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On the upscaling approach to wind tunnel experiments of horizontal axis hydrokinetic turbines

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Abstract

In this work, we proposed an upscaling methodology to extrapolate results from wind tunnel experiments with small-scale model to the full-size hydrokinetic turbine. Small-scale 1:20 wind tunnel experiments (\({\hbox {Re}}\sim 10^4\)), with a three-blade horizontal axis turbine, were carried out looking to identify the characteristic curves of a full-size turbine operating in water (\({\hbox {Re}}\sim 10^6\)). The lack of dynamic similarity due to unmatched Reynolds numbers is analyzed in the framework of blade element momentum theory arguments. A new semi-empirical power-law equation is achieved, uniquely based on the BEM theory which relates the power coefficients of model and full-size turbine to the Reynolds numbers and a power factor, specific to each turbine. Computational fluid dynamic CFD simulations for the same rotor geometry, simulating different runners with varying diameters from small-scale model to full-scale turbine are carried out to validate the upscaling arguments, and to verify the accuracy of the power coefficient curves predicted by proposed methodology.

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Notes

  1. The scaling effects correspond to discrepancies between model and full-size turbines due to lack of geometric, kinematic and/or dynamic similarity.

  2. The blockage effects are the result of the interference of wind tunnels walls on the rotor efficiency.

  3. Technology Readiness Levels (TRLs) are a method for defining the level of maturity of the technology in the industrial sector developed at NASA [36]. TRL3 (level 3): Proof-of-Concept Demonstrated Analytically and/or Experimentally. TRL4 (level 4): Component and/or Breadboard Laboratory Validated.

References

  1. Adaramola MS, Krogstad PA (2011) Experimental investigation of wake effects on wind turbine performance. Renew Energy 36(8):2078–2086. https://doi.org/10.1016/j.renene.2011.01.024

    Article  Google Scholar 

  2. Ashuri T, Zaaijer MB, Martins JRRA, Zhang J (2016) Multidisciplinary design optimization of large wind turbines—technical, economic, and design challenges. Energy Convers Manag 123:56–70. https://doi.org/10.1016/j.enconman.2016.06.004

    Article  Google Scholar 

  3. Bahaj AS, Molland AF, Chaplin JR, Batten WMJ (2007) Power and thrust measurements of marine current turbines under various hydrodynamic flow conditions in a cavitation tunnel and a towing tank. Renew Energy 32(3):407–426. https://doi.org/10.1016/j.renene.2006.01.012

    Article  Google Scholar 

  4. Bahaj AS, Myers LE (2013) Shaping array design of marine current energy converters through scaled experimental analysis. Energy 59:83–94. https://doi.org/10.1016/j.energy.2013.07.023

    Article  Google Scholar 

  5. Bai CJ, Wang WC (2016) Review of computational and experimental approaches to analysis of aerodynamic performance in horizontal-axis wind turbines {HAWTs}. Renew Sustain Energy Rev 63:506–519. https://doi.org/10.1016/j.rser.2016.05.078

    Article  Google Scholar 

  6. Barnsley MJ, Wellicome JF (1990) Final report on the 2nd phase of development and testing of a horizontal axis wind turbine test rig for the investigation of stall regulation aerodynamics. Technical report, ETSU

  7. Bottasso CL, Campagnolo F, Petrović V (2014) Wind tunnel testing of scaled wind turbine models: beyond aerodynamics. J Wind Eng Ind Aerodyn 127:11–28. https://doi.org/10.1016/j.jweia.2014.01.009

    Article  Google Scholar 

  8. Brasil ACP, Rafael J, Théo CFM, Ricardo W, Taygoara N (2019) On the design of propeller hydrokinetic turbines: the effect of the number of blades. J Braz Soc Mech Sci Eng 41(6):1–14. https://doi.org/10.1007/s40430-019-1753-4

