Do we really need rotor equivalent wind speed?

The use of the rotor equivalent wind speed for determination of power curves and annual energy production for wind turbines is advocated in the second edition of the IEC 61400‐12‐1 standard. This requires the measurements of wind speeds at different heights, for which remote sensing equipment is recommended in addition to meteorological masts. In this paper, we present a theoretical analysis that shows that the relevance of the rotor equivalent wind speed method depends on turbine dimensions and wind shear regime. For situations where the ratio of rotor diameter and hub height is smaller than 1.8, the rotor equivalent wind speed method is not needed if the wind shear coefficient at the location of the wind turbine has a constant value between ?0.05 and 0.4: in these cases, the rotor equivalent wind speed and the wind speed at hub height are within 1%. For complex terrains with high wind shear deviations are larger. The effect of non‐constant wind shear exponent, ie, different wind shear coefficients for lower and upper half of the rotor swept area especially at offshore conditions is limited to also about 1%.     

Wind turbine generator trends for site‐specific tailoring

Turbine optimization for specific wind regimes and climate conditions is becoming more common as the market expands into new territories (offshore, low‐wind regimes) and as technology matures. Tailoring turbines for specific sites by varying rotor diameter, tower height and power electronics may be a viable technique to make wind energy more economic and less intermittent. By better understanding the wind resource trends and evaluating important wind turbine performance parameters such as specific power (ratio of rated power and rotor swept area), developers and operators can optimize plant output and better anticipate operational impacts. This article presents a methodology to evaluate site‐specific wind data for turbine tailoring. Wind characteristics for the Tehachapi wind resource area in California were utilized for this study. These data were used to evaluate the performance of a range of wind turbine configurations. The goal was to analyse the variations in wind power output for the area, assess the changes in these levels with the time of day and season and determine how turbine configuration affects the output. Wind turbine output was compared with California statewide system electrical demand to evaluate the correlation of the wind resource site with local peak demand loads. A comparison of the commercial value of electricity and corresponding wind generation is also presented using a time‐dependent valuation methodology. Copyright © 2005 John Wiley & Sons, Ltd.     

Technological evolution of onshore wind turbines—a market‐based analysis

Wind energy technology is evolving towards larger machines (longer blades, taller towers and more powerful generators). Scaling up wind turbines is a challenging task, which requires innovative solutions as well as new configurations and designs. The size of wind turbines (in terms of rotor diameter, hub height and rated power) has increased extraordinary from 30 m rotor diameter, 30 m of hub height and 300 kW rated power, usual in the late 1980s, to 92.7 m rotor diameter, 87.7 m of height and 2.1 MW on average at the end of 2014. However, technological evolution has not only been focused on the scaling up process but also on developing innovative solutions that minimize costs at the same time as they deal with aspects of different nature, such as grid code requirements, reliability, quality of the wind resource or prices and availability of certain commodities, among others. This paper analyses the evolution of wind technology from a market‐based perspective by identifying trends in the most relevant technological indicators at the same time as stressing the key differentiating aspects between regions/markets. Evolution and trends in indicators such as rated power, rotor diameter, hub height, specific power, wind class, drive train configuration and power control systems are presented and analysed, showing an intense and fast technological development, which is enabling wind energy to reduce costs and becoming increasingly more competitive with conventional fuel‐based generating technologies. © 2016 The Authors Wind Energy Published by John Wiley & Sons Ltd.     

Technology effects in repowering wind turbines

This research investigates, analyses, and quantifies the technological effects of wind turbine repowering (ie, where old turbines are removed and new turbines are installed at the same or a very close location, including the enhanced performance in energy production). In these cases, it is assumed that both old and new turbines are subject to the same wind regime, other than because of technological elements, such as hub height, and thus it is possible to isolate the effects of new technology from the effect of changing local wind conditions. This research is based on the analysis of empirical data on repowering turbines in Denmark and Germany, and on historical production data available for the Danish component of the data set. Technological innovations are expected to enable new wind turbines to capture more energy at the repowering site, mostly through larger rotors and higher hub heights, and this is what this study has analysed. The results show that new turbines in repowering projects are twice as high, have three times the rotor diameter, nine times the swept area, six times the nominal power, and nine times as much electricity as the old turbines. However, the most significant improvement is probably the increase of capacity factor of 7.1% on a per‐turbine basis, or 9.7% on a per‐production basis.     

Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind

For region‐2 operation of wind turbines in practice, the optimal torque gain can deviate from the nominal value because of the variations in turbine and wind conditions. The extremum‐seeking control (ESC) has shown its potential as a model‐free region‐2 control solution in some recent work; however, the ESC with rotor power feedback suffers from undesirable convergence under fluctuating wind. In this paper, we propose to use an estimated power coefficient as the objective function for the torque‐gain ESC, where the hub‐height free‐stream wind speed (FSWS) is estimated with the nacelle anemometer measurement on the basis of the so‐called nacelle transfer function (NTF) between the nacelle anemometer and met‐tower measurement. A sensitivity analysis is performed to quantify the impact of the wind speed estimation error on the estimation of power coefficient. An ESC integrated interregion switching scheme is proposed to avoid the load increase. Simulation results show that, compared with the power feedback‐based ESC, the proposed method can greatly improve the convergence rate of ESC under fluctuating wind, even under relatively large wind speed estimation error. Evaluation for the fatigue loads of wind turbine shows that the proposed control strategy induces mild increase of the wind turbine load.     

Large eddy simulations of the effect of vertical staggering in large wind farms

In order to study the effect of vertical staggering in large wind farms, large eddy simulations (LES) of large wind farms with a regular turbine layout aligned with the given wind direction were conducted. In the simulations, we varied the hub heights of consecutive downstream rows to create vertically staggered wind farms. We analysed the effect of streamwise and spanwise turbine spacing, the wind farm layout, the turbine rotor diameter, and hub height difference between consecutive downstream turbine rows on the average power output. We find that vertical staggering significantly increases the power production in the entrance region of large wind farms and is more effective when the streamwise turbine spacing and turbine diameter are smaller. Surprisingly, vertical staggering does not significantly improve the power production in the fully developed regime of the wind farm. The reason is that the downward vertical kinetic energy flux, which brings high velocity fluid from above the wind farm towards the hub height plane, does not increase due to vertical staggering. Thus, the shorter wind turbines are effectively sheltered from the atmospheric flow above the wind farm that supplies the energy, which limits the benefit of vertical staggering. In some cases, a vertically staggered wind farm even produced less power than the corresponding non vertically staggered reference wind farm. In such cases, the production of shorter turbines is significantly negatively impacted while the production of the taller turbine is only increased marginally.     

实度对低风速风电机组风轮气动性能影响研究

为提高低风速地区的风能利用率,研究风轮实度对低风速风电机组气动性能的影响。考虑影响风轮实度因素（叶片数量、弦长及安装角）,设计2组不同弦长叶片与可调安装角轮毂。安装角改变时不仅会引起实度变化,还会使叶尖速比发生改变。通过车载试验验证安装角不同时对风轮气动性能的影响主要与叶尖速比相关。根据不同风轮表面压力分布数值模拟结果得出：相同风速下,弦长由叶根到叶尖逐渐增大的叶片更易启动。相同条件下,试验机组输出功率与数值模拟机组输出功率最大相差5.37%,说明数值模拟结果可信。随着风轮实度的增加,风速5 m/s时,其风能利用系数呈增大趋势,风速8 m/s时,其风能利用系数呈减小趋势,两趋势相交时实度为25.38%,得出该实度下风轮气动性能较优,即可得到适合低风速地区的风轮实度。     

Modeling of the dynamics of wind to power conversion including high wind speed behavior

This paper proposes and validates an efficient, generic and computationally simple dynamic model for the conversion of the wind speed at hub height into the electrical power by a wind turbine. This proposed wind turbine model was developed as a first step to simulate wind power time series for power system studies. This paper focuses on describing and validating the single wind turbine model, and is therefore neither describing wind speed modeling nor aggregation of contributions from a whole wind farm or a power system area. The state‐of‐the‐art is to use static power curves for the purpose of power system studies, but the idea of the proposed wind turbine model is to include the main dynamic effects in order to have a better representation of the fluctuations in the output power and of the fast power ramping especially because of high wind speed shutdowns of the wind turbine. The high wind speed shutdowns and restarts are represented as on–off switching rules that govern the output of the wind turbine at extreme wind speed conditions. The model uses the concept of equivalent wind speed, estimated from the single point (hub height) wind speed using a second‐order dynamic filter that is derived from an admittance function. The equivalent wind speed is a representation of the averaging of the wind speeds over the wind turbine rotor plane and is used as input to the static power curve to get the output power. The proposed wind turbine model is validated for the whole operating range using measurements available from the DONG Energy offshore wind farm Horns Rev 2. Copyright © 2015 John Wiley & Sons, Ltd.     

