html5-img
1 / 16

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. Introduction to the test site Measurements Comparison to models Conclusions. Introduction to the Site.

ingo
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Measuring the Impact of Atmospheric Conditions and Array Depth on Wake Losses Anna Marsh – DNV KEMA 04 – 07 Feb 2013, Vienna Austria

  2. Contents Introduction to the test site Measurements Comparison to models Conclusions

  3. Introduction to the Site

  4. Turbine Row Grouping – 225º - 245º Direction Sector 2 km Grid Lines (about 25 D) Lidar

  5. Measured Shear Profiles by TI Rotor

  6. Measured Wake by Row - TI Relative Power = % Power Difference Relative to Front Row TI Range

  7. 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

  8. Measured Wake by Row – Shear Difference Across Rotor Shear Difference

  9. 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

  10. Measured vs. Modelled Wakes Rows 1-15 -Measured Wakes

  11. Measured vs. Eddy Viscosity Model - TI

  12. Measured vs. Fuga Model – Stable and Unstable Conditions

  13. Measured vs. Time Series Average of Models - TI

  14. 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.

  15. DNV KEMA Energy & Sustainability • Part of DNV Group—an independent foundation with HQ in Norway founded in 1864—with 11,000 employees globally • 200+ wind energy experts • 30 GW+ energy assessments globally • Testing, inspections, certification, consulting • Risk, performance, and quality management • Research & innovation • Offices in over 30 countries

  16. 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 Anna.Marsh@dnvkema.com www.dnvkema.com www.dnv.com/windenergy www.dnvkema.com

More Related