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access icon free Structural responses suppression for a barge-type floating wind turbine with a platform-based TMD

As the ocean environment is more complex than the land environment, the offshore wind turbines especially the floating types generally suffer significant structural loads. In this study, in order to carry out the accurate simulation and analysis for the dynamic characteristics of a barge-type floating wind turbine, a detailed turbine model including the complete drivetrain is constructed. Additionally, the structural responses of the wind turbine are mitigated by using a single-degree of freedom tuned mass damper (TMD) system installed in the platform. In order to achieve the ideal response mitigation effect, a parametric study on the TMD configuration is carried out. Based on a new co-simulation model combining multi-body model and external control codes, the turbine model coupled with the TMD is then simulated under the combined wind and wave. The results demonstrate the effectiveness of the designed TMD on mitigating the structural responses of the barge-type floating wind turbine.

References

    1. 1)
      • 24. Zuo, H., Kaiming, B., Hong, H..: ‘Using multiple tuned mass dampers to control offshore wind turbine vibrations under multiple hazards’, Eng. Struct., 2017, 141, pp. 303315.
    2. 2)
      • 23. Zhang, Q.Y., Zhou, H.: ‘Dynamic response analysis of wind turbine with tuned mass damper under typhoon conditions’, Adv. Mater. Res., 2014, 945–949, pp. 600606.
    3. 3)
      • 18. Zhao, H., Gao, Z., Wang, Z., et al: ‘Shaking table test on vibration control effect of a monopole offshore wind turbine with a tuned mass damper’, Wind Energy, 2018, 21, (12), pp. 13091328.
    4. 4)
      • 1. Petković, D., Ćojbašić, Ž., Nikolić, V., et al: ‘Adaptive neuro-fuzzy maximal power extraction of wind turbine with continuously variable transmission’, Energy, 2014, 64, pp. 868874.
    5. 5)
      • 25. Peeters, J., Vandepitte, D., Sas, P.: ‘Analysis of internal drive train dynamics in a wind turbine’, Wind Energy J., 2006, 9, pp. 141161.
    6. 6)
      • 9. Sun, C., Jahangiri, V.: ‘Bi-directional vibration control of offshore wind turbines using a 3D pendulum tuned mass damper’, Mech. Syst. Signal Process., 2018, 105, pp. 338360.
    7. 7)
      • 20. Stewart, G., Lackner, M.: ‘Offshore wind turbine load reduction employing optimal passive tuned mass damping systems’, IEEE Trans. Control Syst. Technol., 2013, 21, (4), pp. 10901104.
    8. 8)
      • 11. Tran, T.T., Kim, D.-H.: ‘The coupled dynamic response computation for a semi-submersible platform of floating offshore wind turbine’, J. Wind Eng. Ind. Aerodyn., 2015, 147, pp. 104119.
    9. 9)
      • 37. Moré, J.J.: ‘The Levenberg–Marquardt algorithm: implementation and theory’, Numerical analysis, (Springer, Berlin, Germany, 1978), pp. 105116.
    10. 10)
      • 13. Jonkman, J., Matha, D.: ‘A quantitative comparison of the responses of three floating platform concepts’. European Offshore Wind 2009 Conf. and Exhibition, Stockholm, Sweden, 2009.
    11. 11)
      • 34. Jin, X., Li, L., Ju, W.B.: ‘Multi-body modelling of varying complexity for dynamic analysis of large-scale wind turbines’, Renew. Energy, 2016, 90, pp. 336351.
    12. 12)
      • 2. Petković, D., Ab Hamid, S.H., Ćojbašić, Ž., et al: ‘Adapting project management method and ANFIS strategy for variables selection and analyzing wind turbine wake effect’, Nat. Hazards, 2014, 74, (2), pp. 463475.
    13. 13)
      • 36. Jonkman, J.: ‘Influence of control on the pitch damping of a floating wind turbine’. Proc. 46th AIAA Aerospace Science Meeting Exhibit., Reno, NV, USA, January 2008, pp. 115.
    14. 14)
      • 6. Petković, D., Ćojbašič, Ž., Nikolić, V.: ‘Adaptive neuro-fuzzy approach for wind turbine power coefficient estimation’, Renew. Sust. Energy Rev., 2013, 28, pp. 191195.
    15. 15)
      • 26. Peeters, J.: ‘Simulation of dynamic drive train loads in a wind turbine’. PhD Thesis, Katholieke Universiteit Leuven, Department of Mechanical Engineering, Division PMA, Belgium, 2006.
    16. 16)
      • 29. Hansen, A.D., Michalke, G.: ‘Fault ride-through capability of DFIG wind turbines’, Renew. Energy, 2007, 32, pp. 15941610.
    17. 17)
      • 40. Garrad Hassan & Partners Ltd: ‘International electrotechnical commission standard on wind turbines. Part 3: design requirements for offshore wind turbines’, 2009.
    18. 18)
      • 27. Jonkman, J., Buhl, J.M.: ‘Fast user's guide’. National Renewable Energy Laboratory, Golden, CO, USA, 2005.
