1 / 15

Wind Flow Over Forested Hills: Mean Flow and Turbulence Characteristics

Peter Stuart, Ian Hunter. Renewable Energy Systems Ltd., UK. CEsA - Centre for Wind Energy and Atmospheric Flows, Portugal. J. Lopes da Costa, José Laginha Palma. Wind Flow Over Forested Hills: Mean Flow and Turbulence Characteristics. What we do with CFD:.

hanne
Download Presentation

Wind Flow Over Forested Hills: Mean Flow and Turbulence Characteristics

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. Peter Stuart, Ian Hunter Renewable Energy Systems Ltd., UK CEsA - Centre for Wind Energy and Atmospheric Flows, Portugal J. Lopes da Costa, José Laginha Palma Wind Flow Over Forested Hills: Mean Flow and Turbulence Characteristics

  2. What we do with CFD: Understand the flow over a wind farm. Effectively place meteorological masts. Site turbines better. Complement linear and empirical models. What we don’t do with CFD: Wind resource predictions. Replace linear and empirical models.

  3. Computer code Community trade mark nº 4706438 Office for Harmonisation in the Internal Market (OHIM) CFD Model Mathematical and Physical Modelling • Reynolds averaged Navier Stokes (RaNS) equations • Two-equation (k-ε) turbulence model with canopy model • Terrain-following coordinate system Numerical Techniques • Finite volume • SIMPLE algorithm • Steady State & Transient

  4. Svensson Canopy Model (in 2004) The drag due to the canopy is taken into account via an additional term entering the momentum equation : α (in m2m-3) is the leaf foliage area per unit of volume CD is the canopy drag coefficient. The effects of the canopy on turbulence are accounted for by additional source terms Sk and Sε in the transport equations of k and ε Lopes da Costa, J. C., Castro F.A., Palma J.M.L.M., Stuart P. “Computer Simulation of Atmospheric Flows over Real Forests for Wind Energy Resource Evaluation”, journal of Wind Engineering and Industrial Aerodynamics, 94 (2006) P. 603-620, 7th February 2006.

  5. New Canopy Model (in 2008) The new canopy model includes extra terms in the turbulence and dissipation equations: The canopy model constants are derived by comparing CFD simulations of an idealised canopy step change with Large Eddy Simulations (LES). Lopes da Costa, J. C. P., “Atmospheric Flow Over Forested and Non-Forested Complex Terrain”,PhD Thesis University of Porto, July 2007.

  6. RANS vs. Large Eddy Simulation (LES) Turbulence Wind Speed

  7. Site Characterisation (1) • European site with complex orography and extensive forest cover (H ~ 15m). • 6 meteorological masts used for validation.

  8. H = 15m, CD = 0.25 and α = 0.2 H = 15m, CD = 0.25 and α = 0.2 Measured Turbulence Intensity Measured Shear CFD (New Canopy Model) CFD (Svensson Canopy Model) CFD (New Canopy Model) 0.80 CFD (Svensson Canopy Model) 30% 0.70 25% 0.60 20% 0.50 Turbulence Intensity Shear Exponent 15% 0.40 0.30 10% 0.20 5% 0.10 0% M273 M272 M223 M1 M187 M186 0.00 M273 M272 M223 M1 M187 M186 Predicted and measured turbulence intensity for 330° direction. Predicted and measured shear exponents for 330° direction. Site Characterisation (2)

  9. Optimisation of Canopy Parameters… Measured Shear Measured Shear CFD (New Canopy Model) CFD (Svensson Canopy Model) CFD (New Canopy Model) CFD (Svensson Canopy Model) 0.80 0.80 0.70 0.70 0.60 0.60 0.50 0.50 Shear Exponent Shear Exponent 0.40 0.40 0.30 0.30 0.20 0.20 0.10 0.10 0.00 0.00 M273 M272 M223 M187 M186 M273 M272 M223 M1 M187 M186 M1 2nd Iteration: α→ 0.13 3rd Iteration: α → 0.05 Site Characterisation (2) Reducing the canopy density improves agreement, but even with α = 0.05the predicted shear exponents are still too high.

  10. Site Characterisation (3) Turbulence From Concurrent Data Turbulence From All Data CFD (New Canopy Model) CFD (Svensson Canopy Model) 30.00% Shear From Concurrent Data Shear From All Data CFD (New Canopy Model) CFD (Svensson Canopy Model) 25.00% 0.80 0.70 20.00% 0.60 Turbulence Intensity 15.00% 0.50 Shear Exponent 10.00% 0.40 5.00% 0.30 0.20 0.00% M273 M272 M223 M1 M187 M186 0.10 0.00 M273 M272 M223 M1 M187 M186 Predicted and measured turbulence intensity for 330° direction. Predicted and measured shear exponents for 330° direction. Further improvement gained by using an effective tree height of ¾ the actual height. Final canopy parameters: H = 11.25m, CD = 0.25, α = 0.05

  11. Site Characterisation (4) Turbulence From Concurrent Data Turbulence From All Data Shear From Concurrent Data Shear From All Data CFD (New Canopy Model) CFD (Svensson Canopy Model) CFD (New Canopy Model) CFD (Svensson Canopy Model) 0.80 30.00% 0.70 25.00% 0.60 20.00% 0.50 Turbulence Intensity Shear Exponent 0.40 15.00% 0.30 10.00% 0.20 5.00% 0.10 0.00% 0.00 M273 M272 M223 M1 M187 M186 M273 M272 M223 M1 M187 M186 Predicted and measured turbulence intensity for 300° direction. Predicted and measured shear exponents for 300° direction. Optimised parameters derived from 330° direction applied to 300° direction.

  12. Wind Speed Profiles

  13. Turbulence Intensity Profiles

  14. Conclusions Svennson and new model are similar > 3 tree heights. New model better < 3 tree heights. Tune α (canopy density) to better predict shear and turbulence. Further Work • Investigate applying a vertically variable canopy density.

  15. VENTOSTM http://paginas.fe.up.pt/ventos/ RES http://www.res-group.com

More Related