No description available.

No description available.

No description available.

No description available.

A neural network prediction method has been developed to compute self-noise of airfoils typically used in wind turbines. The neural networks were trained using experimental data corresponding to tests of several different airfoils over a range of flow conditions. The experimental data corresponds to the NACA 0012, Delft DU96, Sandia S831, S822 and S834, Fx63-137, SG6043 and SD-2030 airfoils. The chord of these airfoils range from 0.025 to 0.91 m and they were tested at Reynolds numbers of up to 3.8 million and angle of attack up to 15° depending on the airfoil. Using experimental data corresponding to different airfoils provides to the neural network the capacity to take into account the geometry of the airfoils in the predictions.geometry of the airfoils in the predictions. The input parameters to the network are the flow speed, chord length, effective angle of attack and parameters describing the geometrical shape of the airfoil. In addition, boundary layer displacement thickness was used for some models. The parameters used for taking into account the airfoil's geometry are based on a conformal mapping method or a polynomial approximation. The output of the neural network is given by sound pressure level in 1/3rd octave bands for nine frequencies ranging from 630 to 4000 Hz. The present work constitutes an application of neural networks to aeroacoustics. The main objective was to assess the potential of using neural networks to model airfoil noise. Therefore, this work is focused in the modeling of the problem, and no mathematical analyses about neural networks are intended. To this end, several models were investigated both in terms of the configuration and training approach. The performance of the networks was evaluated for a range of flow conditions. The neural network technique was first investigated for the NACA 0012 airfoil only. For this case, the geometry of the airfoil was not incorporated as input into the model. The neural network approach was then extended to account for airfoils of any geometry by including data from all airfoils in the training. The results show that the neural networks are capable of predicting the airfoils self-noise reasonably well for most of the flow conditions. The broadband noise due to the turbulent boundary layer interacting with the trailing edge is estimated very well. The tonal vortex shedding noise due to laminar boundary layer-trailing edge interaction is not predicted as well, most likely due to the limited data available for this noise source. In summary, the research here demonstrated the potential of the neural network as a tool to predict noise from typical wind turbine airfoils. / Master of Science

In the entirety of this project, a power converter is modeled, simulated, designed, and optimized to convert a three-phase AC wind turbine source to charge DC lead-acid batteries, applying new control techniques and an innqvative design to produce the most energy from the small wind turbine. The converter will implement new approaches to power factor correction and maximum power point tracking to capture the most energy under any operating conditions of the wind turbine. Overwind conditions will be protected against using the converter's ability to slow the turbine instead of usual resistive loads or mechanical braking. Other techniques to protect the batteries and the converter will be discussed in the scope of this paper. Through testing the designed converter, supporting evidence is shown whether the topology and control techniques are beneficial by comparing the degree of effectiveness of each method. The goal is to prove that these methods will provide a significant increase in energy converted.

The technologies of urban wind turbines have been rapidly developed in recent years, but urban wind turbines have not found a wide application due to the limitations of their designs. The power output of urban wind turbine is significantly affected by urban terrain, which can cause low speed flow with frequent change of its direction. Thus, there is a need for a new wind turbine to meet the requirements of an urban wind turbine. In this study, a novel wind turbine for urban areas was designed and developed. The investigations of the novel urban wind turbine were carried out by using computational fluid dynamic (CFD) simulations and wind tunnel tests. The results from the investigation have shown that the novel wind turbine has a great potential to harvest wind energy in urban areas. A detailed study of effects of each parameter on wind energy concentration of the novel wind turbine was carried out with CFD simulations. According to the simulation results, the shroud structure of the novel wind turbine was modified and the dimensions of the final structure were identified. It was determined that the capability of wind energy concentration of the novel wind turbine shroud has been significantly improved through the structure optimisations. Furthermore, guide vane and impulse turbine were implemented in the novel wind turbine. The flow characteristics through the guide vane was studied and discussed. It was found that the wind flow characteristics can be properly modified by implementing guide vane and the structure of impulse turbine was suitable to be implemented in the novel wind turbine due to the flow characteristic through the guide vane.

