Dissipation of Turbulence in the Wake of a Wind Turbine

详细信息    查看全文

• 作者：J. K. Lundquist (1) (2)
  L. Bariteau (3) (4)
  
  1. Department of Atmospheric and Oceanic Sciences ; University of Colorado at Boulder ; Boulder ; CO ; 80309-0311 ; USA
  2. National Wind Technology Center ; National Renewable Energy Laboratory ; Golden ; CO ; 80401-3305 ; USA
  3. Earth System Research Laboratory ; NOAA ; 325 Broadway ; Boulder ; CO ; 80305-3337 ; USA
  4. Cooperative Institute for Research in Environmental Sciences ; University of Colorado at Boulder ; Boulder ; CO ; 80309-0216 ; USA
  
• 关键词：Dissipation rate ; Tethered lifting system ; Turbulent kinetic energy ; Wind energy ; Wind turbines
• 刊名：Boundary-Layer Meteorology
• 出版年：2015
• 出版时间：February 2015
• 年：2015
• 卷：154
• 期：2
• 页码：229-241
• 全文大小：392 KB
• 参考文献：1. Aitken ML, Lundquist JK, Pichugina YL, Banta RM (2014a) Quantifying wind turbine wake characteristics from scanning remote sensor data. J Atmos Ocean Technol 31:765鈥?87. doi:10.1175/JTECH-D-13-00104.1
  2. Aitken ML, Kosovic B, Mirocha JD, Lundquist JK (2014b) Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model. J Renew Sustain Energy 6:033137. doi:10.1063/1.4885111 CrossRef
  3. Aitken ML, Lundquist JK (2014c) Utility-scale wind turbine wake characterization using nacelle-based long-range scanning lidar. J Atmos Ocean Technol 31:1529鈥?539 CrossRef
  4. Balsley BB, Frehlich RG, Jensen ML, Meillier Y, Muschinski A (2003) Extreme gradients in the nocturnal boundary layer: structure, evolution, and potential causes. J Atmos Sci 60:2496鈥?508. doi:10.1175/1520-0469(2003)060<2496:EGITNB>2.0.CO;2
  5. Banta RM, Olivier LD, Gudiksen PH, Lange R (1996) Implications of small-scale flow features to modeling dispersion over complex terrain. J Appl Meteorol 35:330鈥?42. doi:10.1175/1520-0450(1996)035<0330:IOSSFF>2.0.CO;2
  6. Barthelmie RJ, Pryor SC, Frandsen ST, Hansen KS, Schepers JG, Rados K, Schlez W, Neubert A, Jensen LE, Neckelmann S (2010) Quantifying the impact of wind turbine wakes on power output at offshore wind farms. J Atmos Ocean Technol 27:1302鈥?317. doi:10.1175/2010JTECHA1398.1 CrossRef
  7. Bhaganagar K, Debnath M (2014) Effect of mean atmospheric forcings of stable atmospheric boundary layer on wind turbine wake. J Renew Sustain Energy (accepted with revision)
  8. Browne LWB, Antonioa RA, Shah DA (1987) Turbulent energy dissipation in a wake. J Fluid Mech 179:307鈥?26. doi:10.1017/S002211208700154X CrossRef
  9. Cabez贸n D, Migoya E, Crespo A (2011) Comparison of turbulence models for the computational fluid dynamics simulation of wind turbine wakes in the atmospheric boundary layer. Wind Energy 14:909鈥?21. doi:10.1002/we.516 CrossRef
  10. Calaf M, Meneveau C, Meyers J (2010) Large eddy simulation study of fully developed wind-turbine array boundary layers. Phys Fluids 22:015110. doi:10.1063/1.3291077 CrossRef
  11. Calaf M, Parlange MB, Meneveau C (2011) Large eddy simulation study of scalar transport in fully developed wind-turbine array boundary layers. Phys Fluids 23:126603. doi:10.1063/1.3663376 CrossRef
  12. Champagne FH, Friehe CA, LaRue JC, Wyngaard J (1977) Flux measurements, flux estimation techniques, and fine-scale turbulence measurements in the unstable surface layer over land. J Atmos Sci 34:515鈥?30. doi:10.1175/1520-0469(1977)034<0515:FMFETA>2.0.CO;2
  13. Churchfield MJ, Lee S, Michalakes J, Moriarty PJ (2012) A numerical study of the effects of atmospheric and wake turbulence on wind turbine dynamics. J Turbul 13:1鈥?2 CrossRef
  14. Clifton A, Schreck S, Jager D, Kelley N, Lundquist JK (2013) Meteorological tower observations at the National Renewable Energy Laboratory. J Sol Energy Eng 135:031017. doi:10.1115/1.4024068 CrossRef
  15. El Kasmi A, Masson C (2008) An extended model for turbulent flow through horizontal-axis wind turbines. J Wind Eng Ind Aerodyn 96:103鈥?22. doi:10.1016/j.jweia.2007.03.007 CrossRef
  16. Fairall CW, Larsen SE (1986) Inertial-dissipation methods and turbulent fluxes at the air鈥搊cean interface. Boundary-Layer Meteorol 34:287鈥?01 CrossRef
  17. Fairall CW, Edson JB, Larsen SE, Mestayer PG (1990) Inertial-dissipation air鈥搒ea flux measurements: a prototype system using realtime spectral computations. J Atmos Ocean Technol 7:425鈥?53. doi:10.1175/1520-0426(1990)007<0425:IDASFM>2.0.CO
  18. Farm J, Kwon S, Law HK (2013) Wind farm power maximization based on a cooperative static game approach. SPIE, San Diego
  19. Fitch AC, Olson JB, Lundquist JK, Dudhia J, Gupta AK, Michalakes J, Barstad I (2012) Local and mesoscale impacts of wind farms as parameterized in a Mesoscale NWP Model. Mon Weather Rev 140:3017鈥?038. doi:10.1175/MWR-D-11-00352.1 CrossRef
  20. Fitch A, Lundquist JK, Olson JB (2013) Mesoscale influences of wind farms throughout a diurnal cycle. Mon Weather Rev 141:2173鈥?198. doi:10.1175/MWR-D-12-00185.1 CrossRef
  21. Frech M (2007) Estimating the turbulent energy dissipation rate in an airport environment. Boundary-Layer Meteorol 123:385鈥?93. doi:10.1007/s10546-006-9149-2 CrossRef
  22. Frehlich R, Meillier Y, Jensen M, Balsley B (2003) Turbulence measurements with the CIRES tethered lifting system during CASES-99: calibration and spectral analysis of temperature and velocity. J Atmos Sci 60:2487鈥?495. doi:10.1175/1520-0469(2003)060<2487:TMWTCT>2.0.CO;2
  23. Frehlich R, Meillier Y, Jensen M, Balsley B, Sharman R (2006) Measurements of boundary layer profiles in an urban environment. J Appl Meteorol Climatol 45:821鈥?37. doi:10.1175/JAM2368.1 CrossRef
  24. Frehlich R, Meillier Y, Jensen ML (2008) Measurements of boundary layer profiles with in situ sensors and Doppler lidar. J Atmos Ocean Technol 25:1328鈥?340. doi:10.1175/2007JTECHA963.1 CrossRef
