In the past ten to fifteen years wind energy remerged on the world scene with a very healthy growth rate, it has outstripped photovoltaics (solar cells) as the world’s fastest growing energy source, with a growth rate in excess of 30 percent per annum. No longer just a “nice idea for the future” Wind energy is becoming a mainstream energy source for many countries. The proposed paper will present a procedure (using numerical methods) for the design and analysis of Horizontal Axis Wind Turbine (HAWT) rotors. To ascertain the accuracy and to determine where further improvements could be initiated; numerical findings were then compared with published experimental test data and the compression showed an average deviation of less than 3% and therefore the simplifying assumptions made for the prediction of fluid behavior over an airfoil section was justified. Once the approach was validated and standardised a comprehensive airfoil design was produced. A computational fluid dynamic code coupled with a simple numerical algorithm aided the inverse design procedure. The final design was well proportioned and was theoretically able to meet the stated objective function and satisfied all the imposed constraints (manufacturing and geometrical). The geometrical data was then generated in a form suitable for manufacture using manually and numerically controlled machines.

Wind energy is currently the fastest growing electricity source. To meet the output demand, wind turbines are becoming larger and more flexible leading to the problems of structural load especially in case of offshore turbines. Advanced control algorithms are developed to reduce the load, allowing to build larger turbines, and expand their lifetime. Observer-based control algorithms such as Linear-Quadratic-Gaussian LQG control which uses LQR to calculate the optimal observer and controller gains are commonly applied to wind turbines in literature. However the approach requires to calculate the observer and control gains separately. In addition, linear models used for parameter calculation may have errors with respect to the nonlinearities of wind turbines and induced to unmodeled dynamical properties. These modeling errors need to be considered to to guarantee the stability of the controlled system. Alternatively a robust design assuming bounds and limits of models have to be realized to guarantee stability while ignoring details of modeling. This paper proposes an optimal robust observer-based state feedback controller for large-scale wind turbines to realize multi objectives, including structural load mitigation and rotor speed regulation. The novel contribution is that the observer gain parameters, control gains, and integral action are optimized at the same time within H ∞ mixed sensitivity framework to achieve desired performance with respect to power regulation, structural load mitigation, and also robustness for the wind turbine control system. The control performances have been verified by a high fidelity simulation software and are compared to those of a classical baseline controller.

This research presents a convergence analysis for an iterative framework for optimizing plant and controller parameters for active systems. The optimization strategy fuses expensive yet valuable experiments with less accurate yet cheaper simulations. The numerical model is improved at each iteration through a cumulative correction law, using an optimally designed set of experiments. The iterative framework reduces the feasible design space between iterations, ultimately yielding convergence to a small design space that contains the optimum. This paper presents the derivation of an asymptotic upper bound on the difference between the corrected numerical model and true system response. Furthermore, convergence of the numerical model to the true system response and convergence of the design space are demonstrated on an airborne wind energy (AWE) application.

Wind energy is a rapidly expanding source of renewable energy, but is highly intermittent. The performance of a wind farm, composed of a collection of wind turbines, depends not only on the placement of wind turbines in a farm, but also control actions taken by individual turbines. The wind turbine placement (layout) design problem involves adjusting turbine locations within a given area to improve a performance objective (such as maximizing annualized energy production). This layout problem has been addressed previously considering the effect of constraints such land configuration, installed capacity, and wake model choice on the performance of wind farms. All the studies, however, ignore the effects of the control system, which can have significant impact on performance. A well designed wind farm — without an optimal controller — will not achieve the full system level optimal performance, and vice-versa. In this article, we propose a novel layout co-design approach that includes optimal control considerations to exploit this synergy between farm layout and control. Layout case studies involving 8 and 12 turbines are presented. An annual energy production improvement of up to 17% is observed when accounting for coupling between control and layout design, when compared to layout-only optimization.

