Size Of Wind Turbines Research Articles

Comprehensive Bird Preservation at Wind Farms.

Wind as a clean and renewable energy source has been used by humans for centuries. However, in recent years with the increase in the number and size of wind turbines, their impact on avifauna has become worrisome. Researchers estimated that in the U.S. up to 500,000 birds die annually due to collisions with wind turbines. This article proposes a system for mitigating bird mortality around wind farms. The solution is based on a stereo-vision system embedded in distributed computing and IoT paradigms. After a bird’s detection in a defined zone, the decision-making system activates a collision avoidance routine composed of light and sound deterrents and the turbine stopping procedure. The development process applies a User-Driven Design approach along with the process of component selection and heuristic adjustment. This proposal includes a bird detection method and localization procedure. The bird identification is carried out using artificial intelligence algorithms. Validation tests with a fixed-wing drone and verifying observations by ornithologists proved the system’s desired reliability of detecting a bird with wingspan over 1.5 m from at least 300 m. Moreover, the suitability of the system to classify the size of the detected bird into one of three wingspan categories, small, medium and large, was confirmed.

A Study on Relationship among Blade Camber Direction and Pitch Angle and Performance of a Small Straight-Blade Darrieus Wind Turbine by Using Scale Test Model and Gurney Flap

Straight-blade Darrieus vertical axis wind turbines are used as medium and small size wind turbine because of higher power output in vertical axis wind turbine (VAWT). In our previous study, the relationship between the performance and Reynolds number based on airfoil chord length had been investigated by using small-scale test models of lift-type VAWT, and the results showed that the performance of tested wind turbine models with small diameter was clearly lower than that of the large-scale field test machine, and its performance also varies significantly with the blade pitch angle. In this study, we focused on the performance of a small-scale straight-blade Darrieus VAWT, the relationship among the blade airfoil camber direction and the pitch angle, and the performance of the small-scale VAWT was examined experimentally by using a small-scale VAWT test model with Gurney flap which was a small flat plate. Gurney flaps with its height h, as a ratio to the blade chord length c, h/c = 0.036 to 0.055, were attached to the blades of the VAWT test model, in addition, the attaching direction of the Gurney flap on the blade was examined for both inward and outward of the rotor, and the pitch angle was also examined for a range of −5 to 10 degrees. These results are discussed comparing with the result of the VAWT without Gurney flap and considering the numerical results for the single blade with/without the Gurney flap. The results showed that the performance of the tested VAWT was reversed between the inward and outward Gurney flaps around a pitch angle of 10 degrees. That is, the inward Gurney flap was superior at a pitch angle of less than 10 degrees, while the outward Gurney flap was effective at a pitch angle of more than 10 degrees. Furthermore, for the tested small-scale VAWT model, the optimum pitch angle was about 5 degrees, and the inward and shorter Gurney flap showed higher power performance of the VAWT under this pitch angle condition.

Large eddy simulations of wind turbine wakes in typical complex topographies

AbstractThere is a need to clarify the coupling characteristics of terrain‐induced wind fields and wind turbine‐induced wake in wind farm micrositing. However, research investigating the effect of hill shape on this interaction is lacking. In addition, during the optimization of the layout of the turbines over topographies, the flow behind the turbines should be predicted in a fast way. After obtaining the wake flow of the turbine mounted on flat terrain and the flow over the topographies, there are mainly two superposition methods to predict the turbine wake flow over the topographies. One is to add the wind deficit following the location with a vertical distance of the hub height (D‐line). The other is to add the wind deficit following the streamline starting from the turbine center (B‐line). It remains unknown to what extent these two superposition methods can be adopted. Therefore, the effects of hill shape, wind turbine size, and turbine location are investigated. When the wind deficit, obtained from modeling the wake flow of the turbine mounted on flat terrain, is superposed following B‐line, the results are overall better than those when following D‐line.

Deterministic and probabilistic multi-objective placement and sizing of wind renewable energy sources using improved spotted hyena optimizer

