There has been an increased interest in renewable energy systems in recent years as a result of concerns on depleting fossil fuel reserves and climate change. Wind and solar energy are amongst the most popular renewable energy technologies. In order to use the full or maximum possible extent of a renewable energy resource in a region, hybrid systems extracting wind and solar energy simultaneously are a popular and obvious choice. It is desired to design hybrid systems that enhance the renewable energy output without increasing the foot print area compared to the base case of only wind or only solar energy. One potential way forward is to consider a vertical axis wind turbine with an enhanced surface area which can be used for mounting solar cells. This way the foot print area remains the same while both wind and solar power are obtained simultaneously. Renewable Energy Solutions LLC has manufactured a novel 2 m high and 2 m in diameter vertical axis wind turbine called Marilyn which has an enhanced surface area, which can be used for the aforementioned purpose. This thesis focuses on the development of a hybrid solar-wind turbine design based on the Marilyn system. Firstly, the wind and solar resource was assessed at Austin, TX using weather monitoring instruments. Typical Meteorological Year 3 (TMY3) data was also used in conjunction with the measured data to estimate the wind and solar resource at Austin, TX. Secondly, the wind turbine performance was assessed based on whether is it able to achieve grid tie in for wind power production starting at wind speeds of 3-4 m/s. It was found that replacing the current generator with different model featuring higher voltage output at lower rotational speeds could help achieve this. Based on this suggested replacement and using the wind resource data, the yearly wind energy production was estimated to be 240 kWh. Finally, a theoretical analysis was performed for estimating the yearly solar energy production. A base case analysis was first made on power production on a particular day of the year if only the top portion of every alternate face of the turbine is covered with flexible 3.4 % efficient solar cells. This analysis is subsequently extended to the case when flexible 20 % efficient solar cells cover the entire top surface of the turbine and the corresponding conservative yearly solar energy output was estimated to be 310 kWh. Thus the total yearly energy output from the Marilyn hybrid system is 550 kWh, which is around 5 % of the annual electricity usage of a typical American home / text

Appréhender la question de l'insertion paysagère des éoliennes suppose la détermination préalable des objets juridiques étudiés. Sous les hospices de la notion de « patrimoine commun de la nation », éoliennes et paysages apparaissent ainsi comme des sœurs ennemies. Cette conflictualité est consommée lorsque l'article L. 110-1 du Code de l'environnement dispose que la protection des paysages est d'intérêt général autant que l'est la mise en valeur des ressources naturelles. L'antagonisme postulé des deux notions doit cependant être nuancé en ce que le juge administratif tient le rôle d'arbitre dans les conflits nés de ce que les préoccupations paysagères viennent limiter l'implantation des constructions éoliennes. Alors que ce rapport de force s'apprête à gagner le contentieux spécial des installations classées, le contentieux des permis de construire éolien a été le terrain fertile et propice de l'émergence d'une démarche objective orientant l'appréciation qualitative et donc a priori subjective de l'atteinte aux paysages. Le contentieux des permis de construire éolien a également rendu possible le dépassement du contrôle de l'atteinte aux paysages que la doctrine présente classiquement comme un contrôle dissymétrique, par la formalisation d'un contrôle du bilan paysager des constructions éoliennes pouvant symboliser l'armistice de cet affrontement infécond. / In order to understand the legal bond between wind turbines and landscapes, preliminary elements must be understood. Regarding the legal concept of a « common national heritage », wind turbines and landscapes appear to be two enemy sisters. The conflict emerges when the Environmental Code presents both landscape protection and natural resource development within general interest. The two antagonising notions have to be refined, as the administrative judge appears to be an adjudicator between landscape protection and wind turbine implementation. Whilst the wind turbine landscape sensitivity question is about to integrate the litigation for Classified Installations for the Protection of the Environment, building permits litigation provides the basis for defining an objective method for the subjective definition of damage to the landscape. Using a litigation concerning building permits, a new method of landscape damage assessment has been drafted. Thus, a fine line balancing landscaping can be considered as the end of the war but not necessarily a victory in this meaningless standoff.