  25. GWEC (2013) Global Wind Report: Annual Market Update (2012). Available at http://www.gwec.net/wp-content/uploads/2012/06/Annual_report_2012_LowRes.pdf
  26. Hamilton N, Kang HS, Meneveau C, Cal RB (2012) Statistical analysis of kinetic energy entrainment in a model wind turbine array boundary layer. J Renew Sustain Energy 4:063105. doi:10.1063/1.4761921 CrossRef
  27. Hartogensis O, de Bruin H (2005) Monin鈥揙bukhov similarity functions of the structure parameter of temperature and turbulent kinetic energy dissipation rate in the stable boundary layer. Boundary-Layer Meteorol 116:253鈥?76. doi:10.1007/s10546-004-2817-1 CrossRef
  28. Jacobson MZ, Archer C (2012) Saturation wind power potential and its implications for wind energy. Proc Natl Acad Sci USA 109:15679鈥?5684. doi:10.1073/pnas.1208993109 CrossRef
  29. Kaffine D, Worley C (2010) The windy commons? Environ Resour Econ 47:151鈥?72. doi:10.1007/s10640-010-9369-2 CrossRef
  30. Kelley ND (2004) An initial overview of turbulence conditions seen at higher elevations over the Western Great Plains. In: Proceedings of global wind power conference, Chicago
  31. Kelley N, Shirazi M, Jager D, Wilde S, Adams J, Buhl M, Sullivan P, Patton E (2004) Lamar Low-Level Jet Program-Interim Report, Report No. NREL/TP-500-34593, National Renewable Energy Laboratory, Golden
  32. Klipp C, Mahrt L (2003) Conditional analysis of an internal boundary layer. Boundary-Layer Meteorol 108:1鈥?7. doi:10.1023/A:1023034932094 CrossRef
  33. Lawrence DA, Balsley BB (2013) High-resolution atmospheric sensing of multiple atmospheric variables using the DataHawk small airborne measurement system. J Atmos Ocean Technol 30:2352鈥?366. doi:10.1175/JTECH-D-12-00089.1 CrossRef
  34. Lu H, Port茅-Agel F (2011) Large-eddy simulation of a very large wind farm in a stable atmospheric boundary layer. Phys Fluids 23:065101. doi:10.1063/1.3589857 CrossRef
  35. Magnusson M, Smedman AS (1994) Influence of atmospheric stability on wind turbine wakes. Wind Energy 18:139鈥?51
  36. Marden JR, Ruben SD, Pao LY (2012) Surveying game theoretic approaches for wind farm optimization. In: Proceedings of the AIAA aerospace sciences meeting
  37. Mellor GL (1973) Analytic prediction of the properties of stratified planetary surface layers. J Atmos Sci 30:1061鈥?069 CrossRef
  38. Mirocha J, Kosovic B, Aitken M, Lundquist JK (2014) Implementation of a generalized actuator disk wind turbine model into WRF for large-eddy simulation applications. J Renew Sustain Energy 6:013104. doi:10.1063/1.4861061 CrossRef
  39. Muschinski A, Frehlich R, Jensen M, Hugo R, Hoff A, Eaton F, Balsley B (2001) Fine-scale measurements of turbulence in the lower troposphere: an intercomparison between a kite- and balloon-borne, and a helicopter-borne measurement system. Boundary-Layer Meteorol 98:219鈥?50 CrossRef
  40. Nakanishi M (2001) Improvement of the Mellor鈥揧amada turbulence closure model based on large-eddy simulation data. Boundary-Layer Meteorol 99:349鈥?78 CrossRef
  41. Oncley S, Friehe CA, Larue JC, Businger JA, Itsweire EC, Chang SS (1996) Surface-layer fluxes, profiles, and turbulence measurements over uniform terrain under near-neutral conditions. J Atmos Sci 53:1029鈥?043. doi:10.1175/1520-0469(1996)053<1029:SLFPAT>2.0.CO;2
  42. Piper M (2001) The effects of a frontal passage on fine-scale nocturnal boundary layer turbulence. PhD thesis, University of Colorado
  43. Piper M, Lundquist JK (2004) Surface layer turbulence measurements during a frontal passage. J Atmos Sci 61:1768鈥?780 CrossRef
  44. Prospathopoulos JM, Politis ES, Rados KG, Chaviaropoulos PK (2011) Evaluation of the effects of turbulence model enhancements on wind turbine wake predictions. Wind Energy 14:285鈥?00. doi:10.1002/we.419 CrossRef
  45. Rajewski Daniel A et al (2013) Crop wind energy experiment (CWEX): observations of surface-layer, boundary layer, and mesoscale interactions with a wind farm. Bull Am Meteorol Soc 94:655鈥?72 CrossRef
  46. Rhodes ME, Lundquist JK (2013) The effect of wind turbine wakes on summertime Midwest atmospheric wind profiles. Boundary-Layer Meteorol 149:85鈥?03. doi:10.1007/s10546-013-9834-x CrossRef
  47. Sim C, Basu S, Manuel L (2009) The influence of stable boundary layer flows on wind turbine fatigue loads. In: Proceedings of the AIAA aerospace sciences meeting, Orlando
  48. Smalikho IN, Banakh VA, Pichugina YL, Brewer WA, Banta RM, Lundquist JK, Kelley ND (2013) Lidar investigation of atmosphere effect on a wind turbine wake. J Atmos Ocean Technol 30:2554鈥?570 CrossRef
  49. Sreenivasan KR (1995) On the universality of the Kolmogorov constant. Phys Fluids 7:2778鈥?784 CrossRef
  50. Stull RB (1988) An introduction to boundary-layer meteorology. Kluwer Academic Publishers, Dordrecht, 666 pp
  51. Thomsen K, S酶rensen P (1999) Fatigue loads for wind turbines operating in wakes. J Wind Eng Ind Aerodyn 80:121. doi:10.1016/S0167-6105(98)00194-9 CrossRef
  52. Vanderwende B, Lundquist JK (2012) The modification of wind turbine performance by statistically distinct atmospheric regimes. Environ Res Lett 7:034035. doi:10.1088/1748-9326/7/3/034035 CrossRef
  53. Wharton S, Lundquist JK (2012) Atmospheric stability affects wind turbine power collection. Environ Res Lett 7:014005-1鈥?14005-9 CrossRef
  54. Wiser R, Bollinger M (2013) Wind Technologies Market Report. LBL Report LBNL-6356E. Available at http://emp.lbl.gov/publications/2012-wind-technologies-market-report
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Meteorology and Climatology
  Atmospheric Protection, Air Quality Control and Air Pollution
  
