In this work, two approaches for computing the near-field distribution around wind turbines are proposed, including: (1) Huygens Principle and (2) the parabolic equation technique. In order to simplify the problem, the cylinder model is utilized to represent the wind turbines and transform the problem into a two-dimensional case. To make Huygens Principle computationally tractable, several approximations are made based on the problem geometry especially modelling the cylinder as a plate. The expression of the electromagnetic field radiated by the equivalent magnetic current can be analytically solved by the error function. To verify the results, FEKO is utilized to simulate the scattering of infinitely long cylinders using periodic boundary condition (PBC). In order to solve the problem of multiple cylinders, a modified method is derived. For more accurate results, the parabolic equation (PE) technique is utilized to solve this problem, which is usually utilized to solve wave propagation problems. In this case, wide-angle approximation is used to solve the parabolic equation, which can obtain accurate results in a region of up to 45 degrees. Although these two approaches are not full-wave simulation, the calculation time is significantly reduced and the error is acceptable. To further verify the computed results by the parabolic equation technique, two commercial transceivers from Time Domain Corporation are used to measure the field distribution behind a finite-length metal pole. The frequency-domain results are obtained from the measured time-domain results using the fast Fourier transform. It is shown that the computed results by the parabolic equation technique agree well with the measurement results. / text

The majority of offshore wind farms utilize monopile substructures. As these wind farms are typically located in water depths less than 30 meters, the effect of breaking waves on these structures is of great concern to design engineers. This research investigation examines many of the practical considerations and alternative ways of estimating breaking wave forces. A survey of existing European wind farms is used to establish a realistic range of basic design parameters. Based upon this information a parametric study was pursued and a series of realistic design scenarios were evaluated. Comparisons include the sensitivity to the wave force model as well as to analytical and numerical wave theories used to evaluate the wave kinematics. In addition, the effect of different kinematics stretching techniques for linear waves is addressed. Establishing whether the bathymetry will induce spilling or plunging wave breaking is critical. Spilling wave breaking can be addressed using existing wave and wave force theories; however for plunging wave breaking an additional impact force must be introduced. Dimensionless design curves are used to display pertinent trends across the full range of design cases considered. This research study provides insight into the evaluation of the maximum breaking wave forces and overturning moment for both spilling and plunging breaking waves as a function of bottom slope.

This thesis focuses on permanent magnet "direct drive" electrical generators for wind turbines with large power output. A variety of such generator topologies is reviewed, tested and optimised in an attempt to increase their potential as commercial concepts for the wind industry. Direct drive electrical generators offer a reliable alternative to gearbox drivetrains. This novel technology reduces energy loses thus allowing more energy to be yield from the wind and decreases the maintenance cost at the same time. A fundamental issue for these generators is their large size which makes them difficult to manufacture, transport and assembly. A number of structural designs have been suggested in the literature in an attempt to minimise this attribute. A set of design tools are set out in an attempt to investigate the structural stiffness of the different permanent magnet direct drive generator topologies against a number of structural stresses that apply to such wind turbine energy converters. Optimisation techniques, both analytical and structural, are also developed for minimising the total mass of a variety of "directly driven" machines with power output of 5MW or greater. Conventional and promising generator designs are modelled and optimised with the use of these optimisation techniques. The topologies under examination are then compared in terms of structural mass, stiffness and cost. As the number of wind turbine manufactures who adopt the direct drive concept increases, it is important to outline the unique characteristics of the different topologies and increase their manufacturing potential. Discussions and conclusions will provide an indication of the design solutions that could help decrease the mass and cost of such machines.

