Recent hurricanes in the Gulf of Mexico (e.g., Ivan, Dennis, Katrina, Rita and Ike) were observed to develop wave conditions that were near or exceeded the predicted 100-year conditions. As a result, many offshore facilities, as well as coastal infrastructure, which were designed to withstand the 100-year condition, were damaged. New estimates of extreme conditions, which incorporate recently observed maxima, are needed to provide better guidelines for design of coastal and offshore structures. Berek et al. (2007) have used modeled data to develop new criteria, but these estimates can be very sensitive to the data and to the statistical methods used in the development. Berek's estimates also do not cover the entire Gulf of Mexico. We have developed updated estimates of the 100-year extreme wave conditions for the entire Gulf of Mexico using a more comprehensive approach. First, the applicability of standard parametric wind models was examined and appropriate adjustments to the Rankine vortex model were developed to reduce the wind field errors during hurricane conditions. The adjusted winds reduced the error by up to 25 percent compared to the original Rankine vortex model. To obtain reliable wave data, merged wind fields were generated using the NCEP/NCAR Reanalysis 1 project modeled wind data for background wind and the parametric wind model for hurricane conditions. Next, the SWAN wave model was used for the 51-year period from 1958 to 2008 along with multiple statistical methods (Gumbel, Weibull and GEV-Generalized Extreme Value distribution). The effect of the recent hurricane season (2004-2008) shows that maximum 100-year wave height values and their distribution changes. A resampling technique (bootstrap) is used to evaluate and select the optimum statistical method to estimate more appropriate extreme wave conditions.

As wind turbines have grown, new installation areas become possible. Placing wind turbines in forested landscapes introduce uncertainties to the wind resource estimation. Even though close-to-canopy processes have been studied intensively during the last thirty years, the focus has mostly been on exchange processes and the height span of the studies has been below the rotor of a modern wind turbine. This thesis contains analysis of new measurements from a 138 m high tower in a forested landscape. The previous knowledge of near-canopy processes is extended to the region above the roughness sublayer. It is shown that above the roughness sublayer, the surface layer behaves as over low vegetation, and Monin-Obukhov similarity is shown to hold for several variables. However, in stable stratification, effects that could be linked to the boundary layer depth are shown to be present in the measurements. These include wind turning with height, the behaviour of the turbulence length scale and the curvature of the wind profile. Two new analytical models are presented in the thesis. One is a flux-profile expression in the roughness sublayer, which allows for analytical integration of the wind gradient. The model suggests that the roughness-sublayer effect depends on stratification and that the aerodynamic roughness length changes with stability. A decrease of roughness length in stable stratification is confirmed with a new method to determine the roughness length using measurements from the 138 m tower. The other model determines the spectral tensor in stable stratification using analytical solution to the rapid distortion equations for stratified shear flow, with homogeneous stratification and shear. By using a formulation for the integration time of the distortions of an isotropic spectrum, a model is derived which provides the cross spectra of velocity and temperature at any two given points in space. Finally the existence of waves in the wind over forests is investigated and it is concluded that the Kelvin-Helmholtz instability can create waves which are coherent in time and exist over the entire height span of wind turbine rotors. Linear wave theory is shown to be able to explain certain features of the waves. / Vindforsk III, Wind power in forests / Vindforsk IV, Forest wind

This master‘s thesis deals with the simulation of small wind power plant with Savonius-Darrieus rotor. On the base of the actuator disk theory the performance of modeled power plant is predicted in theoretical part and the power coefficient as well. The process of designing the wind model is also described in this theoretical part. The practical part of this thesis is dedicated to the creating a model of DS300 vertical axis hybrid wind turbine in Matlab/Simulink. This model was used to generating of the power curve of modeled wind power plant and for the computing of power and total produced energy during an average and above-average day as well. The whole thesis is enclosed by evaluating of obtained results.

In the spring of 1999 NASA will launch the scatterometer SeaWinds, beginning a 3 year mission to measure the ocean winds. SeaWinds is different from previous spaceborne scatterometers in that it employs a rotating pencil-beam antenna as opposed to fixed fan-beam antennas. The scanning beam provides greater coverage but causes the wind retrieval accuracy to vary across the swath. This thesis develops a filed-wise wind retrieval algorithm to improve the overall wind retrieval accuracy for use with SeaWinds data. In order to test the field-wise wind retrieval algorithm, methods for simulating wind fields are developed. A realistic approach interpolates the NASA Scatterometer (NSCAT) estimates to fill a SeaWinds swath using optimal interpolation along with linear wind filed models. The two stages of the field-wise wind retrieval algorithm are filed-wise estimation and field-wise ambiguity selection. Field-wise estimation is implemented using a 22 parameter Karhunen-Loeve (KL) wind field model in conjunction with a maximum likelihood objective function. An augmented multi-start global optimization is developed which uses information from the point-wise estimates to aid in a global search of the objective function. The local minima in the objective function are located using the augmented multi-start search techniques and are stored as field-wise ambiguities. The ambiguity selection algorithm uses a field-wise median filter to select the field-wise ambiguity closest to the true wind in each region. Point-wise nudging is used to further improve the filed-wise estimate using information from the point-wise estimates. Combined, these two techniques select a good estimate of the wind 95% of the time. The overall performance of the field-wise wind retrieval algorithm is compared with the performance of the current point-wise techniques. Field-wise estimation techniques are shown to be potentially better than point-wise techniques. The field-wise estimates are also shown to be very useful tools in point-wise ambiguity selection since 95.8%-96.6% of the point-wise estimates closest to the field-wise estimates are the correct aliases.