A new semi-empirical wind turbine capacity factor for maximizing annual electricity and hydrogen production

The capacity factor is an important wind turbine parameter which is ratio of average output electrical power to rated electrical power of the wind turbine. Another main factor, the AEP, the annual energy production, can be determined using wind characteristics and wind turbine performance. Lower rated power may lead to higher capacity factor but will reduce the AEP. Therefore, it is important to consider simultaneously both the capacity factor and the AEP in design or selecting a wind turbine. In this work, a new semi-empirical secondary capacity factor is introduced for determining a rated wind speed at which yearly energy and hydrogen production obtain a maximum value. This capacity factor is expressed as ratio of the AEP for wind turbine to yearly wind energy delivered by mean wind speed at the rotor swept area. The methodology is demonstrated using the empirical efficiency curve of Vestas-80 2 MW turbine and the Weibull probability density function. Simultaneous use of the primary and the secondary capacity factors are discussed for maximizing electrical energy and hence hydrogen production for different wind classes and economic feasibility are scrutinized in several wind stations in Kuwait.     

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.     

双馈风力发电系统最大风能追踪控制

在分析风力机功率特性和DFIG运行特性的基础上,通过对双馈机转速控制进行最大风能追踪具体过程的深入研究,提出一种基于最大风能追踪的双馈电机有功、无功功率的解耦控制方法。建立了基于发电机定子磁链定向矢量控制的双馈风力发电系统最大风能追踪系统模型,并利用PSCAD／EMTDC对其进行仿真,结果验证了控制策略的正确性。     

低空急流条件下水平轴风力机风轮气动特性的研究

为阐明低空急流条件下风力机风轮的气动特性,基于工程化的边界层风速模型和Von Karman谱模型建立不同来流的脉动风场,对比研究低空急流条件下NREL 5 MW风力机风轮的输出功率和气动载荷的变化规律。结果表明:如果仅以轮毂高度处的风速作为风力机变桨控制的依据,与均匀来流和剪切来流相比较,低空急流条件下,虽然来流风功率明显增大,但风轮的输出功率在较高风速时反而减小;风轮所受的不平衡气动载荷,包括横向力、纵向力、偏航力矩和倾覆力矩在较高风速时小于剪切来流的结果;且仅以轮毂高度处的风速预测得到的风轮输出功率高于实际结果,其最大相对误差为89.4%。因此,低空急流条件下,为提高风能利用率和风轮输出功率的预测精度,应考虑不同高度位置处的风速大小对风力机进行变桨控制和功率预测。     

基于转子动能控制的风电机组功率平滑控制结构及优化策略研究

采用转子动能控制方法对直驱永磁同步风力发电机组输出的有功功率进行功率平滑控制,并对控制效果进行优化。首先,分析转子动能控制造成功率损失的原因,并据此提出一种能够补偿功率损失的平滑指令,结合风电机组稳定性分析,得到风电机组采用功率平滑控制的条件,以此采用Matlab/Simulink进行仿真分析,验证所提控制策略的有效性。然后,利用模糊逻辑控制算法（FLC）进行优化控制,以提高风电机组输出有功功率平滑度和风能利用率,并改善由于功率指令切换造成的平滑度下降问题。最后,通过Matlab/Simulink进行仿真分析,对比不同参数下的优化效果,验证所提控制策略和优化方法的有效性。     

双馈风力发电系统最大风能追踪控制的研究

在分析了风力机功率特性和DFIG运行特性的基础上,通过对双馈机转速控制进行最大风能追踪具体过程的深入研究,提出了一种基于最大风能追踪的双馈电机有功、无功功率的解耦控制方法。建立了基于发电机定子磁链定向矢量控制的双馈风力发电系统最大风能追踪系统模型,并利用PSCAD/EMTDC对其进行仿真,结果验证了控制策略的正确性。     

The concept of a smart wind turbine system

A smart wind turbine concept with variable length blades and an innovative hybrid mechanical-electrical power conversion system was analyzed. The variable length blade concept uses the idea of extending the turbine blades when wind speeds fall below rated level, hence increasing the swept area, and thus maintaining a relatively high power output. It is shown for a typical site, that the annual energy output of such a wind turbine that could double its blade length, could be twice that of a corresponding turbine with fixed length blades. From a cost analysis, it is shown that the concept would be feasible if the cost of the rotor could be kept less than 4.3 times the cost of a standard rotor with fixed length blades. Given the variable length blade turbine system exhibits a more-or-less linear maximum power curve, as opposed to a non-linear curve for the standard turbine, an innovative hybrid mechanical-electrical power conversion system was proposed and tested proving the feasibility of the concept.     