In this paper, deterministic and probabilistic optimal placement and sizing of wind turbines (WTs) in distribution networks are investigated with two objectives: reducing loss and improving voltage profile and stability index. A new improved meta-heuristic method, named β-chaotic sequence spotted hyena optimizer, is proposed to determine the optimal size and location of wind turbines. The proposed method is implemented on IEEE 33-bus and 69-bus radial distribution networks. The performance of the method is verified with finding the optimal location and size of WTs, which exhibited lower power loss and better minimum voltage and voltage stability index with more convergence speed in comparison with the conventional spotted hyena optimizer and particle swarm optimization, and previous studies. Additionally, the probabilistic placement and sizing of WTs are implemented considering the uncertainty of wind generation and the network demand based on Monte Carlo simulation. The results showed that losses increased, the voltage profile weakened, and the voltage stability index was reduced, compared with the deterministic method. For 33 bus network, the loss, minimum voltage, and voltage stability index in two WTs application are recorded as 28.79 kW, 0.9811, and 31.12 p. u, respectively, using the deterministic method, while the values of 34.56 kW, 0.9789, and 30.72 p. u are recorded using the probabilistic method. On the other hand, for 69 bus network, these values are recorded as 18.60 kW, 0.9833, and 67.13 p. u using the deterministic method, and 29.36 kW, 0.9794, and 65.62 p. u using the probabilistic method. Therefore, the resultsclearly show that the probabilistic method is more realistic and accurate than the deterministic method due to consideration of load and wind generation intrinsic changes with all possible probabilities, based on which the network operators can have a more accurate view of the impact of renewable resources on the network characteristics, hence making better decisions to improve them.

Determining the size and location of variable speed wind turbines for reducing power losses and improving voltage profile

Due to the voltage level and current of feeders in distribution systems, power loss is high in such networks. With the proliferation of distributed generations, it has become more important to determine their location and rating. These goals can be obtained according to different purposes such as improving the voltage profile. Unlike fixed speed wind turbines, the variable speed type can produce or absorb the reactive power. Hence, this paper specifies the placement and sizing of variable speed wind turbines based on a multi-objective function and according to the reactive power management. In the first step, the variable speed wind turbine is modeled by using the practical curve and Levenberg–Marquardt algorithm and then, the objective functions are optimized simultaneously to achieve the locations and sizes. Also, the impact of wind speed uncertainty on the functions is evaluated. To validate the results, a comparison between variable speed and fixed speed wind turbines is also presented. The proposed model is implemented on an IEEE 33-bus standard test system and the results show a significant (42%) decrease in power loss by adding variable speed wind turbines. However, the investment cost is also increased. Moreover, with considering the uncertainty, power loss and investment cost are increased by about 8% and 15%, respectively. However, the robustness of the system is enhanced against the wind speed fluctuations.

How loud is the underwater noise from operating offshore wind turbines?

Offshore wind turbines are increasingly abundant sources of underwater low frequency noise. This increase raises concern for the cumulative contribution of wind farms to the underwater soundscape and possible impact on marine ecosystems. Here, available measurements of underwater noise from different wind turbines during operation are reviewed to show that source levels are at least 10-20 dB lower than ship noise in the same frequency range. The most important factor explaining the measured sound pressure levels from wind turbines is distance to the turbines with smaller effects of wind speed and turbine size. A simple multi-turbine model demonstrates that cumulative noise levels could be elevated up to a few kilometres from a wind farm under very low ambient noise conditions. In contrast, the noise is well below ambient levels unless it is very close to the individual turbines in locations with high ambient noise from shipping or high wind speeds. The rapid increase in the number and size of offshore wind farms means that the cumulative contribution from the many turbines may be considerable and should be included in assessments for maritime spatial planning purposes as well and environmental impact assessments of individual projects.

Optimal maintenance planning and resource allocation for wind farms based on non-dominated sorting genetic algorithm-ΙΙ

The complex structure and harsh working environment of wind turbines cause frequent failures and unavailability of these turbines in wind farms. To promote the long-term stable development of wind power and enhance its market competitiveness, the reduction of operation and maintenance costs is particularly important, which are estimated to account for approximately 1/3 of the total life cycle cost. With the continuous increase in the size and number of wind turbines, wind farm maintenance tasks and resources are increasing and becoming unpredictable. The realization of the dynamic scheduling of maintenance tasks and resources under various constraints has become vital. In this study, an optimal multi-objective model of maintenance planning and resource allocation for wind farms is established. The maintenance tasks are obtained according to the preset maintenance strategy and current operating status of the wind turbine components. The dynamic requirements of maintenance planning and resource allocation for different wind farms in adjacent areas are periodically generated, and the Non-dominated sorting genetic algorithm-ΙΙ (NSGA-ΙΙ) is adopted to conduct a combinatorial optimization process. The validity of the proposed model are verified by a corresponding case study, along with a comparative analysis with other optimization algorithms and a sensitivity study of different parameters.