Experimental research has been completed using a custom designed and built 4m diameter wind turbine in a university operated wind facility. The primary goals of turbine testing were to determine the power production of the turbine and to apply the particle image velocimetry (PIV) technique to produce flow visualization images and velocity vector maps near the tip of a blade. These tests were completed over a wide range of wind speeds and turbine blade rotational speeds. This testing was also designed to be a preliminary study of the potential for future research using the turbine apparatus and to outline it's limitations. The goals and results of other large scale turbine tests are also briefly discussed with a comparison outlining the unique aspects of the experiment outlined in this thesis. Power production tests were completed covering a range of mean wind speeds, 6.4 m/s to 11.1 m/s nominal, and rotational rates, 40 rpm to 220 rpm. This testing allowed the total power produced by the blades to be determined as a function of input wind speed, as traditionally found in power curves for commercial turbines. The coefficient of power, Cp, was determined as a function of the tip speed ratio which gave insight into the peak power production of the experimental turbine. It was found, as expected, that the largest power production occurred at the highest input wind speed, 11.1 m/s, and reached a mean value of 3080 W at a rotational rate of 220 rpm. Peak Cp was also found, as a function of the tip speed ratio, to approach 0.4 at the maximum measurable tip speed ratio of 8. Blade element momentum (BEM) theory was also implemented as an aerodynamic power and force prediction tool for the given turbine apparatus. Comparisons between the predictions and experimental results were made with a focus on the Cp power curve to verify the accuracy of the initial model. Although the initial predictions, based on lift and drag curves found in Abbot and Von Doenhoff (1959), were similar to experimental results at high tip speed ratios an extrapolation of the data given by Hoffman et al. (1996) was found to more closely match the experimental results over the full range of tip speed ratios. Finally PIV was used to produce flow visualization images and corresponding velocity maps of the chord-wise air flow over an area at a radius ratio of 0.9, near the tip of a blade. This technique provided insight into the flow over a blade at three different tip speed ratios, 4, 6 and 8, over a range of wind speeds and rotational rates. A discussion of the unique aspects and challenges encountered using the PIV technique is presented including: measuring an unbounded external flow on a rotating object and the turbulence in the free stream affecting the uniform seeding and stability of the flow.

Wind energy accounts for 9.1% of the total energy capacity in Europe. Recent studies have raised critical questions regarding the dependability of current wind turbines. The statistical data reveals that gear box is the most critical component reducing dependability caused by increased failure rate, downtime, and high repair cost (J. Ribrant and L. Bertling, 2007). Gear box failures in wind farms reveal a staggering 19.4 % of downtime of operation (J. Ribrant and L. Bertling, 2007). A significant reduction in the failure rate has been observed in the recent years, but downtime of operation and high repair investment still remains a bottleneck. Wear is the most critical failure mode and a number of theories have been proposed in order to understand the system behavior of wear mechanism. The empirical and historical incident data shows that the lubrication system has the largest share of contribution of gearbox failures and wear rate. On other hand, a number of commercial lubrication system have developed to cope with wear mechanism, however, these systems have different capabilities and characteristics and needed to be assessed in a new life cycle perspective. The purpose of the thesis is to analyze the influence of lubrication system on the current problem of wear in Wind Turbine Gearbox and improve the existing lubrication system architecture. The research methodology adopted is System Engineering approach with architecture assessment tools. The expected result of the thesis is effective and efficient wind turbine gearbox lubrication system architecture and an efficient contractual process between lubrication system provider and purchaser.

Experimental research has been completed using a custom designed and built 4m diameter wind turbine in a university operated wind facility. The primary goals of turbine testing were to determine the power production of the turbine and to apply the particle image velocimetry (PIV) technique to produce flow visualization images and velocity vector maps near the tip of a blade. These tests were completed over a wide range of wind speeds and turbine blade rotational speeds. This testing was also designed to be a preliminary study of the potential for future research using the turbine apparatus and to outline it's limitations. The goals and results of other large scale turbine tests are also briefly discussed with a comparison outlining the unique aspects of the experiment outlined in this thesis. Power production tests were completed covering a range of mean wind speeds, 6.4 m/s to 11.1 m/s nominal, and rotational rates, 40 rpm to 220 rpm. This testing allowed the total power produced by the blades to be determined as a function of input wind speed, as traditionally found in power curves for commercial turbines. The coefficient of power, Cp, was determined as a function of the tip speed ratio which gave insight into the peak power production of the experimental turbine. It was found, as expected, that the largest power production occurred at the highest input wind speed, 11.1 m/s, and reached a mean value of 3080 W at a rotational rate of 220 rpm. Peak Cp was also found, as a function of the tip speed ratio, to approach 0.4 at the maximum measurable tip speed ratio of 8. Blade element momentum (BEM) theory was also implemented as an aerodynamic power and force prediction tool for the given turbine apparatus. Comparisons between the predictions and experimental results were made with a focus on the Cp power curve to verify the accuracy of the initial model. Although the initial predictions, based on lift and drag curves found in Abbot and Von Doenhoff (1959), were similar to experimental results at high tip speed ratios an extrapolation of the data given by Hoffman et al. (1996) was found to more closely match the experimental results over the full range of tip speed ratios. Finally PIV was used to produce flow visualization images and corresponding velocity maps of the chord-wise air flow over an area at a radius ratio of 0.9, near the tip of a blade. This technique provided insight into the flow over a blade at three different tip speed ratios, 4, 6 and 8, over a range of wind speeds and rotational rates. A discussion of the unique aspects and challenges encountered using the PIV technique is presented including: measuring an unbounded external flow on a rotating object and the turbulence in the free stream affecting the uniform seeding and stability of the flow.