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In this paper, the nonlinear dynamic response in a wind turbine system is considered and the quantification of uncertainty effects on the variability of this nonlinear response is investigated. Under dynamic conditions, a lumped model with 12 degrees of freedom is proposed taking into account the uncertainty associated to the power coefficient of the input aerodynamic torque. The dynamic response of the two-stage spur gear system is obtained using ODE45 solver of Matlab. The Polynomial Chaos (PC) method is used to introduce the uncertainties on the proposed model. A comparison between the two dynamic responses given by the proposed lumped dynamic model takes into account the uncertainty. It is performed on the existed model without uncertainty. Thus, the efficiency and robustness of the proposed new methodology is evaluated.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
601--612
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
autor
- Laboratory of Mechanics, Modelling and Mansufacturing (LA2MP), National School of Engineers of Sfax, Sfax, Tunisia
autor
- Laboratory of Mechanics, Modelling and Mansufacturing (LA2MP), National School of Engineers of Sfax, Sfax, Tunisia
autor
- Laboratory of Mechanics, Modelling and Mansufacturing (LA2MP), National School of Engineers of Sfax, Sfax, Tunisia
autor
- Laboratory of Mechanics, Modelling and Mansufacturing (LA2MP), National School of Engineers of Sfax, Sfax, Tunisia
autor
- Laboratory of Mechanics, Modelling and Mansufacturing (LA2MP), National School of Engineers of Sfax, Sfax, Tunisia
autor
- Laboratory of Mechanics, Modelling and Mansufacturing (LA2MP), National School of Engineers of Sfax, Sfax, Tunisia
Bibliografia
- 1. Abboudi K., Walha L., Driss Y., Maatar M., Fakhfakh T., Haddar M., 2011, Dynamic behavior of a two-stage gear train used in a fixed-speed wind turbine, Journal of Mechanism and Machine Theory, 46
- 2. Beltran B., Benbouzid M.E.H., Mohamed-Ali T., 2011, Second-order sliding mode power control and grid fault-tolerance a dfig-based wind turbine, Revue des Sciences et de la Technologie, 2, 75-91
- 3. Buckspan A., 2012, Nonlinear control of a wind turbine, Journal of Undergraduate Research, 13, 2, 1-5
- 4. Chantrasmi T., Constantine P., Etemadiz N., Iaccarino G., Wang Q., 2006, Uncertainty quantification in simple linear and non-linear problems, Annual Research Briefs
- 5. Fisher J., Bhattacharya R., 2008, Stability analysis of stochastic systems using polynomial chaos, American Control Conference, 4250-4255
- 6. Gebreslassie M.G., Tabor G.R., Belmont M.R., 2013, Numerical simulation of a new type of cross flow tidal turbine using OpenFOAM – Part I: Calibration of energy extraction, Renewable Energy, 50, 994-1004
- 7. Ghanem R., Spanos P.D., 1991, Stochastic Finite Elements. A Spectral Approach, SpringerVerlag, New York
- 8. Helsen J., Vanhollebeke F., Marrant B., Vandepitte D., Desmet W., 2011, Multibody modelling of varying complexity for modal behaviour analysis of wind turbine gearboxes, Renewable Energy, 36, 11, 3098-113
- 9. Isukapalli S.S., Roy A., Georgopoulos P.G., 1998a, Development and application of methods for assessing uncertainty in photochemical air quality problems, Interim Report for U.S.EPA National Exposure Research Laboratory
- 10. Isukapalli S.S., Roy A., Georgopoulos P.G., 1998b, Stochastic response surface methods (SRSMs) for uncertainty propagation: application to environmental and biological systems, Risk Analysis, 18, 351-363
- 11. Jakerman J.D., Roberts S.G., 2009, Stochastic Galerkin and collocation methods for quantifying uncertainties in differential equation, a review, ANZIAM Journal, 50, 815-830
- 12. Kalos M.H., Whitlock P.A., 1986, Monte Carlo ethods, Basics, Wiley-Interscience, 1, New York
- 13. Lei Y., Bai Y., Xu Z., Gao Q., Zhao C., 2013, An experimental investigation on aerodynamic performance of a coaxial rotor system with different rotor spacing and wind speed, Experimental Thermal and Fluid Science, 44, 779-785
- 14. Nechak L., Berger S., Aubry E., 2011, A polynomial chaos approach to the robust analysis of the dynamic behavior of friction systems, European Journal of Mechanics A/Solids, 594-607
- 15. Pettersson P., Iaccarino G., Nordstrom J., 2009, Numerical analysis of the Burgersequation in the presence of uncertainty, Journal of Computational Physics, 228, 8394-8412
- 16. Rubinstein R.Y., 1981, Simulation and the Monte Carlo Method, John Wiley & Sons Inc. New York
- 17. Sandu A., Sandu C., Ahmadian M., 2006a, Modeling multibody dynamic systems with uncertainties. Part I: numerical application, Multibody System Dynamic, 15, 369-391
- 18. Sandu C., Sandu A., Ahmadian M., 2006b, Modeling multibody dynamic systems with uncertainties. Part II: theoretical and computational aspects, Multibody System Dynamic, 15, 241-262
- 19. Sloth C., Esbensen T., Stoustrup J., 2011, Robust and fault-tolerant linear parameter-varying control of wind turbines, Mechatronics, 21
- 20. Wei S., Zhao J., Han Q., Chu F., 2015, Dynamic response analysis on torsional vibrations of wind turbine geared transmission system with uncertainty, Renewable Energy, 78, 60-67
- 21. Wiener N., 1938, The homogeneous chaos, American Journal of Mathematics, 60, 4, 897-936
- 22. Xiu D., Karniadakis G., 2002, The Wiener-Askey polynomial chaos for stochastic differential equations, SIAM Journal on Scientific Computing, 24, 2, 619-644
- 23. Zhu C., Xu X., Liu H., Luo T., Zhai H., 2014, Research on dynamical characteristics of wind turbine gearboxes with flexible pins, Renewable Energy, 68, 724-32
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniajacą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0ec1439d-c531-4ab8-b6c2-ca49570f612c
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