Comparison of the response of doubly fed and fixed-speed induction generator wind turbines to changes in network frequency

Synchronous and fixed-speed induction generators release the kinetic energy of their rotating mass when the power system frequency is reduced. In the case of doubly fed induction generator (DFIG)-based wind turbines, their control system operates to apply a restraining torque to the rotor according to a predetermined curve with respect to the rotor speed. This control system is not based on the power system frequency and there is negligible contribution to the inertia of the power system. A DFIG control system was modified to introduce inertia response to the DFIG wind turbine. Simulations were used to show that with the proposed control system, the DFIG wind turbine can supply considerably greater kinetic energy than a fixed-speed wind turbine.     

Power correlation for vertical axis wind turbines with varying geometries

In this paper, a new predictive model that can forecast the performance of a vertical axis wind turbine (VAWT) is presented. The new model includes four primary variables (rotor velocity, wind velocity, air density, and turbine power output) as well as five geometrical variables (rotor radius, turbine height, turbine width, stator spacing, and stator angle). These variables are reduced to include the power coefficient (C_p) and tip speed ratio (TSR). A power coefficient correlation for a novel VAWT (called a Zephyr Vertical axis Wind Turbine (ZVWT)) is developed. The turbine is an adaptation of the Savonius design. The new correlation can predict the turbine's performance for altered stator geometry and varying operating conditions. Numerical simulations with a rotating reference frame are used to predict the operating performance for various turbine geometries. The case study includes 16 different geometries for three different wind directions. The resulting 48 data points provide detailed insight into the turbine performance to develop a general correlation. The model was able to predict the power coefficient with changes in TSR, rotor length, stator spacing, and stator angle, to within 4.4% of the numerical prediction. Furthermore, the power coefficient was predicted with changes in rotor length, stator spacing, and stator angle, to within 3.0% of the numerical simulations. This correlation provides a useful new design tool for improving the ZVWT in the specific conditions and operating requirements specific to this type of wind turbine. Also, the new model can be extended to other conditions that include different VAWT designs. Copyright © 2010 John Wiley & Sons, Ltd.     

Real-time rotor effective wind speed estimation based on actuator disc theory: Design and full-scale experimental validation

The use of state estimation techniques offers a means of inferring rotor effective wind speed from standard measurements of wind turbines. Typical wind speed estimators rely upon a pre-computed quasi-steady aerodynamic mapping, which describes the relationship between pitch angle and tip-speed ratio and the power coefficient. In practice, the static mapping does not capture the influence of turbine structural dynamics and atmospheric turbulence, inevitably resulting in poor performance of the wind speed estimation. In addition, the turbine aerodynamic properties might not be easily accessible. Thus, this paper presents a rotor effective wind speed estimation method that obviates the requirement for prior knowledge of turbine power coefficients. Specifically, the proposed method exploits a simple actuator disc model, where the aerodynamic power and thrust coefficients can be characterized in terms of axial induction factors. Based on this insight and standard turbine measurements, real-time estimation of rotor effective wind speed and axial induction factors can then be achieved using a simplified turbine drive-train model and an extended Kalman filter. In addition, the actuator disc model can be updated easily over time by calibrating solely two correction factors. Thus, the proposed algorithm presents an alternative for estimating the rotor effective wind speed, which is valuable for numerous applications, for example, LiDAR-assisted control and coherence studies.     

基于LabVIEW的离网型风力发电机风速-功率特性研究

通过对离网型风力发电机实际运行状态及气象情况的监测,绘制了风速-功率散点图.利用最大似然估计法对风机输出功率曲线进行拟合,结果表明:七次多项式拟合结果最逼近实际工况;二次多项式拟合曲线精度稍差,但表达式简单明了,可快速预测风力发电机发电量.此外,通过对风力发电机发电量的实际值、理论功率曲线预测值以及利用最大似然估计法拟合得到的功率曲线的预测值的对比,结果表明:风力发电机生产厂商提供的曲线只能反映其稳态的风速-功率关系,用来预测风力发电机发电量还存在较大误差;利用最大似然估计法拟合得到的功率曲线预测的风力发电机发电量误差明显偏小.     

