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Long-term fatigue reliability enhancement of horizontal axis wind turbine blade

  • Sajeer, M. Mohamed (Department of Civil Engineering, Indian Institute of Technology Guwahati) ;
  • Chakraborty, Arunasis (Department of Civil Engineering, Indian Institute of Technology Guwahati)
  • Received : 2021.01.04
  • Accepted : 2021.08.25
  • Published : 2021.08.25

Abstract

The enhancement of fatigue life of ultra-large horizontal axis wind turbine blade using longitudinal stiffening is the theme of this work. For this purpose, a tendon made of shape memory alloy is used along the longitudinal axis of blade, which is modelled in aeroelastic spinning finite element framework. The force developed in the tendon acts against the deformation where the material is modelled using Liang and Rogers constitutive relationship along with the principles of thermodynamics. The fatigue design follows the guidelines provided in internationally recognised codal provisions. The blade responses are simulated using aeroelastic loads obtained from blade element momentum theory. These dynamic responses are utilised to evaluate the longitudinal stress in the extreme fibre over the blade profile. Then, short-term and long-term damages are evaluated using rainflow matrix obtained from these stresses. Finally, the reliability of blade against fatigue failure is investigated. The numerical analysis presented in this study clearly demonstrates the performance of the longitudinal stiffening in combination with pitch angle on the fatigue life of the blade.

