Application of Soft Computing in the Design and Optimization of Tuned Liquid Column–Gas Damper for Use in Offshore Wind Turbines

Author

Assistant Professor, Faculty of Civil Engineering, Babol Noshirvani University of Technology, Iran

Abstract

Tuned liquid column gas damper is a new type of energy absorber that can mitigate the vibrations of structures if their frequency and mass parameters are well tuned. Since this damper has recently been introduced and its behaviour in certain structures such as offshore oil platforms and wind turbines has already been tested, a suitable and accurate method is required to identify these optimal parameters. Therefore, considering the complexity of loads exerted on wind turbines in seas (wave and wind loads), in present study attempts are made to use a new artificial neural network approach to obtain optimal tuned liquid column–gas damper (TLCGD) parameters for mitigation of wind turbine vibrations. First fixed offshore wind turbines at various depths are designed in the MATLAB coding environment. After obtaining the stiffness, damping and mass matrices of the structures, the program enters the Simulink, and the wind turbine structure along with the TLCGD is exposed to different wave-wind load combinations within reasonable range of damper parameters. The neural network training is launched based on available statistical data of the offshore wind turbine with different heights as well as different frequency and mass ratios of the damper. According to this method, the percentage of errors found in the neural network outputs was negligible compared to the actual results obtained from the analysis in Simulink (even for inputs that stood outside the training range of the neural network). The mean error percentage, the standard deviation and the effective value of the neural network with actual values are below 10% for all three types of the structure. Finally, the method presented in this study can be used to obtain optimal parameters of the TLCGD for all kinds of offshore wind turbines at different depths of the sea, which leads to the optimal design of this damper to reduce the vibrations of wind turbines under wave and wind load pressures.