Master of Science / Department of Mechanical and Nuclear Engineering / Warren N. White / As traditional resources are becoming scarce, renewable energy is a recent topic receiving greater concern. Among the renewable energies, wind power is a very popular type of energy extracted from wind which is readily available in the environment. The use of wind power all over the world is receiving increased attention. Horizontal axis wind turbines are the most popular equipment for extracting power form the wind. One of the problems of using wind turbines is how to maximize the wind power capture. In this paper, a method for maximizing the rotor power coefficient of a wind turbine is proposed. Simultaneous Perturbation Stochastic Approximation (SPSA) is an efficient way for extremum seeking. It is different from the classical gradient based extremum seeking algorithms. For maximizing the rotor power coefficient, it only needs two objective function measurements to take a step toward the next extremum approximation. The one measurement SPSA is a modification of SPSA method developed in this work. Instead of using measurements of two positions occurring at random directions away from the current position, it uses the measurement of one position in a random direction and the measurement of the current position to estimate the gradient. Usually, the rotor power coefficient is not easily measurable. For speed regulation, a nonlinear robust speed controller is used in this work. The controller produces an estimate of the aerodynamic torque of wind turbine. The quality of this estimate improves with time. From that, a good estimate of power coefficient can be obtained. Simulations in MATLAB are executed with a model of a wind turbine based on its dynamic equations. From simulations, it can be seen that the one measurement SPSA method works very well for the wind turbine. It changes the tip speed ratio and blade pitch simultaneously, and the power coefficient reaches its maximum value quickly in a reliable manner. The power capture optimization is then implemented in FAST, a turbine simulation model created by NREL which is used to test the 5MW NREL reference turbine. From the results, it is evident that the wind turbine reaches the maximum power coefficient rapidly.

This thesis addresses the development of industries manufacturing in the renewable energy sector. As the most mature of the renewable energy technologies, it specifically assesses the development of the wind turbine manufacturing industry up to the present in order to address what lessons may be learned for the future development of the industry and for other renewable energy industries. Data is presented in the form of a number of case studies which detail the comparative successes of Denmark, Germany, Spain and the UK in encouraging the growth of wind turbine industries. Three areas of study are identified, and the data collected in the case studies applied to each. Firstly, the question of whether it is still possible for countries to stimulate national industries to successfully gain entry to the wind turbine manufacturing industry. Applying the historical data in the context of a typological theory on entrepreneurial success with regard to industrial phase, it is argued that such entry is still possible. The remaining two areas of study are linked in that they both address what lessons might be learned from the international development of the wind turbine manufacturing industry in order for the UK to replicate the success of other nations. The first of these areas specifically addresses how lessons from elsewhere might enable UK access to the wind turbine manufacturing industry. The second area addresses the extent to which experiences in the wind turbine industry might provide lessons for entrants to the industries of newer, less mature renewable energy technologies.

This Thesis aims to assess the reliability of turbulence models in predicting the flow fields around the horizontal axis wind turbine (HAWT) rotor blades and also to improve our understanding of the aerodynamics of the flow field around the blades. The simulations are validated against data from the NREL/NASA Phase VI wind turbine experiments. The simulations encompass the use of fourteen turbulence models including low-and high-Reynolds-number, linear and non-linear eddy-viscosity models and Reynolds stress models. The numerical procedure is based on the finite-volume discretization of the 3D unsteady Reynolds-Averaged Navier-Stokes equations in an inertial reference frame with the sliding mesh technique to follow the motion of the rotor blades. Comparisons of power coefficient, normalised thrust, local surface pressure coefficients (CP) and the radial variation of the section average of normal force coefficients with published experimental data over a range of tip-speed ratios, lead to the identification of the turbulence models that can reliably reproduce the values of the key performance indicators. The main contributions of this study are in establishing which RANS models can produce quantitatively reliable simulations of wind turbine flows and in presenting the flow evolution over a range of operating conditions. At low (relative to the blade tip speed) wind speeds the flow over the blade surfaces remains attached and all RANS models return the correct values of key performance coefficients. At higher wind speeds there is circumferential flow separation over the downwind surface of the blade, which eventually spreads over the entire surface, Moreover, within the separation bubble the centrifugal force pumps the flow outwards, which at the higher wind speeds suppresses the formation of the classical tip vortices. More refined RANS models which do not rely on the linear effective viscosity approximation generally lead to more reliable predictions over this range of higher wind speeds. In particular the Gibson-Launder version of the Reynolds stress transport model and the high-Re versions of the Lien et al non-linear k-ε produce consistently reliable simulations over the entire range of wind speeds. By contrast some popular linear effective viscosity models, like the SST (k-ω) and the v^2-f, perform the poorest over this complex flow range. Finally all RANS models are also able to predict the dominant (lowest) frequency of the pressure fluctuations and the non-linear effective viscosity models, the Launder and Shima version of RSM and the SST are also able to return some of the higher frequencies measured.