Keywords

References

  1. Agarwala, R. and Ro, P.I., (2015), "Separated pitch control at tip: innovative blade design explorations for large NW wind turbine blades", J. Wind Energy, 2015, 1-12. https://doi.org/10.1155/2015/895974.
  2. Bathe, K.J. (2006), Finite element procedures, PHI Learning Private Limited, Delhi, India.
  3. Berg, D.E., Johnson, S.J. and Van Dam, C.P. (2008), Active Load Control Techniques for Wind Turbines, Research Report No. SAND2008-4809. Sandia National Laboratories.
  4. Bolat, F. and Sivrioglu, S. (2018), "Active control of a small-scale wind turbine blade containing magnetorheological fluid", Micromachines, 9(2), 80. https://doi.org/10.3390/mi9020080.
  5. Burton, T., Jenkins, N., Sharpe, D. and Bossanyi, E. (2011), Wind Energy Handbook, John Wiley & Sons, Chichester, West Sussex, U.K. https://doi.org/10.1002/9781119992714.
  6. Cao, Y., Zavala, V.M. and DAmato, F. (2018), "Using stochastic programming and statistical extrapolation to mitigate long-term extreme loads in wind turbines", Appl. Energy 230, 1230-1241. https://doi.org/10.1016/j.apenergy.2018.09.062.
  7. Capuzzi, M., Pirrera, A. and Weaver, P. (2014), "A novel adaptive blade concept for large-scale wind turbines. Part I: Aeroelastic behaviour", Energy, 73, 15-24. https://doi.org/10.1016/j.energy.2014.06.044.
  8. Capuzzi, M., Pirrera, A. and Weaver, P. (2014), "A novel adaptive blade concept for large-scale wind turbines. Part II: Structural design and power performance", Energy, 73, 25-32. https://doi.org/10.1016/j.energy.2014.04.073.
  9. Capuzzi, M., Pirrera, A. and Weaver, P. (2015), "Structural design of a novel aeroelastically tailored wind turbine blade", Thin-Walled Struct., 95, 7-15. https://doi.org/10.1016/j.tws.2015.06.006.
  10. Chehouri, A., Younes, R., Ilinca, A. and Perron, J. (2015), "Review of performance optimization techniques applied to wind turbines", Appl. Energy, 142, 361-388. https://doi.org/10.1016/j.apenergy.2014.12.043.
  11. Chen, J., Yuan, C., Li, J. and Xu, Q. (2015), "Semi-active fuzzy control of edgewise vibrations in wind turbine blades under extreme wind", J. Wind Eng. Ind. Aerod., 147, 251-261. https://doi.org/10.1016/j.jweia.2015.10.012.
  12. Das, S., Sajeer, M.M. and Chakraborty, A. (2019), "Vibration control of horizontal axis offshore wind turbine blade using sma stiffener", Smart Mater. Struct., 28(9), 095025. https://doi.org/10.1088/1361-665X/ab1174.
  13. Das, S., Sajeer, M.M., Chakraborty, A. and Sarkar, S. (2019), "Shape memory alloy-based centrifugal stiffening for response reduction of horizontal axis wind turbine blade", Struct Control Health Monit, 2020, e2669. https://doi.org/10.1002/stc.2669.
  14. Downing, S.D. and Socie, D. (1982), "Simple rainflow counting algorithms", Int. J, Fatigue, 4(1), 31-40. https://doi.org/10.1016/0142-1123(82)90018-4.
  15. Elmaati, Y.A., El Bahir, L. and Faitah, K. (2015), "An integrator based wind speed estimator for wind turbine control", Wind Struct., 21(4), 443-460. http://dx.doi.org/10.12989/was.2015.21.4.443.
  16. Epaarachchi, J.A. and Clausen, P.D. (2003), "An empirical model for fatigue behavior prediction of glass fibre-reinforced plastic composites for various stress ratios and test frequencies", Compos. Part A: Appl. Sci. Manufact., 34(4), 313-326. https://doi.org/10.1016/s1359-835x(03)00052-6.
  17. FAST v8, (2016), NREL's primary physics-based engineering tool for simulating the coupled dynamic response of wind turbines, NWTC Information Portal, Golden, Colorado. https://nwtc.nrel.gov/FAST8, [Last modified on 04-January-2018; Accessed on 04-December-2019].
  18. Fischer, T., De Vries, W. and Schmidt, B. (2010), "Upwind design basis (wp4: Offshore foundations and support structures)", Upwind.
  19. Goodman, J. (1918), Mechanics Appl. Eng., Longmans, Green, and Co. London.
  20. Greaves, P.R., Dominy, R.G., Ingram, G.L., Long, H. and Court, R. (2011), "Evaluation of dualaxis fatigue testing of large wind turbine blades", Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 226(7), 1693-1704. https://doi.org/10.1177/0954406211428013.
  21. Haghdoust, P., Cinquemani, S. and Conte, A.L. (2018), "Preliminary studies on SMA embedded wind turbine blades for passive control of vibration", Active Passive Smart Struct. Integrat. Syst. XII, Int. Soc. for Optics Photonics, 10595, 105953B. https://doi.org/10.1117/12.2292645.
  22. Haliade-x Offshore Turbine (2020), G.E. Renewable Energy, https://www.ge.com/renewableenergy/wind-energy/offshorewind/haliade-x-offshore-turbine
  23. IEC 61400-3 (2009), Wind turbines - part 3: Design requirements for offshore wind turbines, Int. Electrotech. Commission. https://doi.org/10.3403/30170387.
  24. Jagadeesh, V., Yuvaraja, M., Chandhru, A. and Viswanathan, P. (2018), "Investigations on vibration characteristics of sma embedded horizontal axis wind turbine blade", IOP Conference Series: Materials Science and Engineering, IOP Publishing, 310(1), 012067. https://doi.org/10.1088/1757-899x/310/1/012067.
  25. Jonkman, B.J. (2009), TurbSim User's Guide, National Renewable Energy Laboratory, Report No. NREL/TP-500-46198, Golden, Colorado. https://doi.org/10.2172/965520.
  26. Jonkman, J., Butterfield, S., Musial, W. and Scott, G. (2009), Definition of a 5-MW reference wind turbine for offshore system development, National Renewable Energy Laboratory, Report No. NREL/TP-500-38060, Golden, Colorado. https://doi.org/10.2172/947422.
  27. Jonkman, J.M. and Buhl Jr, M.L., (2005), Fast User's Guide, National Renewable Energy Laboratory, Report No. NREL/TP-500-38230, Golden, Colorado. https://doi.org/10.2172/15020796.
  28. Krenk, S., Svendsen, M.N. and Hogsberg, J. (2012), "Resonant vibration control of three-bladed wind turbine rotors", AIAA J., 50(1), 148-161. https://doi.org/10.2514/1.j051164.