This paper presents a sustainable design method for wind turbines. Sustainable design recognizes three main pillars; economic growth, social equity, and environmental protection. A framework is developed to observe the tradeoffs among these areas of sustainable design. Each pillar of sustainability is mapped to a design variable, and normalized objective functions are defined. For the economic component, the objective function is based on costs and power production. The societal objective function focuses on noise and aesthetics impacts. These are represented by risk averse utility functions. Carbon dioxide emissions and noise pollution are the environmental objectives. A multi-objective genetic algorithm is also used with Pareto optimality to identify tradeoffs between these three sustainability factors. Wind speed data from three sites is used to simulate the performance of the system. The sets of data are unique and represent low, medium, and high wind speed areas. In all three cases, the results indicate that the economic and environmental objectives can both be met with a relatively small tradeoff. However, a greater amount of tradeoff is necessary when considering societal impacts.

Maintenance costs are a main cost driver for offshore wind energy. Prediction of failure and particularly failure understanding can help to bring these costs down significantly. Since the wind turbine is subjected to a large number of dynamic events it is important to fully understand the turbine response to these events. Pattern mining has been used successfully for different applications. We believe it to have large potential for understanding turbine behavior based on turbine status logs. These logs record all turbine actions and can be used as input for pattern mining algorithms. This paper proposes the use of a multi-level pattern mining approach in order to minimize the number of uninteresting patterns and facilitate response understanding. The paper mainly focuses on the extraction of patterns and association rules linked to certain alarms and how they can be annotated for further use in the multi-level pattern mining approach. Several years of wind turbine data is used. The use of the approach is illustrated by detecting the characteristic pattern linked to turbine response to an Extremely High Wind Speed Alert.

Wind turbines can provide energy in developing countries. However, there are limitations to the skilled labor and manufacturing equipment required to manufacture these systems in these regions. Accordingly, the manufacturing process needs to be adapted to the potential of the developing world. In this work, a simplified wind turbine blade design is investigated. The turbine efficiency is analyzed by the blade element momentum (BEM) theory. Two different scenarios are considered to simplify the design of the wind turbine blade. The shape of the blade is simulated by a rectangular root connected to several trapezoidal segments. This results in a simple chord length distribution. The design of the twist angle is also considered. The area under the power curve is used to compare the performance of the simplified blades with that of the original design. Results show that the twist angle can be completely omitted as a tradeoff between efficiency and manufacturability. Depending on the number of simplified design segments, the area under the power curve is reduced between 13% and 25 % with respect to the original blade. The model also demonstrates how the loss in efficiency increases as the simplicity of blade design increases. Still, the design simplification enables a manufacturing process which may facilitate the use of wind energy in the developing world.

When designing a wind turbine blade, the goal is to attain the highest possible power output under specified atmospheric conditions.In this paper,the maximum likelihood estimation method was used to compute the hub height wind speed at 65m mathematical model based on the observation data of He xi Corridor wind at 10m height, taking He xi region of a certain type of 40m blade as an example, based on the Blade Element Momentum Theoty and tip loss, established the blade aerodynamic mathematic model, using the genetic algorithm on the blades. Each section of the chord, twist angle of wind energy utilization coefficient, girder cap layer thickness parameters were optimized, The aerodynamic performance and stress distribution are given out, the results showed that the optimized blade wind energy utilization coefficient is greatly improved and the quality of the blade is significantly reduced. It is suitable for wind the characteristics of the blade design condition performance supper than that of general blade.It provides a theoretical basis for the blade design.