    Article  Google Scholar 

  9. Burton T, Sharpe D, Jenkins N, Bossanyi E (2001) Wind energy handbook. Wiley, Berlin

    Google Scholar 

  10. Cai X, Gu R, Pan P, Zhu J (2016) Unsteady aerodynamics simulation of a full-scale horizontal axis wind turbine using CFD methodology. Energy Convers Manag 112:146–156. https://doi.org/10.1016/j.enconman.2015.12.084

    Article  Google Scholar 

  11. Campagnolo F (2013) Wind tunnel testing of scaled wind turbine models: aerodynamics and beyond. PhD thesis, Politecnico Di Milano

  12. Chen TY, Liou LR (2011) Blockage corrections in wind tunnel tests of small horizontal-axis wind turbines. Exp Thermal Fluid Sci 35(3):565–569. https://doi.org/10.1016/j.expthermflusci.2010.12.005

    Article  Google Scholar 

  13. Cheng M, Zhu Y (2014) The state of the art of wind energy conversion systems and technologies: a review. Energy Convers Manag 88:332–347. https://doi.org/10.1016/j.enconman.2014.08.037

    Article  Google Scholar 

  14. da Silva Holanda P, Blanco CJC, Mesquita ALA, Junior ACPB, de Figueiredo NM, Macêdo EN, Secretan Y (2017) Assessment of hydrokinetic energy resources downstream of hydropower plants. Renew Energy 101:1203–1214. https://doi.org/10.1016/j.renene.2016.10.011

    Article  Google Scholar 

  15. Drela M (1989) XFOIL: an analysis and design system for low Reynolds number airfoils. Springer, New York

    Google Scholar 

  16. Glauert H (1933) Wind tunnel interference on wings, bodies and airserews. Technical report, Aeronautical Research Committee-Reports and Memoranda

  17. Hand MM, Simms DA, Fingersh LJ, Jager DW, Cotrell JR, Schreck S, Larwood SM (2001) Unsteady aerodynamics experiment phase VI: wind tunnel test configurations and available data campaigns. Technical report, NREL

  18. Javaherchi T, Stelzenmuller N, Aliseda A (2017) Experimental and numerical analysis of the performance and wake of a scale-model horizontal axis marine hydrokinetic turbine. J Renew Sustain Energy 9(4):44–54. https://doi.org/10.1063/1.4999600

    Article  Google Scholar 

  19. Khan MJ, Bhuyan G, Iqbal MT, Quaicoe JE (2009) Hydrokinetic energy conversion systems and assessment of horizontal and vertical axis turbines for river and tidal applications: a technology status review. Appl Energy 86(10):1823–1835. https://doi.org/10.1016/j.apenergy.2009.02.017

    Article  Google Scholar 

  20. Kinsey T, Dumas G, Lalande G, Ruel J, Méhut A, Viarouge P, Lemay J, Jean Y (2011) Prototype testing of a hydrokinetic turbine based on oscillating hydrofoils. Renew Energy 36(6):1710–1718. https://doi.org/10.1016/j.renene.2010.11.037

    Article  Google Scholar 

  21. Koh WXM, Ng EYK (2017) A CFD study on the performance of a tidal turbine under various flow and blockage conditions. Renew Energy 107:124–137. https://doi.org/10.1016/j.renene.2017.01.052

    Article  Google Scholar 

  22. Laws ND, Epps BP (2016) Hydrokinetic energy conversion: technology, research, and outlook. Renew Sustain Energy Rev 57:1245–1259. https://doi.org/10.1016/j.rser.2015.12.189

    Article  Google Scholar 

  23. Leimeister M, Bachynski EE, Muskulus M, Thomas P (2016) Rational upscaling of a semi-submersible floating platform supporting a wind turbine. Energy Proc 94:434–442. https://doi.org/10.1016/j.egypro.2016.09.212

    Article  Google Scholar 

  24. Lignarolo LEM, Ragni D, Krishnaswami C, Chen Q, Ferreira CJS, van Bussel GJW (2014) Experimental analysis of the wake of a horizontal-axis wind-turbine model. Renew Energy 70(Supplement C):31–46. https://doi.org/10.1016/j.renene.2014.01.020

