0
Research Papers

Optimization of the Taper/Twist Stacking Axis Location of NREL VI Wind Turbine Rotor Blade Using Neural Networks Based on Computational Fluid Dynamics Analyses

[+] Author and Article Information
Mustafa Kaya

Aeronautical Engineering Department,
Ankara Yidirim Beyazit University,
Havacilik ve Uzay Bilimleri Fakultesi, Ulus,
Ankara 06050, Turkey
e-mail: mukaya@ybu.edu.tr

Munir Elfarra

Ankara Yidirim Beyazit University,
Havacilik ve Uzay Bilimleri Fakultesi, Ulus,
Ankara 06050, Turkey
e-mail: melfarra@ybu.edu.tr

1Corresponding author.

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received February 12, 2018; final manuscript received July 20, 2018; published online September 14, 2018. Assoc. Editor: Yves Gagnon.

J. Sol. Energy Eng 141(1), 011011 (Sep 14, 2018) (14 pages) Paper No: SOL-18-1067; doi: 10.1115/1.4041102 History: Received February 12, 2018; Revised July 20, 2018

The stacking axis locations for twist and taper distributions along the span of a wind turbine blade are optimized to maximize the rotor torque and/or to minimize the thrust. A neural networks (NN)-based model is trained for the torque and thrust values calculated using a computational fluid dynamics (CFD) solver. Once the model is obtained, constrained and unconstrained optimization is conducted. The constraints are the torque or the thrust values of the baseline turbine blade. The baseline blade is selected as the wind turbine blade used in the National Renewable Energy Laboratory (NREL) Phase VI rotor model. The Reynolds averaged Navier–Stokes (RANS) computations are done using the FINE/turbo flow solver developed by NUMECA International. The k-epsilon turbulence model is used to calculate the eddy viscosity. It is observed that achieving the same torque value as the baseline value is possible with about 5% less thrust. Similarly, the torque is increased by about 4.5% while maintaining the baseline thrust value.

Copyright © 2019 by ASME
Your Session has timed out. Please sign back in to continue.