Active flutter control of the wind turbines using double-pitched blades

Classical flutter of a wind turbine blade is a concerned issue to hinder the wind utilization to a large extent. Recent predictions showed a decreasing flutter margin (the ratio of flutter speed to rated rotor speed) with the increase in wind turbine size. To address this issue, a new blade configuration called the double-pitched blade is proposed and analytically investigated for its potential to enhance the flutter suppressing capability of modern large-size wind turbine blades. This new blade comprise an inner part and a tip part, where the tip part can rotate (or pitch) independently with respect to the inner part through a tip actuator commanded by a feedback control law. The aerodynamic loads of blade tip due to the actively controlled rotation of the tip part provide a torque on the inner part, which provides damping for the torsional mode of the wind turbine blade. The effectiveness of this new double-pitched blade for suppressing flutter is verified through a simulation study conducted on a 907-DOF aero-servo-elastic wind turbine model. Parametric studies are performed on two main design parameters, i.e. the length of the tip part and the associated chordwise location of tip shaft with respected to the blade cross section, and flutter control performance are obtained by numerical optimization process. Simulation results show the optimal length of tip part is around 3.3%of blade length, and the associated chordwise location of tip shaft is around 45%of chord length, the flutter amplitude of the conventional blade can be mitigated to around 4%using this double-pitched blade.

URANS simulations of a horizontal axis wind turbine under stall condition using Reynolds stress turbulence models

Over the last decade, a dramatic increase in the size of commercial wind turbines is noticeable. The optimal structural design and reliable fatigue-life prediction of these large-scale structures depend on the accurate modeling of the turbulent flow around the rotors. The present paper aims at extending the knowledge of the turbulent flow characteristics around horizontal axis wind turbines and assessing the performance of several URANS turbulence models, principally Reynolds stress turbulence (RST) models, in predicting the wind turbine aerodynamics under stall condition. The simulations are performed using the NREL phase VI wind turbine over a wide range of wind speeds. Three RST models and the linear and quadratic variants of the k−ω SST turbulence model are examined. The results demonstrate that the RST models generally provide more reliable predictions. An evaluation of the Boussinesq hypothesis questions the applicability of the turbulence models employing this hypothesis to the wind turbine aerodynamic problems. Finally, the elliptic blending RST model, which is one of the latest formulations of the RST models, appears to provide the best trade-off between accuracy and computational cost.

How accurate is a machine learning-based wind speed extrapolation under a round-robin approach?

As the size of commercial wind turbines keeps increasing, having accurate ways to vertically extrapolate wind speed is essential to obtain a precise characterization of the wind resource for wind energy production. Recently, machine learning has been proposed and applied to extrapolate wind speed to hub heights. However, previous studies trained and tested the machine learning methods at the same site, giving them an unfair advantage over the conventional extrapolation techniques, which are instead more universal. Here, we use data from four sites in Oklahoma to test a round-robin validation approach for machine learning, under which we train a random forest at a site, and test it at a different site, where the model has no prior knowledge of the wind resource. We quantify how the accuracy of this technique varies with distance from the training site, and we find that it outperforms conventional techniques for wind extrapolation at all the considered spatial separations. We then assess how the accuracy of the machine-learning based approach varies when it is used to predict wind speed in a wind farm far wake. Finally, we explore as case study the performance of the random forest in extrapolating winds during a low-level jet event.

Fluid scaling laws of idealized wind farm simulations

Utilizing fluid scaling laws of idealized wind farm and wind resource simulations can reduce the computational effort and increase the understanding of the corresponding numerical model. However, not all fluid scaling laws are fully appreciated in the wind energy community. In this work, we employ dimensional analysis and Reynolds-averaged Navier-Stokes simulations of interacting wind turbine wakes and a Gaussian hill, and large-eddy simulations of a single wind turbine, to show that idealized wind farm simulations including terrain, subjected to a non-neutral atmospheric surface layer following Monin-Obukhov Similarity Theory, are independent of the inflow wind speed and wind turbine size due to Reynolds number similarity.

Repetitive Individual Pitch Control for Load Alleviation at Variable Rotor Speed

In recent years, wind turbines have been growing in size and became more lightweight and thus more flexible. Spatial variation in the wind speed results in asymmetrical blade loads, which include a periodic component increasing with growing wind turbine size. Asymmetrical blade loads can be reduced by individual blade pitch control in general and repetitive control can reduce especially the periodical parts of the loads. We investigate, how a repetitive control based individual blade pitch controller as extension to an existing collective pitch controller can reduce periodical loads resulting from unsteady non-uniform wind conditions under consideration of variable rotor speeds. As plant, we use a simulation model of a 3 MW wind turbine, developed by W2E Wind to Energy GmbH, and control it with a model predictive collective pitch controller. This controller is extended with the proposed repetitive individual pitch control scheme. This study shows, that the presented repetitive controller reduces especially the tower yaw moments by up to 65% and higher harmonics of the blade root moments by up to 30% at the cost of increased pitch activity. Hence, for the use of this controller one has to balance the load reduction of blades and tower with increased loads of the pitch actuators.