    Article  Google Scholar 

  25. Lungo GV, Wu YT, Porté-Agel F (2013) Field measurements of wind turbine wakes with lidars. J Atmos Ocean Technol 30(2):274–287. https://doi.org/10.1175/JTECH-D-12-00051.1

    Article  Google Scholar 

  26. Maganga F, Germain G, King J, Pinon G, Rivoalen E (2010) Experimental characterisation of flow effects on marine current turbine behaviour and on its wake properties. IET Renew Power Gener 4:498

    Google Scholar 

  27. Mikkelsen R, Sorensen JN (2002) Modelling of wind tunnel blockage. In: Proceeding of the 2002 global windpower conference and exhibition

  28. Miller MA, Duvvuri S, Brownstein I, Lee M, Dabiri JO, Hultmark M (2018) Vertical-axis wind turbine experiments at full dynamic similarity. J Fluid Mech. https://doi.org/10.1017/jfm.2018.197

    Article  MATH  Google Scholar 

  29. Mo JO, Lee YH (2012) CFD Investigation on the aerodynamic characteristics of a small-sized wind turbine of NREL PHASE VI operating with a stall-regulated method. J Mech Sci Technol 26(1):81–92. https://doi.org/10.1007/s12206-011-1014-7

    Article  Google Scholar 

  30. Monteiro JP, Silvestre MR, Piggott H, Andre JC (2013) Wind tunnel testing of a horizontal axis wind turbine rotor and comparison with simulations from two Blade Element Momentum codes. J Wind Eng Ind Aerodyn 123:99–106. https://doi.org/10.1016/j.jweia.2013.09.008

    Article  Google Scholar 

  31. Moshfeghi M, Jun Song Y, Xie Y (2012) Effects of near-wall grid spacing on SST-K-\(\omega\) model using NREL Phase VI horizontal axis wind turbine. J Wind Eng Ind Aerodyn 107:94–105

    Google Scholar 

  32. Nunes MM, Mendes RCF, Oliveira TF, Junior ACPB (2019) An experimental study on the diffuser-enhanced propeller hydrokinetic turbines. Renew Energy 133:840–848. https://doi.org/10.1016/j.renene.2018.10.056

    Article  Google Scholar 

  33. Oggiano L (2014) CFD simulations on the NTNU wind turbine rotor and comparison with experiments. Energy Proc 58:111–116

    Google Scholar 

  34. Rezaeiha A, Montazeri H, Blocken B (2018) Towards accurate CFD simulations of vertical axis wind turbines at different tip speed ratios and solidities: guidelines for azimuthal increment, domain size and convergence. Energy Convers Manag 156:301–316. https://doi.org/10.1016/j.enconman.2017.11.026

    Article  Google Scholar 

  35. Ryi J, Rhee W, Hwang UC, Choi JS (2015) Blockage effect correction for a scaled wind turbine rotor by using wind tunnel test data. Renew Energy 79:227–235. https://doi.org/10.1016/j.renene.2014.11.057

    Article  Google Scholar 

  36. Sadin Stanley R, Povinelli Frederick P, Rosen R (1988) The NASA technology push towards future space mission systems. In: IAF, international astronautical congress, 39th, Bangalore, India, Oct. 8–15, p 6

  37. Sieros G, Chaviaropoulos P, Sørensen JD, Bulder BH, Jamieson P (2012) Upscaling wind turbines: theoretical and practical aspects and their impact on the cost of energy. Wind Energy 15(1):3–17. https://doi.org/10.1002/we.527

    Article  Google Scholar 

  38. Silva PASF, de Oliveira TF, Brasil Junior ACP, Vaz JRP (2016) Numerical study of wake characteristics in a horizontal-axis hydrokinetic turbine. Anais Acad Bras Ciencias 88:2441–2456