  29. Kucuk, M., Cetin, N.S. and Emeksiz, C. (2012), "Stress analysis of shape memory alloys used in wind turbine blade root connection", Energy Edu. Sci. Technol. Part A: Energy Sci. Res., 30, 667-676.
  30. Kusiak, A. Li, W. and Song, Z. (2010), "Dynamic control of wind turbines", Renew. Energy, 35(2), 456-463. https://doi.org/10.1016/j.renene.2009.05.022.
  31. Lachenal, X., Daynes, S. and Weaver, P.M. (2013), "Review of morphing concepts and materials for wind turbine blade applications", Wind Energy, 16(2), 283-307. https://doi.org/10.1002/we.531.
  32. Lee, J.W., Kim, J.K., Han, J.H., and Shin, H.K., (2013), "Active load control for wind turbine blades using trailing edge flap", Wind Struct., 16(3), 263-278. http://dx.doi.org/10.12989/was.2013.16.3.263.
  33. Liang, C. and Rogers, C.A. (1997), "One-dimensional thermomechanical constitutive relations for shape memory materials", J. Intel. Mater. Syst. Struct., 8(4), 285-302. https://doi.org/10.2514/6.1990-1027.
  34. Liu, T. (2015), "Classical flutter and active control of wind turbine blade based on piezoelectric actuation", Shock Vib., 2015. https://doi.org/10.1155/2015/292368.
  35. Liu, T. and Liu, G. (2018), "Vibration control of rotating piezocomposite blade beam with CUS configuration based on optimal LQG controller", J. Vibroeng., 20(1), 427-447. https://doi.org/10.1016/j.apenergy.2015.11.080.
  36. Mani, Y., Veeraragu, J., Sangameshwar, S. and Rangaswamy, R. (2020), "Dynamic behavior of smart material embedded wind turbine blade under actuated condition", Wind Struct., 30(2), 211-217. http://dx.doi.org/10.12989/was.2020.30.2.211.
  37. Mirzaei Rafsanjani, H., Sorensen, J.D., Faester, S. and Sturlason, A., (2017), "Fatigue reliability analysis of wind turbine cast components", Energies, 10(4), 466. https://doi.org/10.3390/en10040466.
  38. Ning, A. Hayman G., Damiani R. and Jonkman, J.M. (2015), "Development and validation of a new blade element momentum skewed-wake model within aerodyn", 33rd Wind Energy Symposium, 2015, 0215. https://doi.org/10.2514/6.2015-0215.
  39. Ning, S.A. (2014), "A simple solution method for the blade element momentum equations with guaranteed convergence", Wind Energy, 17(9), 1327-1345. https://doi.org/10.1002/we.1636.
  40. Noyes, C. Loth, E. Martin, D., Johnson, K., Ananda, G. and Selig, M. (2020), "Extreme-scale load aligning rotor: To hinge or not to hinge?", Appl. Energy, 257, 113985. https://doi.org/10.1016/j.apenergy.2019.113985.
  41. Pechlivanoglou, G., Wagner, J., Nayeri, C. and Paschereit, C. (2010), "Active aerodynamic control of wind turbine blades with high deflection flexible flaps", 48th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, 644. https://doi.org/10.2514/6.2010-644.
  42. Pern, N., Jacob, J. and Lebeau, R. (2006), "Characterization of zero mass flux flow control for separation control of an adaptive airfoil", 3rd AIAA Flow Control Conference, 2006, 3032. https://doi.org/10.2514/6.2006-3032.
  43. Qiao, Y.H., Han, J., Zhang, C.Y., Chen, J.P. and Yi, K.C. (2012), "Finite element analysis and vibration suppression control of smart wind turbine blade", Appl. Compos. Mater., 19(3-4), 747-754. https://doi.org/10.1007/s10443-011-9236-5.
  44. Rehman, S., Alam, M. and Alhems, L.M. (2020), "A review of wind-turbine structural stability, failure and alleviation", Wind Struct., 30(5), 511-524. http://dx.doi.org/10.12989/was.2020.30.5.511.
  45. Resor, B.R. (2013), Definition of a 5MW/61.5 m Wind Turbine Blade Reference Model, Report No. SAND2013-2569, Albuquerque, New Mexico, USA, Sandia National Laboratories. https://doi.org/10.2172/1095962.
  46. Sajeer, M.M., Chakraborty, A. and Das, S. (2020), "An efficient vibration control strategy for reliability enhancement of HAWT blade", Smart Struct. Syst., 26(6). http://dx.doi.org/10.12989/sss.2020.26.6.703.
  47. Sajeer, M.M., Mitra, A. and Chakraborty, A. (2020), "Spinning finite element analysis of longitudinally stiffened horizontal axis wind turbine blade for fatigue life enhancement", Mech. Syst. Signal Proc., 145, 106924. https://doi.org/10.1016/j.ymssp.2020.106924.
  48. Seebregts, A., Rademakers, L. and Van Den Horn, B. (1995), "Reliability analysis in wind turbine engineering", Microelectron. Reliability, 35(9-10), 1285-1307. https://doi.org/10.1016/0026-2714(95)99378-V.
  49. Song, D., Yang, J., Cai, Z., Dong, M., Su, M. and Wang, Y. (2017), "Wind estimation with a nonstandard extended kalman filter and its application on maximum power extraction for variable speed wind turbines", Appl. Energy, 190, 670-685. https://doi.org/10.1016/j.apenergy.2016.12.132.
  50. Thomson, W. (1996), Theory of Vibration with Applications, Dorling Kindersley, India.
  51. Tippmann, J.D. and di Scalea, F.L. (2014), "Vibration control experiments using piezoelectric transducers on a wind turbine blade", Sensors Smart Struct. Technol. Civil Mech. Aerosp. Syst., Int. Soc. Optics Photonics, 8692, 86921H. https://doi.org/10.1117/12.2009534.
  52. TurbSim (2008), NWTC Information Portal. https://nwtc.nrel.gov/TurbSim
  53. Van Dam, C., Berg, D.E. and Johnson, S.J. (2008), "Active load control techniques for wind turbines", Tech. Rep., Sandia Nat. Lab., https://doi.org/10.2172/943932.
  54. Wilson, D.G., Berg, D.E., Barone, M.F., Berg, J.C., Resor, B.R. and Lobitz, D.W. (2009), "Active aerodynamic blade control design for load reduction on large wind turbines", Europ. Wind Energy Conference, Marseille, France, 26(19), 643-678.
  55. Zhang, M., Tan, B. and Xu, J. (2016), "Smart fatigue load control on the large-scale wind turbine blades using different sensing signals", Renew. Energy, 87, 111-119. https://doi.org/10.1016/j.renene.2015.10.011.
  56. Zuo, S., Song, Y., Wang, L. and Song, Q.W. (2013), "Computationally inexpensive approach for pitch control of offshore wind turbine on barge floating platform", Sci. World J., 2013. https://doi.org/10.1155/2013/357849.