References

Sessarego, M. , Ramos-Garcia, N. , Yang, H. , and Shen, W. Z. , 2016, “Aerodynamic Wind-Turbine Rotor Design Using Surrogate Modeling and Three-Dimensional Viscous-Inviscid Interaction Technique,” Renewable Energy, 93, pp. 620–635. [CrossRef]
Dai, J. C. , Hu, Y. P. , Liu, D. S. , and Long, X. , 2011, “Aerodynamic Loads Calculation and Analysis for Large Scale Wind Turbine Based on Combining BEM Modified Theory With Dynamic Stall Model,” Renewable Energy, 36(3), pp. 1095–1104. [CrossRef]
Robison, D. J. , Coton, F. N. , Galbraith, R. A. M. C. D. , and Vezza, M. , 1995, “Application of a Prescribed Wake Aerodynamic Prediction Scheme to Horizontal Axis Wind Turbines in Axial Flow,” Wind Eng., 19(1), pp. 41–51. https://www.jstor.org/stable/43749564
Ashuri, T. , Zhang, T. , Qian, D. , and Rotea, M. , 2016, “Uncertainty Quantification of the Levelized Cost of Energy for the 20 MW Research Wind Turbine Model,” AIAA Paper. No. 2016-1998.
Castillo Capponi, P. , Ashuri, T. , Van Bussel, G. J. W. , and Kallesoe, B. , 2011, “A Non-Linear Upscaling Approach for Wind Turbines Blades Based on Stresses,” European Wind Energy Conference, Brussels, Belgium, Mar. 14–17, pp. 1–8.
Afjeh, A. A. , and Keith, T. G. , 1986, “A Vortex Lifting Line Method for the Analysis of Horizontal Axis Wind Turbines,” ASME J. Sol. Energy Eng., 108(4), pp. 303–309. [CrossRef]
Ashuri, T. , Martins, J. R. R. A. , Zaaijer, M. B. , van Kuik, G. A. M. , van Bussel ., and Gerard, J. W. , 2016, “Aeroservoelastic Design Definition of a 20 MW Common Research Wind Turbine Model,” Wind Energy, 19(11), pp. 2071–2087. [CrossRef]
Ning, A. , and Petch, D. , 2016, “Integrated Design of Downwind Land-Based Wind Turbines Using Analytic Gradients,” Wind Energy, 19(12), pp. 2137–2152. [CrossRef]
Dhert, T. , Ashuri, T. , and Martins, J. R. R. A. , 2016, “Aerodynamic Shape Optimization of Wind Turbine Blades Using a Reynolds-Averaged Navier–Stokes Model and an Adjoint Method,” Wind Energy, 20(5), pp. 909–926. [CrossRef]
Chattot, J.-J. , 2003, “Optimization of Wind Turbines Using Helicoidal Vortex Model,” ASME J. Sol. Energy Eng., 125(4), pp. 418–424. [CrossRef]
Wijnen, M. , and Chattot, J.-J. , 2011, “Multi-Point Optimization of Wind Turbine Blades Using Helicoidal Vortex Model,” Computational Fluid Dynamics 2010, A. Kuzmin , ed., Springer, Berlin, pp. 235–240.
Johansen, J. , and Sørensen, N. N. , 2006, “Aerodynamic Investigation of Winglets on Wind Turbine Blades Using CFD,” Risø National Laboratory, Roskilde, Denmark, Report No. Risø-R-1543(EN). http://orbit.dtu.dk/en/publications/aerodynamic-investigation-of-winglets-on-wind-turbine-blades-using-cfd(81167298-0483-4d7a-8d25-f5aa47130927).html
Elfarra, M. A. , Uzol, N. S. , and Akmandor, I. S. , 2013, “NREL VI Rotor Blade: Numerical Investigation and Winglet Design and Optimization Using CFD,” Wind Energy, 17(4), pp. 605–626. [CrossRef]
Elfarra, M. A. , Uzol, N. S. , and Akmandor, I. S. , 2015, “Investigations on Blade Tip Tilting for HAWT Rotor Blades Using CFD,” Int. J. Green Energy, 12(2), pp. 125–138. [CrossRef]
Economon, T. D. , Palacios, F. , and Alonso, J. J. , 2013, “A Viscous Continuous Adjoint Approach for the Design of Rotating Engineering Applications,” AIAA Paper. No. 2013-2580.
Amano, R. S. , and Malloy, R. J. , 2009, “Aerodynamic Comparison of Straight Edge and Swept Edge Wind Turbine Blade,” AIAA Paper. No. 2009-1208.
Larwood, S. , van Dam, C. P. , and Schow, D. , 2014, “Design Studies of Swept Wind Turbine Blades,” Renewable Energy, 71, pp. 563–571. [CrossRef]
Suzuki, K. , Schmitz, S. , and Chattot, J.-J. , 2010, “Analysis of a Swept Wind Turbine Blade Using a Hybrid Navier–Stokes/Vortex-Panel Model,” Sixth International Conference on Computational Fluid Dynamics (ICCFD6), St Petersburg, Russia, July 12–16, pp. 213–218. https://pennstate.pure.elsevier.com/en/publications/analysis-of-a-swept-wind-turbine-blade-using-a-hybrid-navier-stok
Zuo, H. M. , Liu, C. , Yang, H. , and Wang, F. , 2016, “Numerical Study on the Effect of Swept Blade on the Aerodynamic Performance of Wind Turbine at High Tip Speed Ratio,” J. Phys.: Conf. Ser., 753, p. 102010. [CrossRef]
Shen, X. , Yang, H. , Chen, J. , Zhu, X. , and Du, Z. , 2016, “Aerodynamic Shape Optimization of Non-Straight Small Wind Turbine Blades,” Energy Convers. Manage., 119, pp. 266–278. [CrossRef]
Vesel , R. W., Jr , and McNamara, J. J. , 2014, “Performance Enhancement and Load Reduction of a 5 MW Wind Turbine Blade,” Renewable Energy, 66, pp. 391–401. [CrossRef]
Chattot, J. J. , 2009, “Effects of Blade Tip Modifications on Wind Turbine Performance Using Vortex Model,” Comput. Fluids, 38(7), pp. 1405–1410. [CrossRef]
Shen, X. , Chen, J.-G. , Zhu, X.-C. , Liu, P.-Y. , and Du, Z.-H. , 2015, “Multi-Objective Optimization of Wind Turbine Blades Using Lifting Surface Method,” Energy, 90, pp. 1111–1121. [CrossRef]
Amano, R. S. , and Malloy, R. J. , 2008, “Aerodynamic Comparison of Straight Edge and Swept Edge Wind Turbine Blade,” ASME Paper No. IMECE2008-69285.
Verelst , D. R. , and Larsen, T. J. , 2010, “Load Consequences When Sweeping Blades—A Case Study of a 5 MW Pitch Controlled Wind Turbine,” Risø DTU National Laboratory for Sustainable Energy, Roskilde, Denmark, Report No. Risø-R-1724(EN). http://orbit.dtu.dk/en/publications/load-consequences-when-sweeping-blades--a-case-study-of-a-5-mw-pitch-controlled-wind-turbine(d0774b4a-ef6a-4fb4-bbd6-0120c36751af).html
Lee, K.-H. , Kim, K.-H. , Lee, D.-H. , Lee, K.-T. , and Park, J.-P. , 2010, “Two-Step Optimization for Wind Turbine Blade With Probability Approach,” ASME J. Sol. Energy Eng., 132(3), p. 034503. [CrossRef]
Bourguet, R. , Martinat, G. , Harran, G. , and Braza, M. , 2007, “Aerodynamic Multi-Criteria Shape Optimization of VAWT Blade Profile by Viscous Approach,” Wind Energy, J. Peinke , P. Schaumann , and S. Barth , eds., Springer, Berlin, pp. 215–219.
Sun, H. , 2011, “Wind Turbine Airfoil Design Using Response Surface Method,” J. Mech. Sci. Technol., 25(5), pp. 1335–1340. [CrossRef]
Han, Z. , Zhang, K. , Song, W. , and Liu, J. , 2013, “Surrogate-Based Aerodynamic Shape Optimization With Application to Wind Turbine Airfoils,” AIAA Paper. No. 2013-1108.
Ribeiro, A. , Awruch, A. , and Gomes, H. , 2012, “An Airfoil Optimization Technique for Wind Turbines,” Appl. Math. Model., 36(10), pp. 4898–4907. [CrossRef]
NUMECA International, 2017, “FINETM/Turbo Software Package,” ver.11.2rc, User Manual, Numeca, Brussels, Belgium.
NUMECA International, 2017, “IGGTM/AutoGrid5TM Software Package,” ver.11.2rc, User Manual, Numeca, Brussels, Belgium.
Hand, M. , Simms, D. , Fingersh, L. , Jager, D. , Cotrell, J. , Schreck, S. , and Larwood, S. , 2001, “Unsteady Aerodynamics Experiment Phase VI: Wind Tunnel Test Configurations and Available Data Campaigns,” National Renewable Energy Laboratory, Golden, CO, Report No. NREL/TP 500-29955. https://www.nrel.gov/docs/fy02osti/29955.pdf
Giguere, P. , and Selig, M. S. , 1999, “Design of a Tapered and Twisted Blade for the NREL Combined Experiment Rotor,” National Renewable Energy Laboratory, Golden, CO, Report No. NREL/SR-500-26173. https://www.nrel.gov/docs/fy99osti/26173.pdf
Hagan, M. T. , and Menhaj, M. B. , 1994, “Training Feed-Forward Networks With the Marquardt Algorithm,” IEEE Trans. Neural Networks, 5(6), pp. 989–993. [CrossRef]
Vanderplaats, G. N. , 2001, “Numerical Optimization Techniques for Engineering Design,” 3rd ed., Vanderplaats Research and Development, Colorado Springs, CO, Chap. 5.
Wilde, D. J. , 1964, Optimum Seeking Methods, 1st ed., Prentice Hall, Englewood Cliffs, NJ.