Wind is becoming an increasingly important source of energy for countries that ratify to reduce the emission of greenhouse gases and mitigate the effects of global warming. Investments in wind farms are affected by inter-related assets and stakeholders’ requirements. These requirements demand a well-founded Asset Management (AM) frame-work which is currently lacking in the wind industry. Drawing from processes, tools and techniques of AM in other industries, a structured model for AM in the wind industry is developed. The model divulges that maintenance is indispensable to the core business objectives of the wind industry. However, the common maintenance strategies applied to wind turbines are inadequate to support the current commercial drivers of the wind industry. Consequently, a hybrid approach to the selection of a suitable maintenance strategy is developed. The approach is used in a case study to demonstrate its practical application. Suitable Condition-Based Maintenance activities for wind turbines are determined. Maintenance optimisation is a means to determine the most cost-effective maintenance strategy. Field failure and maintenance data of wind turbines are collected and analysed using two quantitative maintenance optimisation techniques; Modelling System Failures (MSF) and Delay-Time Maintenance Model (DTMM). The MSF permits the evaluation of life-data samples and enables the design and simulation of a system’s model to determine optimum maintenance activities. Maximum Likelihood Estimation is used to estimate the shape (β) and scale (η) parameters of the Weibull distribution for critical components and subsystems of the wind turbines. Reliability Block Diagrams are designed using the estimated β and η to model the failures of the wind turbines and of a selected wind farm. The models are simulated to assess and optimise the reliability, availability and maintainability of the wind turbine and the farm. The DTMM examines equipment failure patterns by taking into account failure consequences, inspection time and cost in order to determine optimum inspection intervals. Defects rate (α) and mean delay-time (1/γ) of components and subsystems within the wind turbine are estimated. Optimal inspection intervals for critical subsystems of the wind turbine are then determined.

a control, power quality and stability perspective. This is chiefly due to the future influence on power system behaviour resulting from the rapid cumulative growth of grid integrated wind power, and the improved control characteristics afforded by modern variable speed wind power generators. There is consequently strong motivation to enhance the inherent control robustness, power quality and fault-ride-through characteristics of modern wind power generators. By so doing, the attributes essential for power system operation regarding security of supply, reliability, and power quality can be assured. The work presented in this thesis employs a two-fold methodology in order to improve the inherent control, power quality and fault tolerance characteristics of a modern wind power generator based on a 2MW medium-voltage directly-driven permanently-excited architecture employing full-scale power conversion. Firstly, due to the complexity of modern wind power generators, accurate and complementary detailed non-linear (circuit orientated) and linear analytical (state-space based) wind generator models are developed. Collectively, these facilitate a wide range of detailed transient and smallsignal, control, stability and fault analysis studies. Ultimately, this facilitates the means by which advanced AC voltage controls are developed that significantly extend the wind power generator stable operating range for grid strength variations (grid impedance variation). Secondly, a supercapacitor based electrical energy storage system is designed and integrated within the developed wind generator models in order to facilitate the means by which fault-ridethrough characteristics and power quality can be improved. Fault-ride-through characteristics are ultimately improved by absorbing a proportion of generated power in the integrated storage system during grid-side faults. Power quality is ultimately improved by effectively buffering wind speed fluctuations in the integrated storage system so that a ‘smoothed’ version of the generated power results at the wind generator terminals.

The work presented in this thesis aims at investigating the attachment of lightning flashes to wind turbines. Modern wind turbines are highly exposed to lightning strikes, due to the increase of their height and the rotation of the blades. Upward lightning is the dominant mechanism of lightning strikes to them. Therefore, this study evaluates the initiation of the initial upward leader discharge and the process of lightning attachment of dart leaders taking place prior to the first return stroke in upward flashes. This work extends the self-consistent leader inception and propagation model (SLIM) to evaluate the lightning attachment of dart and dart-stepped leaders to grounded objects. SLIM was originally proposed to evaluate the lightning attachment of stepped leaders. Unlike the well-studied lightning attachment of stepped leaders, upward connecting leaders initiated in response to dart and dart-stepped leaders develop under a significantly faster change of the ambient electric field. Additionally, these connecting leaders could develop in warm air pre-conditioned by the previous strokes in the same flash. An analytical expression to evaluate the charge required to thermalize the connecting leader per unit length is also developed in the extended model. This model is validated through the analysis of three attachment events recorded in rocket-triggered lightning experiments. Good agreement between the predicted properties of the upward leaders and the measurements has been found. The model is utilized to evaluate the different conditions where connecting leaders can develop prior to the return strokes in upward lightning. The extended model of SLIM is also applied to study the interception of lightning dart leaders by upward connecting leaders initiated from wind turbines. The evaluation considers the influence of the return stroke peak current, the blade rotation and wind on the attachment of lightning dart leaders to wind turbines. The probability of lightning strikes to the receptors along the blade and on the nacelle is calculated for upward lightning flashes. It is shown that the lightning attachment of dart leaders is a mechanism that can explain the lightning damages to the inboard region of the blades (more than 10 meters from the tip) and the nacelle of wind turbines. Furthermore, the critical stabilization electric field required to initiate upward lightning from wind turbines is evaluated for both ‘self-initiated’ and ‘other-triggered’ upward flashes. The calculation shows that the stabilization electric field of an operating wind turbine periodically changes due to the rotation of its blades.  The initiation of upward lightning is greatly facilitated by the electric field change produced by nearby lightning events. However, the rate of rise of the electric field only has a weak impact on the stabilization electric field. The evaluation of the stabilization electric field provides essential information needed for the estimation of the incidence of upward lightning to wind turbines. / <p>QC 20161201</p>

