this equivalent wind speed would be less dependant on the shear than the standard power curve. The equivalent wind speed method was then experimentally validated with lidar measurements. Two equivalent wind speed definitions were considered both resulting in the reduction of the scatter in the power curve. As a lidar wind profiler can measure the wind speed at several heights within the rotor span, the wind speed profile is described with more accuracy than with the power law model. The equivalent wind speed derived from measurements, including at least one measurement above hub height, resulted in a smaller scatter in the power curve than the equivalent wind speed derived from profiles extrapolated from measurements at hub height and below only. It is well established that the turbulence intensity also influences the power performance of a wind turbine. Two ways of accounting for the turbulence were tested with the experimental data: an adaptation of the equivalent wind speed so that it also accounts for the turbulence intensity and the combination of the equivalent wind speed accounting for the wind shear only with the turbulence normalising method for turbulence intensity suggested by Albers. The second method was found to be more suitable for normalising the power curve for the turbulence intensity. Using the equivalent wind speed accounting for the wind shear in the power performance measurement was shown to result in a more repeatable power curve than the standard power curve and hence, in a better annual energy production estimation. Furthermore, the decrease of the scatter in the power curve corresponds to a decrease of the category A uncertainty in power, resulting in a smaller uncertainty in estimated AEP.The thesis is submitted to the Danish Tec...

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Section: Scatter Due To Turbulencementioning

confidence: 99%

Accounting for the speed shear in wind turbine power performance measurement

Wagner¹,

Courtney²,

Gottschall³

et al. 2011

Wind Energy

147

109

View full text Add to dashboard Cite

show abstract

“…Previous work on power performance highlights the role of turbulence intensity (TI) and wind shear in influencing power production (Elliot and Cadogan, 1990;Hunter et al, 2001;Kaiser et al, 2003;Sumner and Masson, 2006;Gottschall and Peinke, 2008;Antoniou et al, 2009;Rareshide et al, 2009;Wharton and Lundquist, 2012a, b;Clifton et al, 2013a;Dörenkämper et al, 2014). Wharton and Lundquist (2012b) also found that vertical TI and turbulence kinetic energy (TKE) affect power performance and Rareshide et al (2009) found that veer affects power performance.…”

Section: Introductionmentioning

confidence: 99%

Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

Martin¹,

Lundquist

Clifton

et al. 2016

Wind Energ. Sci.

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Abstract. Using detailed upwind and nacelle-based measurements from a General Electric (GE) 1.5sle model with a 77 m rotor diameter, we calculate power curves and annual energy production (AEP) and explore their sensitivity to different atmospheric parameters to provide guidelines for the use of stability and turbulence filters in segregating power curves. The wind measurements upwind of the turbine include anemometers mounted on a 135 m meteorological tower as well as profiles from a lidar. We calculate power curves for different regimes based on turbulence parameters such as turbulence intensity (TI) as well as atmospheric stability parameters such as the bulk Richardson number (R B ). We also calculate AEP with and without these atmospheric filters and highlight differences between the results of these calculations. The power curves for different TI regimes reveal that increased TI undermines power production at wind speeds near rated, but TI increases power production at lower wind speeds at this site, the US Department of Energy (DOE) National Wind Technology Center (NWTC). Similarly, power curves for different R B regimes reveal that periods of stable conditions produce more power at wind speeds near rated and periods of unstable conditions produce more power at lower wind speeds. AEP results suggest that calculations without filtering for these atmospheric regimes may overestimate the AEP. Because of statistically significant differences between power curves and AEP calculated with these turbulence and stability filters for this turbine at this site, we suggest implementing an additional step in analyzing power performance data to incorporate effects of atmospheric stability and turbulence across the rotor disk.

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“…Turbulence affects the wind turbines mainly in two ways: first, the fluctuations that are caused in the extracted wind power (Kaiser et al, 2007;Gottschall and Peinke, 2008), and second, the fluctuations in the loads on different components of a wind turbine . These fluctuations result in inefficient harnessing of wind energy and have the potential to inflict fatigue damage.…”

Section: Introductionmentioning

confidence: 99%

A review of turbulence measurements using ground-based wind lidars

Sathe¹,

Mann²

2013

Atmos. Meas. Tech.

154

117

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Abstract.A review of turbulence measurements using ground-based wind lidars is carried out. Works performed in the last 30 yr, i.e., from 1972-2012 are analyzed. More than 80 % of the work has been carried out in the last 15 yr, i.e., from 1997-2012. New algorithms to process the raw lidar data were pioneered in the first 15 yr, i.e., from 1972-1997, when standard techniques could not be used to measure turbulence. Obtaining unfiltered turbulence statistics from the large probe volume of the lidars has been and still remains the most challenging aspect. Until now, most of the processing algorithms that have been developed have shown that by combining an isotropic turbulence model with raw lidar measurements, we can obtain unfiltered statistics. We believe that an anisotropic turbulence model will provide a more realistic measure of turbulence statistics. Future development in algorithms will depend on whether the unfiltered statistics can be obtained without the aid of any turbulence model. With the tremendous growth of the wind energy sector, we expect that lidars will be used for turbulence measurements much more than ever before.

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Turbulence Correction for Power Curves

Cited by 55 publications

References 0 publications

Accounting for the speed shear in wind turbine power performance measurement

Accounting for the speed shear in wind turbine power performance measurement

Wind turbine power production and annual energy production depend on atmospheric stability and turbulence

A review of turbulence measurements using ground-based wind lidars

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