Figures

Grahic Jump Location
Fig. 1

O4H grid bloc k structure used

Grahic Jump Location
Fig. 2

Schematic for the neural network model used in this study

Grahic Jump Location
Fig. 3

Three-dimensional mesh structure of the baseline blade

Grahic Jump Location
Fig. 4

Comparison of computed torque with experimental torque. Bars show one standard deviation from the average of the experimental data.

Grahic Jump Location
Fig. 5

Comparison of pressure coefficient distribution at different spanwise sections for 5 m/s wind speed

Grahic Jump Location
Fig. 6

Design of experiment

Grahic Jump Location
Fig. 7

Top view of the blade planforms according to the different taper stacking axis locations: (a) baseline blade (sample 2), (b) taper stacking axis at leading edge (sample 7), (c) taper stacking axis at 50% chord (sample 8), (d) taper stacking axis at 80% chord (sample 9), and (e) taper stacking axis at trailing edge (sample 10)

Grahic Jump Location
Fig. 8

Blade section at 20% span for different twist stacking axis locations. Dotted profile is the baseline airfoil: (a) twist stacking axis at leading edge (sample 1), (b) twist stacking axis at 50% chord (sample 3), (c) twist stacking axis at 80% chord (sample 4), and (d) twist stacking axis at trailing edge (sample 5).

Grahic Jump Location
Fig. 9

Performance of the NN training

Grahic Jump Location
Fig. 10

Surfaces given by NN. Dots show values computed by CFD: (a) torque and (b) thrust.

Grahic Jump Location
Fig. 11

Optimization steps for constrained torque maximization: (a) path of the optimization variables and (b) torque values along the iterations

Grahic Jump Location
Fig. 12

Optimization steps for constrained thrust minimization: (a) path of the optimization variables and (b) thrust values along the iterations

Grahic Jump Location
Fig. 13

Skin friction coefficient distribution along the chord of the blade optimized for constrained torque at different span locations

Grahic Jump Location
Fig. 14

Skin friction coefficient distribution along the chord of the blade optimized for unconstrained torque at different span locations

Grahic Jump Location
Fig. 15

Pressure coefficient distribution along the chord of the blade optimized for constrained thrust at different span locations

Grahic Jump Location
Fig. 16

Pressure coefficient distribution along the chord of the blade optimized for unconstrained thrust at different span locations

Tables

Errata

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In