Publications

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This report documents the status of the Sandia National Laboratories' Wind Plant Reliability Database. Included in this report are updates on the form and contents of the Database, which stems from a fivestep process of data partnerships, data definition and transfer, data formatting and normalization, analysis, and reporting. Selected observations are also reported.

Various sources of risk exist for all civil structures, one of which is seismic risk. As structures change in scale, the magnitude of seismic risk changes relative to risk from other sources. This paper presents an introduction to seismic hazard as applied to wind turbine structures. The existing design methods and research regarding seismic risk for wind turbines is then summarized. Finally a preliminary assessment is made based on current guidelines to understand how tower moment demand scales as rated power increases. Potential areas of uncertainty in the application of the current guidelines are summarized.

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When a system design approach is applied to wind turbine blades, manufacturing and structural requirements are included along with aerodynamic considerations in the design optimization. The resulting system-driven design includes several innovative structural features such as flat-back airfoils, a constant thickness carbon spar-cap, and a thin, large diameter root. Subscale blades were manufactured to evaluate the as-built integrated performance. The design resulted in a 22% reduction in mass, but withstood over 300% of its design load during testing. Compressive strains of nearly 0.9% were measured in the carbon spar-cap. The test results from this and an earlier design are compared, as are finite element models of each design. Included in the analysis is a review of the acoustic emission events that were detected through the use of surface mounted microphones.

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An estimate of the distribution of fatigue ranges or extreme loads for wind turbines may be obtained by separating the problem into two uncoupled parts, (1) a turbine specific portion, independent of the site and (2) a site-specific description of environmental variables. We consider contextually appropriate probability models to describe the turbine specific response for extreme loads or fatigue. The site-specific portion is described by a joint probability distribution of a vector of environmental variables, which characterize the wind process at the hub-height of the wind turbine. Several approaches are considered for combining the two portions to obtain an estimate of the extreme load, e.g., 50-year loads or fatigue damage. We assess the efficacy of these models to obtain accurate estimates, including various levels of epistemic uncertainty, of the turbine response.

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International standards for wind turbine certification depend on finding long-term fatigue load distributions that are conservative with respect to the state of knowledge for a given system. Statistical models of loads for fatigue application are described and demonstrated using flap and edge blade-bending data from a commercial turbine in complex terrain. Distributions of rainflow-counted range data for each ten-minute segment are characterized by parameters related to their first three statistical moments (mean, coefficient of variation, and skewness). Quadratic Weibull distribution functions based on these three moments are shown to match the measured load distributions if the non-damaging low-amplitude ranges are first eliminated. The moments are mapped to the wind conditions with a two-dimensional regression over ten-minute average wind speed and turbulence intensity. With this mapping, the short-term distribution of ranges is known for any combination of average wind speed and turbulence intensity. The long-term distribution of ranges is determined by integrating over the annual distribution of input conditions. First, we study long-term loads derived by integration over wind speed distribution alone, using standard-specified turbulence levels. Next, we perform this integration over both wind speed and turbulence distribution for the example site. Results are compared between standard-driven and site-driven load estimates. Finally, using statistics based on the regression of the statistical moments over the input conditions, the uncertainty (due to the limited data set) in the long-term load distribution is represented by 95% confidence bounds on predicted loads.

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Over the past several years, extensive databases have been developed for the S-N behavior of various mate&& used in wind turbine blades, primarily fiberglass composites. These data are typically presented both in their "raw" form and curve fit to define their average properties. For design, confidence limits must be placed on these descriptions. In particular, most designs call for the "95195" design values; namely, with a 95 percent level of confidence, thedesiguerisassuredthat95percentofthematerial will 'meet or exceed the design value. For such material properties as the ultimate streng& the procedures for estimating its value at a particular confidence level is wellffiedifthemeasured values follow a normal or a log-normal distribution. Namely, based upon the number of sample points and their standard deviation, a commonly-found table may be used to determine the survival percentagea t a particular confidencel evel with respect to its mean value. The same is true for fatigue data at a constaut stress level (the number of cycles to failure N at stress level SI). However, when the stress level is allowed to vary, as with a typical S-N fatigue curve, the proceduresf or determmingc onfidencel imits are not as well delked. This paper outlines techn.iques for determimng confklence limits of fatigue data Different approachesto estimating the 95195l evel are compared. Data from the MSUIDOE and the FACT fatigue databam are used to illustrate typical results.