Keywords

References

  1. Zhang, P., & Huang, S. (2011). Review of aeroelasticity for wind turbine: current status, research focus and future perspectives. Frontiers in Energy, 5(4), 419-434.
  2. Zhang, P., & Huang, S. (2011). Review of aeroelasticity for wind turbine: current status, research focus and future perspectives. Frontiers in Energy, 5(4), 419-434.
  3. Ogunjuyigbe, A. S. O., Ayodele, T. R., & Bamgboje, O. D. (2017). Optimal placement of wind turbines within a wind farm considering multi-directional wind speed using two-stage genetic algorithm. Frontiers in Energy, 1-16. [DOI:10.1007/s11708-018-0514-x]
  4. Ogunjuyigbe, A. S. O., Ayodele, T. R., & Bamgboje, O. D. (2017). Optimal placement of wind turbines within a wind farm considering multi-directional wind speed using two-stage genetic algorithm. Frontiers in Energy, 1-16. [DOI:10.1007/s11708-018-0514-x]
  5. IEC, I. (2009). 61400-3, Wind Turbines-Part 3: Design Requirements for Offshore Wind Turbines. International Electrotechnical Commission, Geneva.
  6. IEC, I. (2009). 61400-3, Wind Turbines-Part 3: Design Requirements for Offshore Wind Turbines. International Electrotechnical Commission, Geneva.
  7. Iemura, H., & Pradono, M. H. (2002). Passive and semi‐active seismic response control of a cable‐stayed bridge. Journal of Structural Control, 9(3), 189-204. [DOI:10.1002/stc.12]
  8. Iemura, H., & Pradono, M. H. (2002). Passive and semi‐active seismic response control of a cable‐stayed bridge. Journal of Structural Control, 9(3), 189-204. [DOI:10.1002/stc.12]
  9. Dezvareh, R. (2019). Upgrading the Seismic Capacity of Pile-Supported Wharfs Using Semi-Active Liquid Column Gas Damper. Journal of Applied and Computational Mechanics.
  10. Dezvareh, R. (2019). Upgrading the Seismic Capacity of Pile-Supported Wharfs Using Semi-Active Liquid Column Gas Damper. Journal of Applied and Computational Mechanics.
  11. Lackner, M. A., & Rotea, M. A. (2011). Passive structural control of offshore wind turbines. Wind energy, 14(3), 373-388. [DOI:10.1002/we.426]
  12. Lackner, M. A., & Rotea, M. A. (2011). Passive structural control of offshore wind turbines. Wind energy, 14(3), 373-388. [DOI:10.1002/we.426]
  13. Lackner, M. A., & Rotea, M. A. (2011). Structural control of floating wind turbines. Mechatronics, 21(4), 704-719. [DOI:10.1016/j.mechatronics.2010.11.007]
  14. Lackner, M. A., & Rotea, M. A. (2011). Structural control of floating wind turbines. Mechatronics, 21(4), 704-719. [DOI:10.1016/j.mechatronics.2010.11.007]
  15. Stewart, G. M., & Lackner, M. A. (2011). The effect of actuator dynamics on active structural control of offshore wind turbines. Engineering Structures, 33(5), 1807-1816. [DOI:10.1016/j.engstruct.2011.02.020]
  16. Stewart, G. M., & Lackner, M. A. (2011). The effect of actuator dynamics on active structural control of offshore wind turbines. Engineering Structures, 33(5), 1807-1816. [DOI:10.1016/j.engstruct.2011.02.020]
  17. Dezvareh, R., Bargi, K., & Mousavi, S. A. (2016). Control of wind/wave-induced vibrations of jacket-type offshore wind turbines through tuned liquid column gas dampers. Structure and Infrastructure Engineering, 12(3), 312-326. [DOI:10.1080/15732479.2015.1011169]
  18. Dezvareh, R., Bargi, K., & Mousavi, S. A. (2016). Control of wind/wave-induced vibrations of jacket-type offshore wind turbines through tuned liquid column gas dampers. Structure and Infrastructure Engineering, 12(3), 312-326. [DOI:10.1080/15732479.2015.1011169]
  19. Bargi, K., Dezvareh, R., & Mousavi, S. A. (2016). Contribution of tuned liquid column gas dampers to the performance of offshore wind turbines under wind, wave, and seismic excitations. Earthquake Engineering and Engineering Vibration, 15(3), 551-561. [DOI:10.1007/s11803-016-0343-z]
  20. Bargi, K., Dezvareh, R., & Mousavi, S. A. (2016). Contribution of tuned liquid column gas dampers to the performance of offshore wind turbines under wind, wave, and seismic excitations. Earthquake Engineering and Engineering Vibration, 15(3), 551-561. [DOI:10.1007/s11803-016-0343-z]
  21. Chopra, A. K., & Chopra, A. K. (1995). Dynamics of structures: theory and applications to earthquake engineering (Vol. 2). Englewood Cliffs, NJ: Prentice Hall.