With wind energy becoming a major source of energy, there is a pressing need to reduce all associated costs to be competitive in a market that might be fully subsidy-free in the near future. Before thousands of wind turbines were installed all over the world, research in e.g. understanding aerodynamics, developing new materials, designing better gearboxes, improving power electronics etc., helped to cut down wind turbine manufacturing costs. It might be assumed, that this would be sufficient to reduce the costs of wind energy as the resource, the wind itself, is free of costs. However, it has become clear that the operation and maintenance of wind turbines contributes significantly to the overall cost of energy. Harsh environmental conditions and the frequently remote locations of the turbines makes maintenance of wind turbines challenging. Just recently, the industry realised that a move from reactive and scheduled maintenance towards preventative or condition-based maintenance will be crucial to further reduce costs. Knowing the condition of the wind turbine is key for any optimisation of operation and maintenance. There are various possibilities to install advanced sensors and monitoring systems developed in recent years. However, these will inevitably incur new costs that need to be worthwhile and retro-fits to existing turbines might not always be feasible. In contrast, this work focuses on ways to use operational data as recorded by the turbine's Supervisory Control And Data Acquisition (SCADA) system, which is installed in all modern wind turbines for operating purposes -- without additional costs. SCADA data usually contain information about the environmental conditions (e.g. wind speed, ambient temperature), the operation of the turbine (power production, rotational speed, pitch angle) and potentially the system's health status (temperatures, vibration). These measurements are commonly recorded in ten-minutely averages and might be seen as indirect and top-level information about the turbine's condition. Firstly, this thesis discusses the use of operational data to monitor the power performance to assess the overall efficiency of wind turbines and to analyse and optimise maintenance. In a sensitivity study, the financial consequences of imperfect maintenance are evaluated based on case study data and compared with environmental effects such as blade icing. It is shown how decision-making of wind farm operators could be supported with detailed `what-if' scenario analyses. Secondly, model-based monitoring of SCADA temperatures is investigated. This approach tries to identify hidden changes in the load-dependent fluctuations of drivetrain temperatures that can potentially reveal increased degradation and possible imminent failure. A detailed comparison of machine learning regression techniques and model configurations is conducted based on data from four wind farms with varying properties. The results indicate that the detailed setup of the model is very important while the selection of the modelling technique might be less relevant than expected. Ways to establish reliable failure detection are discussed and a condition index is developed based on an ensemble of different models and anomaly measures. However, the findings also highlight that better documentation of maintenance is required to further improve data-driven condition monitoring approaches. In the next part, the capabilities of operational data are explored in a study with data from both the SCADA system and a Condition Monitoring System (CMS) based on drivetrain vibrations. Analyses of signal similarity and data clusters reveal signal relationships and potential for synergistic effects of the different data sources. An application of machine learning techniques demonstrates that the alarms of the commercial CMS can be predicted in certain cases with SCADA data alone. Finally, the benefits of having wind turbines in farms are investigated in the context of condition monitoring. Several approaches are developed to improve failure detection based on operational statistics, CMS vibrations or SCADA temperatures. It is demonstrated that utilising comparisons with neighbouring turbines might be beneficial to get earlier and more reliable warnings of imminent failures. This work has been part of the Advanced Wind Energy Systems Operation and Maintenance Expertise (AWESOME) project, a European consortium with companies, universities and research centres in the wind energy sector from Spain, Italy, Germany, Denmark, Norway and UK. Parts of this work were developed in collaboration with other fellows in the project (as marked and explained in footnotes).

Wind turbines are an environmentally friendly and sustainable power source. Unfortunately, the noise impact can cause deteriorated living conditions for nearby residents. The audibility of wind turbine sound is influenced by ambient sound. This thesis deals with some aspects of noise from wind turbines. Ambient sounds influence the audibility of wind turbine noise. Models for assessing two commonly occurring natural ambient sounds namely vegetation sound and sound from breaking waves are presented in paper A and B. A sound propagation algorithm has been compared to long range measurementsof sound propagation in paper C. Psycho-acoustic tests evaluating the threshold and partial loudness of wind turbine noise when mixed with natural ambient sounds have been performed. These are accounted for in paper D. The main scientific contributions are the following.Paper A: A semi-empiric prediction model for vegetation sound is proposed. This model uses up-to-date simulations of wind profiles and turbulent wind fields to estimate sound from vegetation. The fluctuations due to turbulence are satisfactory estimated by the model. Predictions of vegetation sound also show good agreement to measured spectra. Paper B: A set of measurements of air-borne sound from breaking waves are reported. From these measurements a prediction method of sound from breaking waves is proposed. Third octave spectra from breaking waves are shown to depend on breaker type. Satisfactory agreement between predictions and measurements has been achieved. Paper C: Long range sound propagation over a sea surface was investigated. Measurements of sound transmission were coordinated with local meteorological measurements. A sound propagation algorithm has been compared to the measured sound transmission. Satisfactory agreement between measurements and predictions were achieved when turbulence were taken into consideration in the computations. Paper D: The paper investigates the interaction between wind turbine noise and natural ambient noise. Two loudness models overestimate the masking from two psychoacoustic tests. The wind turbine noise is completely concealed when the ambient sound level (A-weighed) is around 10 dB higher than the wind turbine noise level. Wind turbine noise and ambient noise were presented simultaneously at the same A-weighed sound level. The subjects then perceived the loudness of the wind turbine noise as 5 dB lower than if heard alone. Keywords: Wind turbine noise, masking, ambient noise, long range sound propagation / QC 20100705

