The effect of varying turbulence levels on long-term loads extrapolation techniques was examined using a joint probability density function of both mean wind speed and turbulence level for loads calculations. The turbulence level has a dramatic effect on the statistics of moment maxima extracted from aeroelastic simulations. Maxima from simulations at lower turbulence levels are more deterministic and become dominated by the stochastic component as turbulence level increases. Short-term probability distributions were calculated using four different moment-based fitting methods. Several hundred of these distributions were used to calculate a long-term probability function. From the long-term probability, 1- and 50-year extreme loads were estimated. As an alternative, using a normal distribution of turbulence level produced a long-term load comparable to that of a log-normal distribution and may be more straightforward to implement. A parametric model of the moments was also used to estimate the extreme loads. The parametric model predicted nearly identical loads to the empirical model and required less data. An input extrapolation technique was also examined. Extrapolating the turbulence level prior to input into the aeroelastic code simplifies the loads extrapolation procedure but, in this case, produces loads lower than the empirical model and may be non-conservative in general.

This paper presents a numerical method for performance predictions of wind turbines immersed into stable, neutral, or unstable atmospheric boundary layer. Tile flowfield around a turbine is described by the Reynolds’ averaged Navier-Stokes equations complemented by the k-ε turbulence model. The density variations are introduced into the momentum equation using the Boussinesq approximation and appropriate buoyancy terms are included into the k and ε equations. An original expression for the closure coefficient related to the buoyancy production term is proposed in order to improve the accuracy of the simulations. The turbine is idealized as actuator disk surface, on which external surficial forces exerted by the turbine blade on the flow are prescribed according to the blade element theory. The resulting mathematical model has been implemented in FLUENT. The results presented in the paper include the power output and wake development under various thermal stratifications of an isolated wind turbine. In stable stratification, the power output is 4% lower than in neutral condition, while in unstable situation, the power is 3% larger. The predicted wake velocity defects are qualitatively in agreement with experimental observations.

The design of a robust frequency converter controller for high dynamic performance of a synchronous generator requires an accurate dynamic model of the electromagnetic part. In this paper a new procedure for identifying the transfer functions of Park’s dq -axis model of a synchronous generator has been developed. It will be shown that the parameters of this model can be easily identified from standstill time-domain data. The validity of the theoretical model has been verified by comparing time-domain simulations with measurements taken from the Lagerwey LW-50/750 direct-drive synchronous generator. It can be concluded that a consistent model estimate of the electromagnetic part of the LW-50/750 generator has been obtained. Ultimate validation, however, will follow after the implementation of the designed frequency converter controller in this wind turbine.

Wind potential — in Italy — has not been completely explored yet, and many investors are still looking into the most promising sites. The interest on the exploitation of a wind site is linked to the possibility of setting up an industrial plan that yields a fast return on investment. The success of this investment depends on the following parameters: • the amount of funding to be spent (cost of the electric lines, roads, turbines, etc.); • the quality of the predicted wind flow; • the price of the electric energy produced. To select a wind site in a fast and convenient way some of the traditional methods of aerodynamics can be borrowed, such as those related to vehicle dynamics. This paper investigates and compares wind site characterization tools and methodologies based on aerodynamics. Simulations and experimental activities were performed in geographical sites located in the center of Italy, where the complex orography requires efficient methods for site characterization and selection, with the aim of speeding up the start-up of wind turbine installations.

Full-scale wind tunnel tests of the NREL Unsteady Aerodynamics Experiment (UAE) Phase VI permitted unprecedented control and measurement of inflow to the UAE rotor. This in turn has allowed in-depth validation of the AeroDyn wind turbine aerodynamics software. This validation began with comparison of simple cases (i.e., fixed yaw, fixed pitch, no teeter), with results presented last year [2]. Among the findings of that study was the significant increase in section lift along the rotor blades due to the 3–dimensional flow over the UAE rotor. This delayed stall was not adequately accounted for in the AeroDyn model. This continued validation effort looks into delayed stall and the static and dynamic behavior of the Generalized Dynamic Wake (GDW) model in AeroDyn. Validation is accomplished through comparison of UAE data and simulation results for the following cases: • Uniform inflow (upwind, zero yaw error), • Step pitch changes on an operating rotor, • A teetering rotor at various yaw angles, and • Downwind rotor released into flee yaw from various initial yaw error positions. Results presented allow us to draw several conclusions. The Du and Selig delayed stall correction adequately models the increase in C L , but the suggested decrease in C D of that model does not agree with observations in the data. The time lag coefficient in the GDW model agrees well with observations in the rapid pitch change UAE data. The phase of teeter response for the GDW model agrees better with data than for the equilibrium wake model. Dynamic stall provides significant additional damping to the teeter motion. The choice of wake model also greatly affects the yaw rate in the yaw release simulations.

Further study of probabilistic methods for predicting extreme wind turbine loading was performed on two large-scale wind turbine models with stall and pitch regulation. Long-term exceedance probability distributions were calculated using maxima extracted from time series simulations of in-plane and out-of-plane blade loads. It was discovered that using a threshold on the selection of maxima increased the accuracy of the fitted distribution in following the trends of the largest extreme values for a given wind condition. The optimal threshold value for in-plane and out-of-plane blade loads was found to be the mean value plus 1.4 times the standard deviation of the original time series for the quantity of interest. When fitting a distribution to a given data set, the higher-order moments were found to have the greatest amount of uncertainty and also the largest influence on the extrapolated long-term load’s. This uncertainty was reduced by using large data sets, smoothing of the moments between wind conditions and parametrically modeling moments of the distribution. A deterministic turbulence model using the 90th percentile level of the conditional turbulence distribution given mean wind speed was used to greatly simplify the calculation of the long-term probability distribution. Predicted extreme loads using this simplified distribution were equal to or more conservative than the loads predicted by the full integration method.

Yaw aerodynamics were computed with three codes of different complexity; 1) The 3D Navier Stokes solver Ellipsys3D using 5–8 million grid points; 2) HAWC3D which is a 3D actuator disc model coupled to a blade element model and using 20–30.000 grid points and 3) HAWC, a finite element based aeroelastic code using The Blade Element Momentum (BEM) model for the aerodynamics. Simulations were performed for two experiments. The first is the field rotor measurements on a 100 kW turbine at Risoe where local flow angle (LFA) and local relative velocity (LRV) at one radial station have been measured in a yaw angle interval of ±60°. The other experiment is the NREL measurements on a 10 m rotor in the NASA Ames 80 ft × 120 ft wind tunnel. LFA were measured at five radial stations and data for the 45° yaw case were analyzed. The measured changes in LFA caused by the yawing were used as the main parameter in the comparison with the models. In general a good correlation was found comparing the Ellipsys3D results with the LFA measured on the NREL rotor whereas a systematic underestimation of the amplitude in LFA as function of azimuth was observed for the two other models. This could possibly be ascribed to upwash influence on the measured LFA.