Wind turbine partial wake merging description and quantification

Individual turbine location within a wind plant defines the flow characterisitcs experienced by a given turbine. Irregular turbine arrays and inflow misalignment can reduce plant efficiency by producing highly asymmetric wakes with enhanced downstream longevity. Changes in wake dynamics as a result of turbine position were quantified in a wind tunnel experiment. Scale model turbines with a rotor diameter of 20 cm and a hub height of 24 cm were placed in symmetric, asymmetric, and rotated configurations. Simultaneous hub height velocity measurements were recorded at 11 spanwise locations for three distances downstream of the turbine array under two inflow conditions. Wake interactions are described in terms of the time‐average streamwise velocity and turbulence intensity as well as the displacement, momentum, and energy thicknesses. The effects of wake merging on power generation are quantified, and the two‐point correlation is used to examine symmetry in the mean velocity between wakes. The results indicate that both asymmetric and rotated wind plant arrangements can produce long‐lasting wakes. At shallow angles, rotated configurations compound the effects of asymmetric arrangements and greatly increase downstream wake persistence.     

Accounting for the speed shear in wind turbine power performance measurement

The current IEC standard for wind turbine power performance measurement only requires measurement of the wind speed at hub height assuming this wind speed to be representative for the whole rotor swept area. However, the power output of a wind turbine depends on the kinetic energy flux, which itself depends on the wind speed profile, especially for large turbines. Therefore, it is important to characterize the wind profile in front of the turbine, and this should be preferably achieved by measuring the wind speed over the vertical range between lower and higher rotor tips. In this paper, we describe an experiment in which wind speed profiles were measured in front of a multimegawatt turbine using a ground–based pulsed lidar. Ignoring the vertical shear was shown to overestimate the kinetic energy flux of these profiles, in particular for those deviating significantly from a power law profile. As a consequence, the power curve obtained for these deviant profiles was different from that obtained for the ‘near power law’ profiles. An equivalent wind speed based on the kinetic energy derived from the measured wind speed profile was then used to plot the performance curves. The curves obtained for the two kinds of profiles were very similar, corresponding to a significant reduction of the scatter for an undivided data set. This new method for power curve measurement results in a power curve less sensitive to shear. It is therefore expected to eventually reduce the power curve measurement uncertainty and improve the annual energy production estimation. Copyright © 2011 John Wiley & Sons, Ltd.     

Simulating Feedback Linearization control of wind turbines using high‐order models

As wind turbines are becoming larger, wind turbine control must now encompass load control objectives as well as power and speed control to achieve a low cost of energy. Due to the inherent non‐linearities in a wind turbine system, the use of non‐linear model‐based controllers has the potential to increase control performance. A non‐linear feedback linearization controller with an Extended Kalman Filter is successfully used to control a FAST model of the controls advanced research turbine with active blade, tower and drive‐train dynamics in above rated wind conditions. The controller exhibits reductions in low speed shaft fatigue damage equivalent loads, power regulation and speed regulation when compared to a Gain Scheduled Proportional Integral controller, designed for speed regulation alone. The feedback linearization controller shows better rotor speed regulation than a Linear Quadratic Regulator (LQR) at close to rated wind speeds, but poorer rotor speed regulation at higher wind speeds. This is due to modeling inaccuracies and the addition of unmodeled dynamics during simulation. Similar performance between the feedback linearization controller and the LQR in reducing drive‐train fatigue damage and power regulation is observed. Improvements in control performance may be achieved through increasing the accuracy of the non‐linear model used for controller design. Copyright © 2009 John Wiley & Sons, Ltd.     

双馈风力发电系统的最大风能控制策略

在分析变速恒频风力发电系统最大风能捕获策略的基础上,提出了一种通过直接控制双馈发电机转子电流就可实现系统低于额定风速下的最大风能捕获又可使得电机铜耗最小化运行的控制策略.首先,在考虑风力机特性和双馈发电机基本电磁关系的基础上,分别推导了双馈发电机定子铜耗最小化运行和最大风能捕获的数学模型.其次,根据双馈发电机最优转子电流的数学模型,建立了双馈风力发电机系统最大风能捕获的控制策略.最后,利用Matlab/Simulink对不同风速下双馈发电机系统的运行性能进行了分析和比较,结果验证了该控制策略的正确性和可行性.     