This report describes how a new and modern monitoring system is crea- ted for a wind turbine. Elvira Vind AB is a company that has an old operating surveillance system manufactured in 1992. A need has arisen with the owner of the company and are looking for a simple and smooth system that monitors the situation in a wind turbine. Therefore, a system is created that can transmit data wireless- ly through a GSM-module. The system must be able to sense temperature, vibration and sound levels. Also a camera has to take a picture when it de- tects vibration and display the values of the sensors in a web site. The system must also be powered during a power failure, therefore a voltage regulator and a charging circuit was made in the circuit board. The goal of this project is to create a sensor-based monitoring system for a wind turbine and to see the sensor readings wirelessly and displayed in a web site. The report describes how the electronic circuit board has been created and which methods have been used for each sensor in this project. There is also a description of how to use the system for both software and hardware. / Övervakningssystem för vindkraftverk

Esta dissertação aborda o desenvolvimento de um método numérico para a análise de forças e momentos aerodinâmicos em turbinas eólicas fixas e flutuantes no domínio do tempo, utilizando a teoria da quantidade de movimento do elemento de pá (Blade Element Momentum Theory, BEMT) em C++. As pás são divididas em segmentos menores, onde a influência da turbina no fluxo é realizada através do cálculo de fatores de indução. Cada segmento é considerado como um aerofólio bidimensional, sendo possível estimar forças e momentos através de coeficientes para asas infinitas. A teoria da quantidade de movimento do elemento de pá, embora conceitualmente simples, é usualmente empregada com algumas correções em suas equações para se ajustar aos resultados experimentais. A inclusão de turbinas flutuantes é realizada através do movimento de corpo rígido da plataforma, que tem um impacto direto no cálculo aerodinâmico. Por não ser o objetivo deste trabalho, as equações de movimento são calculadas através de uma fonte externa e posteriormente colocadas como dado de entrada do código, simplificando assim a análise e excluindo uma fonte potencial de erro na verificação. O caso de estudo é a turbina do projeto Offshore Code Comparison Collaboration Continuation (OC4), a qual é analisada como uma turbina fixa e flutuante, utilizando uma plataforma semi-submersível. Os resultados das forças e momentos aerodinâmicos do software FAST do Laboratório Nacional de Energias Renováveis (National Renewable Energy Laboratory, NREL) são comparados ao código desenvolvido, mostrando excelente concordância para todos os casos analisados. / This dissertation addresses the development of a numerical method for the analysis of aerodynamic forces and moments of fixed and floating wind turbines in time domain, using the Blade Element Moment Theory (BEMT) written in C++. The blades are divided into smaller segments, where the influence of the turbine in the flow is performed through the calculation of induction factors. Each segment is considered as a two-dimensional airfoil, and it is possible to estimate forces and moments through coefficients for infinite wings. The Blade Element Moment Theory, though conceptually simple, is usually employed with some corrections in its equations to fit experimental results. The inclusion of floating turbines is performed through the rigid body motion of the platform, which has a direct impact on the aerodynamic calculation. Since it is not the objective of this work, the equations of movement are calculated through an external source and then placed as input data of the code, thus simplifying analysis and excluding a potential source of error in verification. The case of study is the turbine of the Offshore Code Comparison Collaboration Continuation (OC4) project, which is analyzed either as a fixed or a floating turbine, using a semi-submersible platform. The results of aerodynamic forces and moments from FAST software of the National Renewable Energy Laboratory (NREL) are compared to the developed code, showing excellent agreement for all cases analyzed.

