4.7 Article

Reliability-based design optimization of wind turbine blades for fatigue life under dynamic wind load uncertainty

Journal

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
Volume 54, Issue 4, Pages 953-970

Publisher

SPRINGER
DOI: 10.1007/s00158-016-1462-x

Keywords

Wind turbine blades; RBDO; Wind load uncertainty; Reliability analysis; Fatigue life

Funding

  1. Iowa Alliance Wind Innovation and Novel Development (IAWIND) [09-IPF-15]
  2. National Science Foundation Experimental Program to Stimulate Competitive Research (EPSCoR) [EPS-1101284]

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This paper studies reliability-based design optimization (RBDO) of a 5-MW wind turbine blade for designing reliable as well as economical wind turbine blades. A novel dynamic wind load uncertainty model has been developed using 249 groups of wind data to consider wind load variation over a large spatiotemporal range. The probability of fatigue failure during a 20-year service life is estimated using the uncertainty model in the RBDO process and is reduced to meet a desired target reliability. Meanwhile, the cost of composite materials used in the blade is minimized by optimizing the composite laminate thicknesses of the blade. In order to obtain the RBDO optimum design efficiently, deterministic design optimization (DDO) of the 5-MW wind turbine blade is carried out first using the mean wind load obtained from the wind load uncertainty model. The RBDO is then initiated from the DDO optimum. During the RBDO iterations, fatigue hotspots for RBDO are identified among the laminate section points. For an efficient RBDO process, surrogate models of 10-min fatigue damages D (10) at the hotspots are accurately created using the Kriging method. Using the wind load uncertainty model and surrogate models, probability of fatigue failure during a 20-year lifespan at the hotspots and the design sensitivities are calculated at given design points. Using the probability of fatigue failure and design sensitivity, RBDO of the 5-MW wind turbine blade has been successfully carried out, satisfying the target probability of failure of 2.275 %.

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