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Comprehensive utilization of mesoscale modelling for wind energy applications

Comprehensive utilization of mesoscale modelling for wind energy applications. Jake Badger, Andrea Hahmann, Xiaoli Guo Larsen, Alfredo Peña Diaz, Ekaterina Batchvarova, Sven-Erik Gryning, Rogier Floors, Hans Ejsing Jørgensen Wind Energy Division Risø DTU. Introduction.

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Comprehensive utilization of mesoscale modelling for wind energy applications

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  1. Comprehensive utilization of mesoscalemodelling for wind energy applications Jake Badger, Andrea Hahmann, Xiaoli Guo Larsen, Alfredo Peña Diaz, Ekaterina Batchvarova, Sven-Erik Gryning, Rogier Floors, Hans Ejsing Jørgensen Wind Energy Division Risø DTU

  2. Introduction PREDICTABILITY OF WIND CONDITIONS17/3/2011, 11:00 - 12:30 SITING CHALLENGES16/3/2011, 11:00 - 12:30 ComprehensiveadjOxford English Dictionary 1. complete; including all, or nearly all elements, aspects etc. 2. of or relating to understanding 3. ... Comprehensive (1st meaning: complete) Wind resource assessment Poster ID 156 Wind power forecasting Poster ID 153 Extreme wind climate assessment Talk Mesoscale variability of wind Talk ‘Tall’ wind profiles Talk Flow over forest Talk Wind power integration Wind farm wakes: their impacts on climate Wind turbine icing forecasting and climate Wind and wave climate studies ...

  3. Introduction Comprehensive (2nd meaning: understanding) There is a need to understand limitations of mesoscale modelling appropriate use of the modelling results Need valid link between mesoscale modelling results and measurement This allows: application verification We can also verify against other meteorological quantities (not just wind) to: test performance of model indicate new linkages between mesocale modelling, microscale modelling and measurements

  4. Routes from mesoscale model to site local roughness corrections mesoscale model output estimates of site conditions Meso ‘local’ corrections micro local corrections

  5. Routes from mesoscale model to site local roughness corrections mesoscale model output estimates of site conditions Meso ‘local’ corrections micro local corrections  direct

  6. Routes from mesoscale model to site local roughness corrections mesoscale model output estimates of site conditions Meso ‘local’ corrections micro local corrections  direct  micro corrections only

  7. Routes from mesoscale model to site local roughness corrections mesoscale model output estimates of site conditions Meso ‘local’ corrections micro local corrections  direct  micro corrections only  meso & micro corrections

  8. Links in the model chain Mesocale model fields and output h, z0 u*, L or u(z) or u(zj) Post-processing Generalization Badger et al (2010) • corrections for • orography • roughness account for ‘local’ mesoscale effects Evaluate u for standard heights above flat terrain of standard roughness lengths • application of • M-O similarity theory • geostrophic drag law Application account for ‘local’ microscale effects at site WAsP WAsP Engineering u at site

  9. Mesoscale ‘local’ corrections due to orography max +18% min +4% due to roughness max +1% min - 6% Site in northern Spain Microscale local corrections due to orography max +60% min +10% due to roughness max 0% min - 6%

  10. Verification of mean wind speed u*Lmeso u*Luser u(z) u(zj) Site in northern Spain normalized wind speed Mesoscale ‘local’ corrections and microscale local corrections give best agreement with measurements method  direct  micro corrections only  meso & micro corrections

  11. Verification of mean power density u*Lmeso u*Luser u(z) u(zj) Site in northern Spain normalized power density Mesoscale ‘local’ corrections and microscale local corrections give best agreement with measurements method  direct  micro corrections only  meso & micro corrections

  12. Importance of microscale... a motivation Wind resource (power density) at 50 m calculated at different resolutions 50 km 10 km 5 km 50 km 328 W/m2 378 W/m2 324 W/m2 378 W/m2 2.5 km 0.1 km 505 W/m2 641 W/m2 323 W/m2 378 W/m2 mean power density of total area mean power density for windiest 50% of area

  13. Application at high resolution Wind climate WAsP Extreme wind climate WAsP Engineering

  14. New modes of model verification Pulsed LIDAR wind measurement to 600 m Floors et al (2010) 100 m 600 m 100 m Separate error contribution into mesoscale and microscale parts? Microscale influence tending to reduce with height.

  15. New modes of model verification Comparison of surface layer fluxes from sonics Peña and Hahmann (2011) u*, WRF v sonic heat flux, WRF v sonic 1/L, WRF v sonic Learn characteristic errors in surface fluxes. B-L schemes may give unexpected velocity profiles. Surface fluxes and theory for alternative profiles.

  16. Advancing the links in the model chain Gryning et al 2007 Modelling profiles beyond the surface layer After Gryning et al (2007), 3 characteristic lengths scales used to define boundary-layer profiles: Neutral with baroclinicity term (Kelly 2011, pers.comm.) (stable and unstable profiles have corresponding expressions)

  17. Advancing the links in the model chain • Modelling profiles beyond the surface layer After Gryning et al (2007), 3 characteristic lengths scales used to define boundary-layer profiles: Neutral with baroclinicity term (Kelly 2011, pers.comm.) (stable and unstable profiles have corresponding expressions) B-L height from pulsed LIDAR via aerosols’ backscatter z [m] B-L height from WRF B-L height [m] Julian day Peña et al (2010) time of day (LST) Hahmann 2011

  18. Advancing the links in the model chain < > at 70 m • Correction of long-term profile will be useful in application of generalized wind climates at sites. Peña and Hahmann (2011) Kelly and Gryning (2010) describe method to correct long-term profile according to long-term distribution of stability (pdf of 1/L). Peña and Hahmann (2011) use WRF to evaluate long-term distribution of stability (pdf of 1/L) and thus give a long-term stability correction < >

  19. Summary and conclusions • Verification of mesoscale modelling applications in wind energy requires consideration of local unresolved effects. • Valuable new model verification possible via application of new measurement technologies. • New theory gives possibilities for advancing the mesoscale to microscale model chain. • Understanding mesoscale model characteristics guides appropriate use of mesoscale model output: • boundary layer parameterizations • surface layer and boundary layer properties • Most appropriate use may not always be the most obvious. • Verification is an essential part of model development loop.

  20. Thank you for your attentionjaba@risoe.dtu.dk Oral presentation sessions PREDICTABILITY OF WIND CONDITIONS17/3/2011, 11:00 - 12:30 SITING CHALLENGES16/3/2011, 11:00 - 12:30 Poster session Poster ID 156 on uncertainty mapping Poster ID 153 on forecasting

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