    19. 19)
      • 41. Li, Y., Castro, A.M., Martin, J.E., et al: ‘Coupled computational fluid dynamics/multibody dynamics method for wind turbine aero-servo-elastic simulation including drivetrain dynamics’, Renew. Energy, 2017, 101, pp. 10371051.
    20. 20)
      • 4. Petković, D., Pavlović, N.T., Ćojbašić, Ž.: ‘Wind farm efficiency by adaptive neuro-fuzzy strategy’, Int. J. Electr. Power Energy Syst., 2016, 81, pp. 215221.
    21. 21)
      • 14. Mitchell, S.J., Lanquaye-Opoku, N., Modzelewski, H., et al: ‘Comparison of wind speeds obtained using numerical weather prediction models and topographic exposure indices for predicting windthrow in mountainous terrain’, For. Ecol. Manag., 2008, 254, (2), pp. 193204.
    22. 22)
      • 33. Matha, D.: ‘Model development and loads analysis of an offshore wind turbine on a tension leg platform with a comparison to other floating turbine concepts’. Technical Report, NREL/SR-500-45891, National Renewable Energy Laboratory (NREL), Golden, CO, USA, 2010.
    23. 23)
      • 3. Petković, D., Nikolić, V., Mitić, V.V., et al: ‘Estimation of fractal representation of wind speed fluctuation by artificial neural network with different training algorithms’, Flow Meas. Instrum., 2017, 54, pp. 172176.
    24. 24)
      • 38. Ranganathan, A.: ‘The Levenberg–Marquardt algorithmGeorgia Institute of Technology, Atlanta, GA, 2004.
    25. 25)
      • 35. SIMPACK AG., 2016 SIMPACK Documentation, 2016.
    26. 26)
      • 12. Veers, P.: ‘Trends in the design, manufacturing and evaluation of wind turbine blades’, Wind Energy, 2003, 3, pp. 245259.
    27. 27)
      • 31. Helsen, J., Vanhollebeke, F., Marrant, B., et al: ‘Multi-body modelling of varying complexity for modal behaviour analysis of wind turbine gearboxes’, Renew. Energy, 2011, 36, pp. 30983113.
    28. 28)
      • 8. Namik, H., Stol, K.A.: ‘Individual blade pitch control of floating offshore wind turbines’, Wind Energy, 2010, 13, (1), pp. 7485.
    29. 29)
      • 5. Nikolić, V., Mitić, V.V., Kocić, L., et al: ‘Wind speed parameters sensitivity analysis based on fractals and neuro-fuzzy selection technique’, Knowl. Inf. Syst., 2017, 52, (1), pp. 255265.
    30. 30)
      • 7. Van, T.L., Nguyen, T.H., Lee, D.C.: ‘Advanced pitch angle control based on fuzzy logic for variable-speed wind turbine systems’, IEEE Trans. Energy Convers., 2015, 30, (2), pp. 578587.
    31. 31)
      • 39. Hansen, M.H., Hansen, A., Larsen, T.J., et al: ‘Control design for a pitch-regulated variable-speed wind turbine’. Report #Riso-R-1500(EN), Riso National Laboratory, Roskilde, Denmark, 2005.
    32. 32)
      • 21. Si, Y., Karimi, H.R., Gao, H.: ‘Modelling and optimization of a passive structural control design for a spar-type floating wind turbine’, Eng. Struct., 2014, 69, (9), pp. 168182.
    33. 33)
      • 30. Boukhezzar, B., Lupu, L., Siguerdidjane, H., et al: ‘Multivariable control strategy for variable speed, variable pitch wind turbines’, Renew. Energy, 2007, 32, pp. 12731287.
    34. 34)
      • 16. Altunişik, A.C., Yetişken, A., Kahya, V.: ‘Experimental study on control performance of tuned liquid column dampers considering different excitation directions’, Mech. Syst. Signal Process., 2018, 102, pp. 5971.
    35. 35)
      • 32. Jonkman, J., Butterfield, S., Musial, W., et al: ‘Definition of a 5-mw reference wind turbine for offshore system development’. Tech. Rep. TP 500-38060, Nat. Renew. Energy Lab., Golden, CO, USA, 2008.
    36. 36)
      • 22. Lackner, M.A., Rotea, M.A.: ‘Passive structural control of offshore wind turbines’, Wind Energ., 2011, 14, pp. 373388.
    37. 37)
      • 19. Stewart, G.M.: ‘Load reduction of floating wind turbines using tuned mass dampers’. Master thesis, University of Massachusetts, Amherst, 2012.
    38. 38)
      • 15. Michajłow, M., Szolc, T., Jankowski, Ł., et al: ‘Semi-active reduction of vibrations of periodically oscillating system’, Solid State Phenomena, 2016, 248, pp. 111118.
    39. 39)
      • 10. Zhang, X., Sun, L., Sun, H., et al: ‘Floating offshore wind turbine reliability analysis based on system grading and dynamic FTA’, J. Wind Eng. Ind. Aerodyn., 2016, 154, pp. 2133.
    40. 40)
      • 28. Garrad Hassan & Partners Ltd.: ‘Bladed theory manual’, Version 4.2, 2011.
    41. 41)
      • 17. Singh, M.P., Matheu, E.E., Suarez, L.E.: ‘Active and semi-active control of structures under seismic excitation’, Earthquake Eng. Struct. Dynam., 1997, 26, (2), pp. 193213.
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