Testing basic performance of a very small wind turbine designed for multi-purposes

A very small wind turbine system for multi-purposes was developed and its performance was reported in this paper. The rotor diameter of the turbine is 500 mm. The tests of the energy output, turbine speed, power coefficient, and torque of turbine were carried out for a wide rage of free stream velocity. The flow around the wind turbine and the influence of the turbulence were investigated with a particle image velocimetry. Experimentally obtained power coefficient was 0.4 in maximum and 0.36 in the rated running condition, respectively. The tip speed ratio corresponding to the optimum driving condition was 2.7. Comparing with the other commercial turbines, the performance was excellent at a slow turbine speed. By the flow visualization and PIV measurement around the wind turbine, the approaching flow velocity and the accelerated flow field passing the blade tip was obtained. It was confirmed that the actual flow passed through the blades was about 20% slower than the ideal flow. Tip vortex shed from the blade tip was also visualized clearly.     

Exploring the benefits of vertically staggered wind farms: Understanding the power generation mechanisms of turbines operating at different scales

Wind farms are known to modulate large scale structures in and around the wake regions of the turbines. The potential benefits of placing small hub height, small rotor turbines in between the large turbines in a wind farm to take advantage of such modulated large‐scale eddies are explored using large eddy simulation (LES). The study has been carried out in an infinite wind farm framework invoking an asymptotic limit, and the wind turbines are modeled using an actuator line model. The vertically staggered wind turbine arrangements that are studied in the present work consist of rows of large wind turbines, with rows of smaller wind turbines (ie, smaller rotor size and shorter hub height) placed in between the rows of large turbines. The influence of the hub height of the small turbines, in particular, how it affects the interactions between the large and small turbines and consequently their power, along with the multiscale dynamics involved, has been assessed in the current study. It was found that, in the multiscale layouts, the small turbines at lower hub heights operate more efficiently than their homogeneous single‐scale counterparts. In contrast, the small turbines with higher hub heights incur a loss of power compared with the corresponding single‐scale arrangements.     

新型双风轮风力机气动特性的三维流场数值模拟

基于Simplic算法,采用SST κ-ω湍流模型,利用Fluent6．3数值模拟软件对新型的小型双风轮风力机的气动特性进行了三维流场研究,并与同规格单风轮风力机的三维流场进行了比较．结果表明：与单风轮风力机相比,随着后风轮叶片数目的增加,新型双风轮风力机的湍流强度变大,风力机运行的稳定性在一定程度上有所降低;当后风轮的叶片数目合理时,后风轮对前风轮的影响较小,且可以有效地捕捉到前风轮的漏风,使得新型双风轮风力机的风轮在获得较大迎风面积的同时可以保持较高的转速,进而能够高效地实现风能的两级利用,明显提高发电功率和增大风能利用系数．     

Wind turbine rotor imbalance detection using nacelle and blade measurements

Wind power is the world's fastest growing renewable energy source, but operations and maintenance costs are still a major obstacle toward reliability and widescale adoption of wind power, accounting for a large part of the cost of energy for offshore installations. Structural health monitoring systems have been proposed for implementing condition‐based maintenance. The wind energy industry currently uses condition monitoring systems that are mostly adapted from roating machinery in other power generation industries. However, these systems have had limited effectiveness on wind turbines because of their atypical operating conditions, which are characterized by low and variable rotational speed, rapidly varying torque, extremely large rotors and stochastic loading from the wind. Although existing systems primarily take measurements from the nacelle, valuable information can be extracted from the structural dynamic response of the rotor blades to mitigate potentially damaging loading conditions. One such condition is rotor imbalance, which not only reduces the aerodynamic efficiency of the turbine and therefore its power output but can also lead to very large increases in loading on the drivetrain, blades and tower. The National Renewable Energy Laboratory's fast software was used to model both mass and aerodynamic imbalance in a 5 MW offshore wind turbine. It is shown that a combination of blade and nacelle measurements, most of which can be obtained from standard instrumentation already found on utility‐scale wind turbines, can be formulated into an algorithm used to detect and locate imbalance. The method described herein allows for imbalance detection that is potentially more sensitive than existing on‐line systems, while taking advantage of sensors that are already in place on many utility‐scale wind turbines. Copyright © 2014 John Wiley & Sons, Ltd.     