    Google Scholar 

  39. Silva PASF, Shinomiya LD, de Oliveira TF, Vaz JRP, Amarante Mesquita AL, Brasil Junior ACP (2017) Analysis of cavitation for the optimized design of hydrokinetic turbines using BEM. Appl Energy 185:1281–1291. https://doi.org/10.1016/j.apenergy.2016.02.098

    Article  Google Scholar 

  40. Silva PASF, Vaz DATDR, Britto V, de Oliveira TF, Vaz JRP, Junior ACPB (2018) A new approach for the design of diffuser-augmented hydro turbines using the blade element momentum. Energy Convers Manag 165:801–814. https://doi.org/10.1016/j.enconman.2018.03.093

    Article  Google Scholar 

  41. Simms D, Schreck S, Hand M, Fingersh LJ (2001) NREL unsteady aerodynamics experiment in the NASA-Ames wind tunnel: a comparison of predictions to measurements. https://doi.org/10.2172/783409

  42. Snel H, Schepers JG, Montgomerie B (2007) The MEXICO project (model experiments in controlled conditions): the database and first results of data processing and interpretation. J Phys Conf Ser 75(1):12014

    Google Scholar 

  43. Sorensen NN, Michelsen JA, Schreck S (2002) Navier-Stokes predictions of the NREL Phase VI rotor in the NASA Ames 80 ft 120 ft wind tunnel. Wind Energy 5(2–3):151–169. https://doi.org/10.1002/we.64

    Article  Google Scholar 

  44. Talavera M, Shu F (2017) Experimental study of turbulence intensity influence on wind turbine performance and wake recovery in a low-speed wind tunnel. Renew Energy 109:363–371. https://doi.org/10.1016/j.renene.2017.03.034

    Article  Google Scholar 

  45. Tangler JL (2002) The nebulous art of using wind tunnel aerofoil data for predicting rotor performance. Wind Energy 5(2–3):245–257. https://doi.org/10.1002/we.71

    Article  Google Scholar 

  46. Vásquez FAM, de Oliveira TF, Junior ACPB (2016) On the electromechanical behavior of hydrokinetic turbines. Energy Convers Manag 115:60–70. https://doi.org/10.1016/j.enconman.2016.02.039

    Article  Google Scholar 

  47. Vaz JRP, Mesquita ALA, Mesquita ALA, de Oliveira TF, Junior ACPB (2019) Powertrain assessment of wind and hydrokinetic turbines with diffusers. Energy Convers Manag 195:1012–1021. https://doi.org/10.1016/j.enconman.2019.05.050

    Article  Google Scholar 

  48. Wen B, Tian X, Dong X, Li Z, Peng Z (2019) Design approaches of performance-scaled rotor for wave basin model tests of floating wind turbines. Renew Energy. https://doi.org/10.1016/j.renene.2019.10.147

    Article  Google Scholar 

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Acknowledgements

This work was conducted during a scholarship at the University of Cádiz supported by the International Cooperation Program of the CAPES—Finance Code 001 (Brazilian Federal Agency within the Ministry of Education of Brasil). It was partially supported also by ELETROBRAS-FURNAS S/A by grants for the validation of Numerical Simulations of Wind Turbines, in the framework of Brazilian Energy Agency (ANEEL) R&D funding actions and by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (BR) (Grant No. 303835/2018-4).

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  1. Energy and Environmental Laboratory, Mechanical Engineering Department, University of Brasilia, Brasília, DF, 70910-900, Brazil

    Marianela M. Macias, Rafael C. F. Mendes, Taygoara F. Oliveira & Antonio C. P. Brasil Jr.

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  1. Marianela M. Macias
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  2. Rafael C. F. Mendes
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Correspondence to Marianela M. Macias.

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Macias, M.M., Mendes, R.C.F., Oliveira, T.F. et al. On the upscaling approach to wind tunnel experiments of horizontal axis hydrokinetic turbines. J Braz. Soc. Mech. Sci. Eng. 42, 539 (2020). https://doi.org/10.1007/s40430-020-02600-2

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