Currently, wind energy presents an excellent opportunity to satisfy the growing demand without the supply and environmental problems associated with conventional energy. The engineering in wind turbines is not fully mature. There are still phenomenon, particularly dynamic stall, that cannot accurately be modeled or controlled. Dynamic stall contributes to fatigue stress and premature failure in many turbine components. The three dimensionality of dynamic stall makes these structures unique for wind turbines. Currently, flow visualization of dynamic stall on a wind turbine rotor has not been achieved. These visualizations can reveal a lot about the structures that contribute to dynamic stall. Particle Image Velocimetry (PIV) is a powerful experimental technique that can take multiple non-intrusive flow measurements simultaneously of planar flow. Using high-speed cameras time resolved PIV can reveal the transient development of a given flow field. This technique is ideally suited to gain a better understanding of dynamic stall. A custom wind turbine is being built at the University of Waterloo to allow such measurements on the blade. A high speed camera is mounted on the hub and will take measurements within the rotating domain. Mirrors are used so that laser illumination rotates with the blade. The wind turbine will operate in controlled conditions provided by a large wind tunnel. High speed pressure data acquisition will be used in conjunction with PIV to get an understanding of the forces associated with the flow structures. Computational fluid dynamics was used to size the rotor within the wind tunnel. Laser based measurements required special considerations for stiffness. Many revealing experiments will be made possible by this apparatus. First, the flow structures responsible for the various forces can be identified. Quantitative measurements of the flow field will identify the development of the stall vortex. The quantified flow structures can be used verify and improve models. The high spatial resolution of PIV can map the three dimensional flow structure in great detail. The experimental apparatus is independent of the blade geometry, as such multiple blades can be used to identify the effect of blade geometry. Finally flow control research in the field of aviation can be applied to control dynamic stall.

In this thesis it has been investigated if LQG control could be used to mitigate torsional oscillations in a variable speed, fixed pitch wind turbine. The wind turbine is a vertical axis wind turbine with a 40 m tall axis that is connected to a generator. The power extracted by the turbine is delivered to the grid via a passive rectifier and an inverter. By controlling the grid side inverter the current is controlled and hence the rotational speed can be controlled. A state space model was developed for the LQG controller. The model includes both the dynamics of the electrical system as swell as the two mass system, consisting of the turbine and the generator connected with a flexible shaft. The controller was designed to minimize a quadratic criterion that punishes both torsional oscillations, command following and input signal magnitude. Integral action was added to the controller to handle the nonlinear aerodynamic torque. The controller was compared to the existing control system that uses a PI controller to control the speed, and tested usingMATLAB Simulink. Simulations show that the LQG controller is just as good as the PI controller in controlling the speed of the turbine, and has the advantage that it can be tuned such that the occurrence of torsional oscillations is mitigated. The study also concluded that some external method of dampening torsional oscillations should be implemented to mitigate torsional oscillations in case of a grid fault or loss of PWM signal.

Currently, wind energy presents an excellent opportunity to satisfy the growing demand without the supply and environmental problems associated with conventional energy. The engineering in wind turbines is not fully mature. There are still phenomenon, particularly dynamic stall, that cannot accurately be modeled or controlled. Dynamic stall contributes to fatigue stress and premature failure in many turbine components. The three dimensionality of dynamic stall makes these structures unique for wind turbines. Currently, flow visualization of dynamic stall on a wind turbine rotor has not been achieved. These visualizations can reveal a lot about the structures that contribute to dynamic stall. Particle Image Velocimetry (PIV) is a powerful experimental technique that can take multiple non-intrusive flow measurements simultaneously of planar flow. Using high-speed cameras time resolved PIV can reveal the transient development of a given flow field. This technique is ideally suited to gain a better understanding of dynamic stall. A custom wind turbine is being built at the University of Waterloo to allow such measurements on the blade. A high speed camera is mounted on the hub and will take measurements within the rotating domain. Mirrors are used so that laser illumination rotates with the blade. The wind turbine will operate in controlled conditions provided by a large wind tunnel. High speed pressure data acquisition will be used in conjunction with PIV to get an understanding of the forces associated with the flow structures. Computational fluid dynamics was used to size the rotor within the wind tunnel. Laser based measurements required special considerations for stiffness. Many revealing experiments will be made possible by this apparatus. First, the flow structures responsible for the various forces can be identified. Quantitative measurements of the flow field will identify the development of the stall vortex. The quantified flow structures can be used verify and improve models. The high spatial resolution of PIV can map the three dimensional flow structure in great detail. The experimental apparatus is independent of the blade geometry, as such multiple blades can be used to identify the effect of blade geometry. Finally flow control research in the field of aviation can be applied to control dynamic stall.