• 出版者：Springer Netherlands
• ISSN：1573-1472

文摘

The wake of a wind turbine is characterized by increased turbulence and decreased wind speed. Turbines are generally deployed in large groups in wind farms, and so the behaviour of an individual wake as it merges with other wakes and propagates downwind is critical in assessing wind-farm power production. This evolution depends on the rate of turbulence dissipation in the wind-turbine wake, which has not been previously quantified in field-scale measurements. In situ measurements of winds and turbulence dissipation from the wake region of a multi-MW turbine were collected using a tethered lifting system (TLS) carrying a payload of high-rate turbulence probes. Ambient flow measurements were provided from sonic anemometers on a meteorological tower located near the turbine. Good agreement between the tower measurements and the TLS measurements was established for a case without a wind-turbine wake. When an operating wind turbine is located between the tower and the TLS so that the wake propagates to the TLS, the TLS measures dissipation rates one to two orders of magnitude higher in the wake than outside of the wake. These data, collected between two and three rotor diameters \(D\) downwind of the turbine, document the significant enhancement of turbulent kinetic energy dissipation rate within the wind-turbine wake. These wake measurements suggest that it may be useful to pursue modelling approaches that account for enhanced dissipation. Comparisons of wake and non-wake dissipation rates to mean wind speed, wind-speed variance, and turbulence intensity are presented to facilitate the inclusion of these measurements in wake modelling schemes.