Meta-heuristic matrix moth–flame algorithm for optimal reconfiguration of distribution networks and placement of solar and wind renewable sources considering reliability

Abstract This paper presents optimal multi-criteria reconfiguration of radial distribution systems with solar and wind renewable energy sources using the weight factor method while considering reliability. Minimizing the power loss, improving the voltage profile and stability of the system, as well as, enhancing the reliability are the main objective functions of the problem to address. The reliability index is assumed as the energy not-supplied (ENS) of the end-users. Optimized variables of the problem include opened lines of the system in the reconfiguration process to maintain the radial structure of the network along with finding the optimal place and size of photovoltaic (PV) systems and wind turbine (WT) units in the distribution system, which are determined based on a new meta-heuristic called moth–flame optimization (MFO) algorithm. Simulations for different scenarios are performed utilizing reconfiguration and placement of renewable sources on an IEEE 33-bus radial distribution system. Obtained results in solving the problem indicate the superiority of the presented method compared with some methods in the literature. Furthermore, the results showed that the combined method as the reconfiguration and WT placement simultaneously bring the best performance for the network with lower power loss, improved voltage profile and stability, and enhanced reliability. Moreover, the results showed that considering reliability helps significantly reduce the energy not-supplied of the customers and supply their maximum load demand.

Fabrication of small size wind turbine and studying its characterization

Wind energy is one of the renewable energies. the horizontal axis wind turbine (HAWT) fabricated in Iraq Tikrit, the system operating at low speeds. The characteristics of the two and three blade turbine are comparing. the results for best performance, We found that when used three-blade increasing the output power of the system, so when using two blades, the power (314.1 W) and the number of cycles (62.1) at wind speed (6.6 m/s), and also when using three blades, the power (354.40 W) and the number of cycles (67.9) at the same Wind speed.

Mechanical performance of carbon-glass hybrid composite joints in quasi-static tension and tension-tension fatigue

The ever increasing size of wind turbines has given rise to a need for robust glass to carbon joint designs. This study investigates the effect of different ply layups on the static and fatigue behaviour of hybrid glass/carbon fibre composite joints. Uni-directional carbon fibre prepreg was co-cured to 8H glass prepreg using an overlap to thickness ratio of 20:1, where four joint designs were examined: scarf, interleaving and two forms of double scarf. The joints were tested statically in uniaxial tension and dynamically in tension-tension fatigue. Finite element analysis has been performed to provide insight into stress distributions within each joint. The double scarf joint (with glass on the outside) was found to perform best in fatigue and static tension, while the interleaving joint performed second best in fatigue in static tension but poorest in fatigue. For joint designs that will be used under highly stressed cyclic loading conditions, the current study indicates that static tests alone are a poor indicator of the joint performance and fatigue tests are required.

The hidden value of large-rotor, tall-tower wind turbines in the United States

The significant upscaling of wind turbine size (nameplate capacity, rotor diameter, and tower height) has, to date, been driven primarily by a goal of minimizing the levelized cost of energy. But with wind’s levelized cost of energy now comparable with that of other generating resources, other design considerations besides cost-minimization have grown in importance—particularly as wind’s increasing market penetration begins to impose challenges on the electric grid. We find that taller towers and larger rotors (relative to nameplate capacity) can enhance the value of wind energy to the electricity system and provide other “hidden” benefits. Specifically, in regions where wind penetration has reached around 20%, we find a boost in wholesale market value of US$2–US$3/MWh. This is augmented by transmission, balancing, and financing benefits that sum to roughly US$2/MWh. The aggregate potential value enhancement of US$4–US$5/MWh is comparable with a 10%–15% reduction in levelized costs.