Simulation of wind turbine wake interaction using the vorticity transport model

The aerodynamic interactions that can occur within a wind farm can result in the constituent turbines generating a lower power output than would be possible if each of the turbines were operated in isolation. Tightening of the constraints on the siting of wind farms is likely to increase the scale of the problem in the future. The aerodynamic performance of turbine rotors and the mechanisms that couple the fluid dynamics of multiple rotors can be most readily understood by simplifying the problem and considering the interaction between only two rotors. The aerodynamic interaction between two rotors in both co‐axial and offset configurations has been simulated using the Vorticity Transport Model. The aerodynamic interaction is a function of the tip speed ratio, and both the streamwise and crosswind separation between the rotors. The simulations show that the momentum deficit at a turbine operating within the wake developed by the rotor of a second turbine is governed by the development of instabilities within the wake of the upwind rotor, and the ensuing structure of the wake as it impinges on the downwind rotor. If the wind farm configuration or wind conditions are such that a turbine rotor is subject to partial impingement by the wake produced by an upstream turbine, then significant unsteadiness in the aerodynamic loading on the rotor blades of the downwind turbine can result, and this unsteadiness can have considerable implications for the fatigue life of the blade structure and rotor hub. Copyright © 2009 John Wiley & Sons, Ltd.     

Can synoptic drivers explain rotor-area wind conditions and predict energy output?

Synoptic-scale weather patterns are an important driver of wind speed at turbine hub height, but wind energy generation is also affected by the wind profile across the rotor. In this research, we use a 6-year record of hourly profile measurements at the Eolos Wind Research Station in Minnesota, USA, to investigate whether synoptic weather patterns can provide information about rotor-area characteristics in addition to hub-height wind speed. We use sea level pressure data from the MERRA-2 reanalysis to classify synoptic patterns at the Eolos site into 15 synoptic types and use the Eolos wind profile data to create mean hourly and mean monthly values of wind speed and turbulence intensity at hub height (80 m), and wind speed shear, wind direction shear, and the potential temperature gradient across the rotor (30–129 m), for each synoptic type. Using a simple linear regression model, we find that, at monthly time scales, wind speed, turbulence intensity, and wind speed shear across the rotor are the most important variables for predicting monthly wind energy output from the Eolos turbine. Regression models using the original Eolos data and the derived synoptic types capture about 64% and 55% of the variance in monthly energy output, respectively. When fewer than the full 6 years of observations are used to fit the regression model, however, predictions using the synoptic types slightly outperform predictions using the Eolos observations. These results suggest that seasonal energy projections may be enhanced by incorporating wind profile measurements with synoptic-scale drivers.     

The influence of the wind speed profile on wind turbine performance measurements

To identify the influence of wind shear and turbulence on wind turbine performance, flat terrain wind profiles are analysed up to a height of 160 m. The profiles' shapes are found to extend from no shear to high wind shear, and on many occasions, local maxima within the profiles are also observed. Assuming a certain turbine hub height, the profiles with hub‐height wind speeds between 6 m s^?1 and 8 m s^?1 are normalized at 7 m s^?1 and grouped to a number of mean shear profiles. The energy in the profiles varies considerably for the same hub‐height wind speed. These profiles are then used as input to a Blade Element Momentum model that simulates the Siemens 3.6 MW wind turbine. The analysis is carried out as time series simulations where the electrical power is the primary characterization parameter. The results of the simulations indicate that wind speed measurements at different heights over the swept rotor area would allow the determination of the electrical power as a function of an ‘equivalent wind speed’ where wind shear and turbulence intensity are taken into account. Electrical power is found to correlate significantly better to the equivalent wind speed than to the single point hub‐height wind speed. Copyright © 2008 John Wiley & Sons, Ltd.     

Investigation of wind turbine wake superposition models using Reynolds‐averaged Navier‐Stokes simulations

It is well accepted that the wakes created by upstream turbines significantly impact on the power production and fatigue loading of downstream turbines and that this phenomenon affects wind farm performance. Improving the understanding of wake effects and overall efficiency is critical for the optimisation of layout and operation of increasingly large wind farms. In the present work, the NREL 5‐MW reference turbine was simulated using blade element embedded Reynolds‐averaged Navier‐Stokes computations in sheared onset flow at three spatial configurations of two turbines at and above rated flow speed to evaluate the effects of wakes on turbine performance and subsequent wake development. Wake recovery downstream of the rearward turbine was enhanced due to the increased turbulence intensity in the wake, although in cases where the downstream turbine was laterally offset from the upstream turbine this resulted in relatively slower recovery. Three widely used wake superposition models were evaluated and compared with the simulated flow‐field data. It was found that when the freestream hub‐height flow speed was at the rated flow speed, the best performing wake superposition model varied depending according to the turbine array layout. However, above rated flow speed where the wake recovery distance is reduced, it was found that linear superposition of single turbine velocity deficits was the best performing model for all three spatial layouts studied.