Electricity demand is rapidly increasing with growth of population, development of technologies and electrically intensive industries. Also, emerging climate change concerns compel governments to seek environmentally friendly ways to produce electricity such as wind energy systems. In 2018, the wind energy reached 600 GW total capacity globally. However, this corresponds to only about 6% of global electricity demand and there is a need to increase wind energy penetration in electricity grids. One way to enhance the competitiveness of wind energy is to improve its reliability and availability and reduce associated maintenance costs. This study utilizes a database entitled “Wind Monitor and Evaluation Program (WMEP)” to investigate, model and improve wind turbine reliability and availability. The WMEP database consists of maintenance data of 575 wind turbines in Germany during 1989-2008. It is unique as it includes details of turbine model and size, affected subsystem and component, cause of failure, date and time of maintenance, location, and energy production from the wind turbines. Additional parameters such as climatic regions, geography number of previous failures and mean annual wind speed are added to the database in this study. In this research, two metrics are considered and developed such as time-to-failure or failure rate and time-to-repair or downtime for reliability and availability, respectively. This study investigated failure causes, effects and criticalities of wind turbine subsystems and components, assessed the risk factors impacting wind turbine reliability, modeled the reliability of wind turbines based on assessed risk factors, and predicted the cost of wind turbine failures under various operational and environmental conditions. A well-established reliability assessment technique - Failure Modes, Effects and Criticality Analysis is applied on the WMEP maintenance data from 109 wind turbines and three different climatic regions to understand the impacts of climate and wind turbine design type on wind turbine reliability and availability. First, climatic region impacts on identical wind turbine failures are investigated, then impacts of wind turbine design type are examined for the same climatic region. Furthermore, we compared the results of this investigation with results from previous FMECA studies which neglected impacts of climatic region and turbine design type in section 5.4. Two-step cluster and survival analyses are used to determine risk factors that affect wind turbine reliability. Six operational and environmental factors are considered for this approach, namely capacity factor (CF), wind turbine design type, number of previous failures (NOPF), geographical location, climatic region and mean annual wind speed (MAWS). Data are classified as frequent (time-to-failure<40 days) and non-frequent (time-to-failure>80 days) failures and we identified 615 operations listing all these factor and energy production from 21 wind turbines in the WMEP data base. These factors are examined for their impact on wind turbine reliability and results are compared. In addition, wind turbine reliability is modeled by machine learning methods, namely logistic regression (LR) and artificial neural network (ANN), using the considered 615 operations. The objective of this investigation is to model and predict probability of frequently-failing wind turbines based on wind turbines’ known operational and environmental conditions. The models are evaluated and cross validated with 10-fold cross validation and prediction performances and compared with other algorithms such as k-nearest neighbor and support vector machines. Also, prediction performances of LR and ANN are discussed along with their easiness to interpret and share with others. Lastly, using data from 753 operations, a decision support tool for predicting cost of wind turbine failures is developed. The tool development includes machine learning application for estimating probability of failures in 60 days of operation and time-to-repair probabilities for divisions of 0-8hrs, 8-16hrs, 16-24hrs and more than 1 day based on operational and environmental conditions of wind turbines. Prediction for cost of wind turbine failures for 60 days of operation is calculated using assumed costs from time-to-repair divisions. The decision support tool can be updated by the user’s discretion on the cost of failures. This study provides a better understanding of wind turbine failures by investigating associated risk factors, modeling wind turbine reliability and predicting the future cost of failures by applying state-of-the art reliability and data analysis techniques. Wind energy developers and operators can be guided by this study in improving the reliability of wind turbines. Also, wind energy investors, operators and maintenance service managers can predict the cost of wind turbine failures with the decision support tool provided in this study.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1982. / Microfiche copy available in Archives and Barker / Includes bibliographical references. / by Edward N. Marcus. / M.S.