No description available.

Thesis (doctoral)--Technical University of Delft, 2006 / Includes bibliographical references (p. 173-191) and index.

One of the biggest environmental concerns of a wind turbine is the wind turbine noise (Prospathopoulos and Voutsinas, 2007). This study assesses the noise impacts of wind turbines on the environment by comparing the micro-wind turbine noise to traditional accepted surrounding sounds. The collection of the sound level data was done by using a randomised experiment. The sound level data was then fitted to a General Linear Model to determine the relationship between the sound levels generated at a given site to the time of day, wind speed, wind direction and distance from the sound source. An additional study was conducted to determine the relationship between wind speed and the sound levels of wind turbines. The distribution of frequency components of wind turbine sound was also determined.

No description available.

CIVINS / The use of wind power is in a period of rapid growth worldwide and wind energy systems have emerged as a promising technology for utilizing offshore wind resources for the large scale generation of electricity Drawing upon the maturity of wind turbine and floater technologies developed by the wind energy and oil and gas industries, respectively, large offshore wind energy systems have been developed and are being proposed for operation in offshore areas where environmental restrictions are less restrictive, large wind resources exist, and open sea areas are available for wind farm development. A fully coupled dynamic analysis/technique was developed to predict the response of a floating wind turbine system in a stochastic wind and wave environment This technique incorporated both non-linear wave loading on the submerged floater and the aerodynamic loading on the wind turbine A tension leg spar buoy was designed to support the wind turbine This design was chosen due to its relatively small size and hence lower potential cost per wind turbine The system's tethers were attached to the ends of spokes which radiated out from the spar cylinder This arrangement of lines and spokes promised to be very stiff in the roll and pitch modes of motion.

No description available.

Recent years have seen the development of wind energy conversion systems that can exploit the superior wind resource that exists at altitudes above current wind turbine technology. One class of these systems incorporates a flying wing tethered to the ground which drives a winch at ground level. The wings often resemble sports kites, being composed of a combination of fabric and stiffening elements. Such wings are subject to load dependent deformation which makes them particularly difficult to model and control. Here we apply the techniques of evolutionary robotics i.e. evolution of neural network controllers using genetic algorithms, to the task of controlling a steerable kite. We introduce a multibody kite simulation that is used in an evolutionary process in which the kite is subject to deformation. We demonstrate how discrete time recurrent neural networks that are evolved to maximise line tension fly the kite in repeated looping trajectories similar to those seen using other methods. We show that these controllers are robust to limited environmental variation but show poor generalisation and occasional failure even after extended evolution. We show that continuous time recurrent neural networks (CTRNNs) can be evolved that are capable of flying appropriate repeated trajectories even when the length of the flying lines are changing. We also show that CTRNNs can be evolved that stabilise kites with a wide range of physical attributes at a given position in the sky, and systematically add noise to the simulated task in order to maximise the transferability of the behaviour to a real world system. We demonstrate how the difficulty of the task must be increased during the evolutionary process to deal with this extreme variability in small increments. We describe the development of a real world testing platform on which the evolved neurocontrollers can be tested.

No description available.

Thesis (M.A.)--York University, 2004. Graduate Programme in Geography. / Typescript. Includes bibliographical references (leaves 170-178). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL:http://gateway.proquest.com/openurl?url%5Fver=Z39.88-2004&res%5Fdat=xri:pqdiss&rft%5Fval%5Ffmt=info:ofi/fmt:kev:mtx:dissertation&rft%5Fdat=xri:pqdiss:MQ99350

Thesis (Ph.D.)--University of Texas at Arlington, 2009.