A variable ratio gearbox (VRG) provides discrete variable rotor speed operation, and thus increases wind capture, for small fixed-speed wind turbines. It is a low-cost, reliable alternative to conventional variable speed operation, which requires special power-conditioning equipment. The authors’ previous work has demonstrated the benefit of using a VRG in a fixed-speed system with passive blades. This work characterizes the performance of the VRG when used with active blades. The main contribution of the study is an integrative design framework that maximizes power production while mitigating stress in the blade root. As part of the procedure, three gear ratios are selected for the VRG. It establishes the control rules by defining the gear ratio and pitch angle used in relation to wind speed and mechanical torque. A 300 kW wind turbine model is used for a case study that demonstrates how the framework is implemented. The model consists of aerodynamic, mechanical, and electrical submodels, which work collaboratively to convert kinetic air to electrical power. Blade element momentum theory is used in the aerodynamic model to compute the blade loads. The resulting torque is passed through a mechanical system and subsequently to the induction machine model to generate power. The BEM method also provides the thrust and bending loads that contribute to blade-root stress. The stress in the root of the blade is also computed in response to these loads, as well as those caused by gravity and centrifugal force. Two case studies are performed using wind data that was obtained from the National Renewable Energy Laboratory (NREL). Each of these represents an installation site with a unique set of wind conditions that are used to customize the wind turbine design. The framework uses dynamic programming to simulate the performance of an exhaustive set of combinations. Each combination is evaluated over each set of recorded wind data. The combinations are evaluated in terms of the total energy and stress that is produced over the simulation period. Weights are applied to a multi-objective cost function that identifies the optimal design configurations with respect to the design objectives. As a final design step, a VRG combination is selected, and a control algorithm is established for each set of wind data. During operation, the cost function can also be used to bias the system towards higher power production or lower stress. The results suggest a VRG can improve wind energy production in Region 2 by roughly 10% in both the low and high wind regions. In both cases, stress is also increased in Region 2, as the power increases. However, the stress in Region 3 may be reduced for some wind speeds through the optimal selection of gear combinations.

Implementing microgrids has become a current trend in the electric utility industry to either improve system reliability or energy access for energy sustainability. This study proposes a probability-based strategy for both long- and short-term power dispatch with wind and load uncertainty. The long-term power dispatch is used to determine a suitable capacity of energy storage, and the short-term power dispatch is used for real-time operation. For both short- and long-term power dispatch, the trends of wind energy and electricity demand are extracted using the wavelet packet analysis method and the moving average technique. The uncertainties from wind speed and power generation data are modeled with log-normal and extreme value distributions, respectively. From the obtained power dispatch and model forecasting, the capacity of energy storage is determined. To validate the proposed approach, a real-time operating simulation is used as a case study to observe the behavior of the wind-integrated electrical system. Results show that the proposed method can estimate the uncertainty variation range of wind energy and the state of charge of energy storage effectively.

Wind energy is one of the fastest growing sectors of renewable energy technologies. Micro-scale wind turbines are becoming increasingly more popular as individuals seek more innovative and efficient ways of reducing their energy demand. However, even with more efficient wind energy harvesting devices, it is not uncommon for the anticipated energy harvesting potential for a wind turbine to be vastly different from the actual energy generation capability for a site. This paper will introduce the problems associated with accurately predicting the energy generation potential of wind energy harvesting systems considering several power loss factors. The focus of this paper is on the use of commonly available engineering tools and simulations to evaluate obstructions on the implementation site and energy harvesting technologies in order to maximize the energy generation potential. The issues of energy generation prediction accuracy will be addressed by incorporating high-resolution weather data and computer simulations into a predictive model. Additionally, several correction factors and design guidelines for the successful implementation of micro-scale wind turbines will be introduced and discussed. A multi-step approach is introduced to collect weather data, generate revised energy generation potential models for various land regions, account for common site obstructions through the use of correction factors, and formulate a final set of recommendations for the wind turbine implementation site. A set of design guidelines are also developed to assist in turbine placement for specific site locations. The guidelines are based on the revised energy generation prediction model, wind speed correction factors for common site obstructions, orientation and placement of the wind turbine, and other factors. Verification of the guidelines has been performed through Computational Fluid Dynamics simulation. The design approach and guidelines are examined and results presented for one case study.

Wind energy production has been increasing steadily in the past decade. The majority of wind power is generated by horizontal axis wind turbines (HAWT). We investigate the modeling of the HAWT using the vortex panel method, which is an inviscid, steady, computationally inexpensive method. Pressure coefficient profiles, calculated by the vortex panel method, were compared to NREL phase VI wind turbine experiments under two different flow conditions. We show that if the flow is not separated over the blade, the vortex panel method can capture the pressure profile on the blade. Furthermore, the panel method has been extended to handle unsteady inviscid flows to investigate the effect of blade oscillations on the power generation, which is not known. The unsteady behavior is modeled by accounting for the time rate of change of circulation. Unsteady effects due to heaving and pitching motion were quantified for different blade oscillation frequencies. It is estimated that the mean thrust coefficient with heaving and pitching motion can be higher than the thrust generated without blade motion in some cases assuming that the flow does not separate.

