Abstract
This chapter gives a short overview of different methods used for turbulence generation in the field of wind energy. The wind fields can be used as an inflow for computational fluid dynamics or blade element momentum-based simulations. For all presented models, the mathematical background is given, and it is discussed which advantages and drawbacks they have. The main focus lies on statistical properties in terms of one- and two-point statistics. This includes variance, autocorrelations, cross correlations, and spectral properties. First different recycling methods are explained, namely, the weak and the strong recycling methods. In the following sections, synthetic coherent eddy methods are shown which approximate the turbulent properties well. Those are the digital filtering method and the random spots method. Also an inflow model based on continuous-time random walks is demonstrated which considers higher-order statistics, the increment statistics. In the last section, two spectral methods are in the focus which are used in a wide range in the field of wind energy, the Sandia method, and the Mann model.
This is a preview of subscription content, log in via an institution.
References
Akselvoll K, Moin P (1993) Application of the dynamic localization model to large-eddy simulation of turbulent flow over a backward facing step. ASME-PUBLICATIONS-FED 162:1–1
Akselvoll K, Moin P (1996) Large-eddy simulation of turbulent confined coannular jets. J Fluid Mech 315:387-411. https://doi.org/10.1017/S0022112096002479
Bazdidi-Tehrani F, Badaghi D, Kiamansouri M, Jadidi M (2017) Analysis of various inflow turbulence generation methods in large eddy simulation approach for prediction of pollutant dispersion around model buildings. J Comput Methods Eng 35:85–112
Berg J, Natarajan A, Mann J, Patton EG (2016) Gaussian vs non-Gaussian turbulence: impact on wind turbine loads. Wind Energy 19(11):1975–1989
Bierbooms WAAM, Dragt JB (1996) SWING 4: a stochastic 3D wind field generator for design calculations. In: Proceedings of European Union Wind Energy Conference, EUWEC 1996, pp 942–945
Bos R (2017) Extreme gusts and their role in wind turbine design. Ph.D. Thesis
Breuer M (2018) Effect of inflow turbulence on an airfoil flow with laminar separation bubble: an LES study. Flow Turbul Combust 101(2):433–456
Chung YM, Sung HJ (1997) Comparative study of inflow conditions for spatially evolving simulation. AIAA J 35:269–274
Dörenkämper M, Witha B, Steinfeld G, Heinemann D, Kühn M (2015) The impact of stable atmospheric boundary layers on wind-turbine wakes within offshore wind farms. J Wind Eng Ind Aerodyn 144:146–153
Dimitrov N, Kelly MC, Vignaroli A, Berg J (2018) From wind to loads: wind turbine site-specific load estimation with surrogate models trained on high-fidelity load databases. Wind Energy Sci 3(2):767–790
Eriksson O, Nilsson K, Breton S-P, Ivanell S (2014) The Science of Making Torque from Wind. Analysis of long distance wakes behind a row of turbines–a parameter study. J Phys Conf Ser 524(1):012152. The Science of Making Torque from Wind 2014 (TORQUE 2014) 18–20 June 2014, Copenhagen
Gontier H, Schaffarczyk AP, Kleinhans D, Friedrich R (2007) A comparison of fatigue loads of wind turbine resulting from a non-Gaussian turbulence model vs. standard ones. J Phys Conf Ser 75(1):012070
Han Y, Stoellinger M, Naughton J (2016) Large eddy simulation for atmospheric boundary layer flow over flat and complex terrains. J Phys Conf Ser 753:032044
IEC61400 IEC (2005) 61400-1: wind turbines part 1: design requirements. Int Electrotechnical Commission 177:68–73
Jarrin N, Benhamadouche S, Laurence D, Prosser R (2006) A synthetic-eddy-method for generating inflow conditions for large-eddy simulations. Int J Heat Fluid Flow 27(4):585–593
Jonkman B, Jonkman J (2016) FAST v8.16.00a-bjj. NREL. https://wind.nrel.gov/nwtc/docs/README_FAST8.pdf
Kaimal JC, Wyngaard JCJ, Izumi Y, Cote OR (1972) Spectral characteristics of surface-layer turbulence. Q J R Meteorol Soc 98(417), 563–589
Kim Y, Jost E, Bangga G, Weihing P, Lutz T (2016) Effects of ambient turbulence on the near wake of a wind turbine. J Phys Conf Ser 753:032047
Klein M, Sadiki A, Janicka J (2001a) Influence of the boundary conditions on the direct numerical simulation of a plane turbulent jet. TSFP digital library online. Begel House Inc.