  22. Chopra, A. K., & Chopra, A. K. (1995). Dynamics of structures: theory and applications to earthquake engineering (Vol. 2). Englewood Cliffs, NJ: Prentice Hall.
  23. Jonkman, J. M., & Buhl Jr, M. L. (2005). FAST user's guide. National Renewable Energy Laboratory, Golden, CO, Technical Report No. NREL/EL-500-38230.
  24. Jonkman, J. M., & Buhl Jr, M. L. (2005). FAST user's guide. National Renewable Energy Laboratory, Golden, CO, Technical Report No. NREL/EL-500-38230.
  25. Laya, E. J., Connor, J. J., & Sunder, S. S. (1984). Hydrodynamic forces on flexible offshore structures. Journal of engineering mechanics, 110(3), 433-448. [DOI:10.1061/(ASCE)0733-9399(1984)110:3(433)]
  26. Laya, E. J., Connor, J. J., & Sunder, S. S. (1984). Hydrodynamic forces on flexible offshore structures. Journal of engineering mechanics, 110(3), 433-448. [DOI:10.1061/(ASCE)0733-9399(1984)110:3(433)]
  27. Dezvareh, R. (2019). Evaluation of turbulence on the dynamics of monopile offshore wind turbine under the wave and wind excitations. Journal of Applied and Computational Mechanics.
  28. Dezvareh, R. (2019). Evaluation of turbulence on the dynamics of monopile offshore wind turbine under the wave and wind excitations. Journal of Applied and Computational Mechanics.
  29. MATLAB, (2008). User Guide, Simulink, MathWorks Inc., Version 7.6.0.
  30. MATLAB, (2008). User Guide, Simulink, MathWorks Inc., Version 7.6.0.
  31. Haykin, S. (1994). Neural networks (Vol. 2). New York: Prentice hall.
  32. Haykin, S. (1994). Neural networks (Vol. 2). New York: Prentice hall.
  33. Flood, I., & Kartam, N. (1994). Neural networks in civil engineering. I: Principles and understanding. Journal of computing in civil engineering, 8(2), 131-148. [DOI:10.1061/(ASCE)0887-3801(1994)8:2(131)]
  34. Flood, I., & Kartam, N. (1994). Neural networks in civil engineering. I: Principles and understanding. Journal of computing in civil engineering, 8(2), 131-148. [DOI:10.1061/(ASCE)0887-3801(1994)8:2(131)]
  35. Leung, A. Y., Zhang, H., Cheng, C. C., & Lee, Y. Y. (2008). Particle swarm optimization of TMD by non‐stationary base excitation during earthquake. Earthquake Engineering & Structural Dynamics, 37(9), 1223-1246. [DOI:10.1002/eqe.811]
  36. Leung, A. Y., Zhang, H., Cheng, C. C., & Lee, Y. Y. (2008). Particle swarm optimization of TMD by non‐stationary base excitation during earthquake. Earthquake Engineering & Structural Dynamics, 37(9), 1223-1246. [DOI:10.1002/eqe.811]
  37. Leung, A. Y. T., & Zhang, H. (2009). Particle swarm optimization of tuned mass dampers. Engineering Structures, 31(3), 715-728. [DOI:10.1016/j.engstruct.2008.11.017]
  38. Leung, A. Y. T., & Zhang, H. (2009). Particle swarm optimization of tuned mass dampers. Engineering Structures, 31(3), 715-728. [DOI:10.1016/j.engstruct.2008.11.017]
  39. Bekdaş, G., & Nigdeli, S. M. (2011). Estimating optimum parameters of tuned mass dampers using harmony search. Engineering Structures, 33(9), 2716-2723. [DOI:10.1016/j.engstruct.2011.05.024]
  40. Bekdaş, G., & Nigdeli, S. M. (2011). Estimating optimum parameters of tuned mass dampers using harmony search. Engineering Structures, 33(9), 2716-2723. [DOI:10.1016/j.engstruct.2011.05.024]
  41. Dezvareh, R. (2019). Providing a new approach for estimation of wave set-up in Iran coasts. RESEARCH IN MARINE SCIENCES, 4(1), 438-448.
  42. Dezvareh, R. (2019). Providing a new approach for estimation of wave set-up in Iran coasts. RESEARCH IN MARINE SCIENCES, 4(1), 438-448.
  43. Dezvareh, R., Bargi, K., & Moradi, Y. (2012). Assessment of Wave Diffraction behind the Breakwater Using Mild Slope and Boussinesq Theories. International Journal of Computer Applications in Engineering Sciences, 2(2).
  44. Dezvareh, R., Bargi, K., & Moradi, Y. (2012). Assessment of Wave Diffraction behind the Breakwater Using Mild Slope and Boussinesq Theories. International Journal of Computer Applications in Engineering Sciences, 2(2).
International Journal Of Coastal, Offshore And Environmental Engineering
Volume 4, Issue 4 - Serial Number 16
November 2019
Pages 47-57

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