Behavioral Evaluation of Modular ICH RC Columns through Quasi-Static Cyclic Tests

Owing to the recent expansion in sizes of wind turbines, the required height for the wind turbine tower is increasing. Therefore, new types of structures are needed to fulfill this requirement. In this study, a modular Internally Confined Hollow Reinforced Concrete (ICH RC) column was suggested for a wind power tower, and quasi-static test was performed to evaluate its bending performance. One single body specimen (SP-S) and two modular specimens (SP-MP, SP-MF) applying different connection methods were fabricated. The specimens were designed and manufactured while considering the numerical analysis and conditions of the testing laboratory. The test was conducted by controlling the displacement according to the drift ratio. The experimental results of moments, lateral loads, displacements, dissipation energy, ductility, etc. for each specimen were compared with those of numerical modeling. Consequently, plastic hinges were found at the bottom of the column and connection part for SP-S and modular specimens, respectively, which is due to the rigidity change at the connection of the modular specimens. Therefore, the result of energy dissipation was 40% higher in the case of the modular specimens than that of SP-S whereas the lateral force and moment in the case of the modular specimens were smaller than those of SP-S. In terms of displacement and energy ductility, modular specimens exhibited 50% higher results than those of SP-S. For the future work, it is necessary to enhance the performance of the connection part to apply the modular ICH RC structure to a wind turbine tower.

Dynamic modelling and thermoeconomic analysis of micro wind turbines and building integrated photovoltaic panels

During the past few years a significant effort has been performed in order to promote the use of renewable energy sources. However, one of the main barriers for a mature commercialization is due to the unpredictability of the renewable power production, mainly in case of wind and solar energy. Unfortunately, electric storage devices are often poorly profitable. Therefore, some more stable renewable energy systems must be designed. In this framework, this paper presents a novel hybrid renewable system consisting of Building Integrated PhotoVoltaic panels and small-scale Wind Turbines and double-stage heat pumps. This combination is very promising since it reduces the typical fluctuations of solar or wind systems, achieving a more stable profile of the overall power production. A detailed dynamic simulation model is developed in TRNSYS environment, including validated models for all the components and a suitable thermoeconomic analysis. A case study is implemented for a hotel building, where the space heating and cooling energy is supplied by an electrically driven reversible air-to-water Heat Pump, supplied by the electricity produced by Building Integrated PhotoVoltaic panels and Wind Turbines. the thermal energy recovered from the HP desuperheater is coupled with the thermal energy produced by a two-stage cascade cycle Heat Pump to produce domestic hot water. Results are presented in terms of hourly, monthly and yearly system performance data as well as by discussing the results of a detailed sensitivity analysis performed to detect the optimum configuration and weather zone of this hybrid renewable system. An analysis of the building envelope features is also performed, according to the nearly zero energy buildings target. Results showed that the combination of photovoltaic and wind technologies allows one to significantly enhance the stability of the renewable power production. Results also show that the use of heat pumps leads to a reduction of the primary energy demand for building space heating/cooling and domestic hot water by 30%. A payback period of about 5.2 years is obtained and the optimum configuration suggests adopting one 20 kW Wind Turbine for the selected case study. • Building integrated photovoltaic panels coupled with small size wind turbines. • Dynamic simulation model developed with TRNSYS software. • Sensitivity analysis on the building envelope features and weather zones. • Simple payback period of about 4.4 years for two 20 kW wind turbines.

Underwater Noise Emission Due to Offshore Pile Installation: A Review

The growing demand for renewable energy supply stimulates a drastic increase in the deployment rate of offshore wind energy. Offshore wind power generators are usually supported by large foundation piles that are driven into the seabed with hydraulic impact hammers or vibratory devices. The pile installation process, which is key to the construction of every new wind farm, is hindered by a serious by-product: the underwater noise pollution. This paper presents a comprehensive review of the state-of-the-art computational methods to predict the underwater noise emission by the installation of foundation piles offshore including the available noise mitigation strategies. Future challenges in the field are identified under the prism of the ever-increasing size of wind turbines and the emerging pile driving technologies.

A comprehensive techno-economic analysis for optimally placed wind farms

Wind power project development investment is based on the separate technical and financial analyses. Based on the actual wind data, data-based wind distribution map and wake effect model, a combined techno-economic analysis is proposed in this paper. Starting from deriving the wind distribution map, a comprehensive analysis extending to the feasibility assessment of the project is presented here. The problem is formulated as the maximization of net present value of the project subject to the specified initial investment cost within a fixed area and turbine spacing constraints. Simultaneous optimization of the wind turbine size, hub height and placement is realized with BPSO-TVAC. Sensitivity analysis and Monte Carlo simulation are used to investigate the feasibility of the project, against various parameters, imposed on by the techno-economic constraints. Hypothesis testing with a confidence level of 99.99% corroborates the results obtained from Monte Carlo simulation. With scenario analysis, a positive NPV is identified even in the worst-case scenario, an attractive trait for investors. An ideal decision-making tool considering technical efficiency and profitability simultaneously is presented.