In this paper, a piezoelectric leaf generator for harvesting wind energy was proposed, fabricated and tested. The leaf generator had a bimorph cantilever structure, with Su-8 as the protective supporting layer, and aligned lead zirconate titanate (PZT) nanofibers as the active layer. Interdigitated electrodes were sputtered on top of the aligned PZT nanofibers to collect the generated charge. After fabrication of the leaf generator, it was tested in a wind tunnel with different wind incident angles and wind speeds. The maximum voltage output of the leaf generator was 820 mV when the wind speed was 17 m/s. The developed leaf generator does not need further bonding to the vibration source, which make it much easier for real applications. In addition, benefited from unique material properties of the PZT nanofiber such as flexible, robust, and high piezoelectric coupling ability, the leaf generator is promising for a high efficiency wind energy harvest.

Wind energy conversion is the fastest growing source of electricity generation in the world among the other renewable energy production technologies. Whereas investment costs have decreased over years, operational and maintenance costs of wind turbines are still high, thus attracting the focus of researchers and industrial operators. Classical maintenance techniques, i.e. : run-to-failure and scheduled-preventive maintenance, are still dominant in this sector; however, condition monitoring has gained space in the wind turbine market and new diagnostic methods and techniques are continuously being proposed. Condition monitoring techniques seem the most effective tools to minimize operational and maintenance costs and reduce downtimes by early detection of faults. This paper is aimed at reviewing the state of the art of condition monitoring for horizontal axis wind turbines. After a brief introduction presenting the current trends in the market of wind energy, the paper reviews the most common failure modes of wind turbines and the traditional approach to maintenance. The core of this study details the state of the art in the field of system architectures, sensors and signal processing techniques for the diagnostic of faults in wind turbine components. Finally, some general conclusions are drawn on the overall trends in the field of condition monitoring of wind turbines.

The primary objective of this paper is to design an aerodynamically efficient delta kite that can balance a given load when subjected to aerodynamic loads at a specific angle of attack (α) and altitude (h). The aerodynamic forces calculated based on the potential theory heavily underestimate the forces because of the formation of leading edge vortices on the delta shaped kite. The leading edge vortices are the flow separations caused at the sharp leading edge even for very small angles of attack, which remain attached to the leading edge while the kutta condition is still satisfied at the trailing edge. Vortex lift and induced drag due to the leading edge vortices are calculated using the Polhamus method. Aerodynamic loads (L and D) have been computed by determining proportionality constants (k p , k v ) using the standard Multhopp lifting surface theory (MLST). The variation of (C L ) and (ΔC D ) for delta kites with aspect ratio A=1, 1.5 and 2 has been examined and validated by comparing the computed C L and ΔC D values to experimental measurements. A set of vertical and horizontal loads (W T ,H T ) that can be balanced by delta kite at operational heights h=140, 150 and 160 m and α=8° has been successfully determined using this method. The method will be applied for the design and control of a delta kite, which will be used to harvest wind energy at high altitudes.

Wind turbine tower design looks primarily at the structural integrity and durability of the tower. Optimization techniques are sometimes employed to maximize the loading capability while reducing material use and cost. Still, the tower is a dynamic part of a complex wind energy conversion system. During system operation, the tower is excited and sways back and forth. This undesirable movement increases cyclical loading on the tower and drivetrain components. To minimize this motion the tower frequency must be offset from the natural frequency of other components. Hence, it is necessary to look at the relationships that exist between the tower and other wind turbine components, such as the rotor, nacelle, and foundation. In addition, tradeoffs between cost, structural performance, and environmental impact can be examined to guide the designer toward a truly sustainable alternative to fossil fuels. Ultimately, an optimal design technique can be implemented and used to automate tower design. This work will introduce the analytical model and decision-making architecture that can be used to incorporate greater considerations in future studies. In this paper, nine wind turbine tower designs with different materials and geometries are analyzed using Finite Element Analysis (FEA). The optimal tower design is selected using a multi-level variation of the Hypothetical Equivalents and Inequivalents Method (HEIM). Using this analysis, a steel tower with variable thickness has been chosen. The findings reaffirm that steel is a favorable choice for turbine tower construction as it performs well on environmental, performance, and cost objectives. The method proposed in this work can be expanded to examine additional design goals and present a higher fidelity model of the wind turbine tower system in future work.