Klein M, Sadiki A, Janicka J (2001b) Influence of the inflow conditions on the direct numerical simulation of primary breakup of liquid jets. In: Proceedings of ILASS Europe, 17. Annual Conference on Liquid Atomization and Spray Systems, pp 475–480
Klein M, Sadiki A, Janicka J (2003) A digital filter based generation of inflow data for spatially developing direct numerical or large eddy simulations. J Comput Phys 186(2):652–665
Kleinhans D, Stochastische Modellierung komplexer Systeme. Ph.D. Thesis
Kolmogorov AN (1991) Dissipation of energy in the locally isotropic turbulence. Proc R Soc Lond Ser A Math Phys Sci 434(1890):15–17
Kornev N, Hassel E (2007) Method of random spots for generation of synthetic inhomogeneous turbulent fields with prescribed autocorrelation functions. Commun Numer Methods Eng 23(1):35–43
Kubilay A, Derome D, Carmeliet J (2016) Analysis of time-resolved wind-driven rain on an array of low-rise cubic buildings using large eddy simulation and an Eulerian multiphase model. Build Environ 114:68–81
Larsen TJ, Hansen AM (2007) How 2 HAWC2, the user’s manual. Risø National Laboratory
Le H, Moin P, Kim J (1997) Direct numerical simulation of turbulent flow over a backward-facing step. J Fluid Mech 330:349–374
Lund TS, Wu X, Kyle D (1998)Squires: generation of turbulent inflow data for spatially-developing boundary layer simulations. J Comput Phys 140(2):233–258
Lygren M, Andersson HI (1999) Influence of boundary conditions on the large-scale structures in turbulent plane couette flow. In: TSFP digital library online. Begel House Inc.
Mücke T, Kleinhans D, Peinke J (2011) Atmospheric turbulence and its influence on the alternating loads on wind turbines. Wind Energy 14(2):301–316
Mann J (1994) The spatial structure of neutral atmospheric surface-layer turbulence. J Fluid Mech 273:141–168
Mann J (1998) Wind field simulation. Probab Eng Mech 13(4):269–282
Mayor SD, Spalart PR, Tripoli GJ (2002) Application of a perturbation recycling method in the large-eddy simulation of a mesoscale convective internal boundary layer. J Atmos Sci 59(15):2385–2395
Morales A, Wächter M, Peinke J (2012) Characterization of wind turbulence by higher-order statistics. Wind Energy 15(3):391–406
Nobach H (1998) Verarbeitung stochastisch abgetasteter Signale: Anwendung in der Laser-Doppler-Anemometrie. Shaker, Aachen
Paulsen S (2018) Uwe: simulation of shear and turbulence impact on wind turbine performance
Reinwardt I, Gerke N, Dalhoff P, Steudel D, Moser W (2018) Validation of wind turbine wake models with focus on the dynamic wake meandering model. J Phys Conf Ser 1037:072028
Reiso M, Muskulus M (2014) Resolution of tower shadow models for downwind mounted rotors and its effects on the blade fatigue. J Phys Conf Ser 555:012084
Sale D, Aliseda A (2016) The flow field of a two-bladed horizontal axis turbine via comparison of RANS and LES simulations against experimental PIV flume measurements. In: Proceedings of the 4th Marine Energy Technology, at Washington, DC
Schwarz CM, Ehrich S, Martin R, Peinke J (2018) Fatigue load estimations of intermittent wind dynamics based on a Blade Element Momentum method. J Phys Conf Ser 1037:072040
Spalart PR (1988) Direct simulation of a turbulent boundary layer up to RΘ = 1410. J Fluid Mech 187:61–98
Stanley SA, Sarkar S (2000) Influence of nozzle conditions and discrete forcing on turbulent planar jets. AIAA J 38(9):1615–1623
Szasz RZ, Fuchs L (2010) Computations of the flow around a wind turbine: grid sensitivity study and the influence of inlet conditions. Notes Numer Fluid Mech 110:345–352
Tabrizi AB, Whale J, Lyons T, Urmee T, Peinke J (2017) Modelling the structural loading of a small wind turbine at a highly turbulent site via modifications to the Kaimal turbulence spectra. Renew Energy 105:288–300
Troldborg N, Sørensen JN, Mikkelsen R (2007) Actuator line simulation of wake of wind turbine operating in turbulent inflow. J Phys Conf Ser 75(1):012063. The Science of Making Torque from Wind 28–31, Technical University of Denmark
van der Laan MP, Andersen S (2018) The turbulence scales of a wind turbine wake: a revisit of extended k-epsilon models. J Phys Conf Ser 1037:072001
Veers P (1984) Modeling stochastic wind loads on vertical axis wind turbines. In: 25th Structures, Structural Dynamics and Materials Conference, p 910
Veers PS (1988) Three-dimensional wind simulation. Sandia National Labs, Albuquerque
Von Karman T (1948) Progress in the statistical theory of turbulence. Proc Natl Acad Sci USA 34(11):530
Wagner R, Courtney M, Larsen TJ, Paulsen US (2010) Simulation of shear and turbulence impact on wind turbine performance. Danmarks Tekniske Universitet, Risø Nationallaboratoriet for Bæredygtig Energi
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this entry
Cite this entry
Ehrich, S. (2020). Turbulent Inflow Models. In: Stoevesandt, B., Schepers, G., Fuglsang, P., Yuping, S. (eds) Handbook of Wind Energy Aerodynamics. Springer, Cham. https://doi.org/10.1007/978-3-030-05455-7_42-1
Download citation
DOI: https://doi.org/10.1007/978-3-030-05455-7_42-1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05455-7
Online ISBN: 978-3-030-05455-7
eBook Packages: Springer Reference EnergyReference Module Computer Science and Engineering