Measuring the impact of atmospheric conditions and array depth on wake losses
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Measuring the Impact of Atmospheric Conditions and Array Depth on Wake Losses. Anna Marsh – DNV KEMA. 04 – 07 Feb 2013, Vienna Austria. Contents. Introduction to the test site Measurements Comparison to models Conclusions. Introduction to the Site.

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Measuring the Impact of Atmospheric Conditions and Array Depth on Wake Losses

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Measuring the impact of atmospheric conditions and array depth on wake losses

Measuring the Impact of Atmospheric Conditions and Array Depth on Wake Losses

Anna Marsh – DNV KEMA

04 – 07 Feb 2013, Vienna Austria


Contents

Contents

Introduction to the test site

Measurements

Comparison to models

Conclusions


Introduction to the site

Introduction to the Site


Turbine row grouping 225 245 direction sector

Turbine Row Grouping – 225º - 245º Direction Sector

2 km Grid Lines (about 25 D)

Lidar


Measured shear profiles by ti

Measured Shear Profiles by TI

Rotor


Measured wake by row ti

Measured Wake by Row - TI

Relative Power = % Power Difference Relative to Front Row

TI Range


Measured shear profiles by shear difference across rotor

Measured Shear Profiles by Shear Difference Across Rotor

Shear Difference Across Rotor =

Top Shear (80m/120m Alpha)

Minus

Bottom Shear (40m/80m Alpha)

Top Shear

Rotor

Shear Difference

Bottom Shear


Measured wake by row shear difference across rotor

Measured Wake by Row – Shear Difference Across Rotor

Shear Difference


Wake models

Wake Models

Single turbine wake models

Park

Eddy Viscosity

Combination methods

Square root of sum of squares (SS)

Energy balance (EB)

Accounting for atmospheric conditions

Time Series Park and Eddy Viscosity Model

Fuga

Data used in Measured and Modelled Results

August through December data

Filtered for 6m/s to 12m/s

9


Measured vs modelled wakes rows 1 15

Measured vs. Modelled Wakes Rows 1-15

-Measured Wakes


Measured vs eddy viscosity model ti

Measured vs. Eddy Viscosity Model - TI


Measured vs fuga model stable and unstable conditions

Measured vs. Fuga Model – Stable and Unstable Conditions


Measured vs time series average of models ti

Measured vs. Time Series Average of Models - TI


Conclusions

Conclusions

  • Wake losses are significantly influenced by TI and shear across the rotor.

  • Models underestimate wakes in some conditions and over predict wakes in other conditions. For some projects, the errors will cancel out.

  • Results are consistent with other DNV KEMA studies and observations.

  • Recommendations

    • Measure parameters that impact wakes, such as shear across and above the rotor

    • Modify wake models to account for conditions that can be measured

    • More wake model validation studies comparing atmospheric conditions and wakes

Special thanks to project participants who shared data for this study.


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DNV KEMA Energy & Sustainability

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Measuring the impact of atmospheric conditions and array depth on wake losses

Anna Marsh

Senior Engineer

DNV KEMA Energy & Sustainability

Palace House

3 Cathedral Street

London SE1 9DE

Tel: +44 20 7716 6591

Mobile: +44 79 6972 9915

[email protected]

www.dnvkema.com

www.dnv.com/windenergy

www.dnvkema.com


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