High turbine reliability is of utmost importance to keep the cost of wind energy to a minimum. A considerable problem in this regard is that of premature drivetrain failures, which have plagued the wind turbine industry since its inception. Accurate prediction of the loads encountered by the drivetrain components during their lifetime is essential for reliable wind turbine design. Of particular interest are transient load events, which are expected to have a detrimental effect on the lifetime of drivetrain components, especially when they give rise to torque reversals. At the electrical side of the wind turbine, transient events worth investigating include grid faults, emergency stops and grid loss. Unlike previous research on the impact of these events, which typically uses simplified gearbox representations, this paper investigates the dynamic behavior of wind turbine drivetrains during grid faults using a coupled simulation of a flexible multibody model of a commercial multimegawatt wind turbine drivetrain and a Simulink model of a doubly fed induction generator (DFIG) and its controller. The mathematical modeling of the DFIG as well as the flexible multibody modeling of the drivetrain are described. Both gear and bearing forces on several components of the gearbox are examined during a symmetrical and asymmetrical voltage dip, and the influence of gearbox flexibility on these loads is assessed.

Sustainability is gaining national and global prominence as a key external constraint in engineering design. Courses in solar energy and wind energy have been common offerings, but due to their power production focus, do not address sustainability in the broader context of design. The question becomes, are undergraduate mechanical engineering programs evolving to introduce design for sustainability concepts, such as life cycle assessment, the triple bottom line, and carbon balance, in the broader context of mechanical engineering design? A review of mechanical engineering programs at well recognized universities indicates that most course offerings with definable sustainable design content remain focused on sustainable energy production. In addition, most of these courses are primarily graduate level offerings, indicating a substantial population of recent graduate engineers with limited knowledge of the scope of design for sustainability. Isolated efforts to broaden awareness of sustainability concepts were also identified and will be reported. These programs may serve as models for integration of sustainability into the general mechanical design education.

Power transmission faults are one important cause of machine downtime many production activities are working to prevail. Vibration monitoring tools have achieved this role on the assumption that the stationary condition hypothesis is maintained. Several industries, including wind energy production, are however demanding to observe mechanical or electrical rotating components behaviour at variable speeds. Instantaneous angular speed measurement has been recently proven able to detect localized faults in bearings using only an encoder close from the source of the defect. This paper presents the results obtained from a large span experiment on a 2MW wind turbine. The uniqueness of the sensor used to monitor the whole line shafting along with the continuous non stationary conditions are so many difficulties cumulated on this attempt. Two basic signal processing tools are theoretically defined and experimentally applied in an original way on the Instantaneous Angular Speed measurement to efficiently tackle these practical issues.

In two recent studies [1; 2], the authors have presented the concept and the analytical modeling framework for a scalable wind micro-power generator. The device transforms wind energy into electricity via the self-excited oscillations of a piezoelectric reed embedded within a cavity. Based on the model developed in [2], this effort utilizes the Routh-Hurwitz criterion and numerical algorithms to understand the influence of the design parameters on the device’s response with the goal of minimizing the cut-on wind speed and maximizing the output power. Results indicate that, for a beam of certain design parameters, there exists an optimal chamber volume that minimizes the cut-on wind speed of the device. This optimal volume is inversely proportional to the beam’s first modal frequency. Results also indicate that the cut-on wind speed can be decreased significantly as the aperture’s width is decreased. However, due to the reduced strain rate in the piezoelectric layer, it is observed that minimizing the cut-on wind speed does not always correspond to an increase in the output power. As such, in an attempt to study the influence of the design parameters on the output power, design charts were constructed to select the optimal design parameters for a known average wind speed. Experimental results are also presented to qualitatively verify the theoretical trends.