基于转矩极限的改进风电机组虚拟惯量控制策略

为解决大规模风电并网带来的系统频率稳定性降低问题,风电机组通过虚拟惯量控制可为系统提供短期频率支撑,然而惯性响应期间风电机组转速收敛缓慢,导致一部分转子动能被无故浪费;转速恢复阶段的有功突变易造成频率二次跌落。为此,提出基于转矩极限的改进风电机组虚拟惯量控制策略,实现在释放较少动能的前提下提供与传统策略相同的频率响应服务;并在频率步入准稳态时,借助时变功率函数开始转速恢复,实现转速快速恢复的同时缓解二次频率跌落。基于EMTP-RV仿真软件搭建包含风电场的电力系统模型,验证了所提策略的有效性。     

New high profitable wind turbines

To generate more quantities of electric energy from wind it is necessary to use a new type of wind turbine built in the regulable mantle's nozzle. This wind turbine type replaces the free air stream from wind by a programmed, i.e. regulated, and partially concentrated stream of air. The nozzle shell is designed as an aerodynamically shaped ring with wings with its lower pressure side pointed towards the centre so that the lift force on each part of the wing is directed radially towards the centre. This induces centrifugal reaction force in the airflow that causes the stream field to expand strongly downstream of the rotor and includes a greater number of streamlines in the active stream in front of the rotor (upstream). Thus the nozzle forces a higher mass flow rate of air through the turbine. The higher mass flow and higher velocity reduction behind the rotor result in a higher energy output from the wind turbine in the nozzle. In this way the wind turbine efficiency is multiplied. New turbines induce more power from weaker and medium winds and their lasting time, because of the relation P=f(v³) (i.e. the power corresponds to wind velocity raised to third power). Wind turbine nozzle produces three times more energy than conventional wind turbine. Short economic analysis for conditions of the island of Lastovo indicates that profit gained by new turbines is up to five times higher than by conventional turbines. The new wind turbine nozzle should generate interest and demand on an international market, even for regions with weaker winds.     

Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm

A modeling framework is proposed and validated to simulate turbine wakes and associated power losses in wind farms. It combines the large-eddy simulation (LES) technique with blade element theory and a turbine-model-specific relationship between shaft torque and rotational speed. In the LES, the turbulent subgrid-scale stresses are parameterized with a tuning-free Lagrangian scale-dependent dynamic model. The turbine-induced forces and turbine-generated power are modeled using a recently developed actuator-disk model with rotation (ADM-R), which adopts blade element theory to calculate the lift and drag forces (that produce thrust, rotor shaft torque and power) based on the local simulated flow and the blade characteristics. In order to predict simultaneously the turbine angular velocity and the turbine-induced forces (and thus the power output), a new iterative dynamic procedure is developed to couple the ADM-R turbine model with a relationship between shaft torque and rotational speed. This relationship, which is unique for a given turbine model and independent of the inflow condition, is derived from simulations of a stand-alone wind turbine in conditions for which the thrust coefficient can be validated. Comparison with observed power data from the Horns Rev wind farm shows that better power predictions are obtained with the dynamic ADM-R than with the standard ADM, which assumes a uniform thrust distribution and ignores the torque effect on the turbine wakes and rotor power. The results are also compared with the power predictions obtained using two commercial wind-farm design tools (WindSim and WAsP). These models are found to underestimate the power output compared with the results from the proposed LES framework.     

Sensitivity of southern California wind energy to turbine characteristics

Using output from a high‐resolution meteorological simulation, we evaluate the sensitivity of southern California wind energy generation to variations in key characteristics of current wind turbines. These characteristics include hub height, rotor diameter and rated power, and depend on turbine make and model. They shape the turbine's power curve and thus have large implications for the energy generation capacity of wind farms. For each characteristic, we find complex and substantial geographical variations in the sensitivity of energy generation. However, the sensitivity associated with each characteristic can be predicted by a single corresponding climate statistic, greatly simplifying understanding of the relationship between climate and turbine optimization for energy production. In the case of the sensitivity to rotor diameter, the change in energy output per unit change in rotor diameter at any location is directly proportional to the weighted average wind speed between the cut‐in speed and the rated speed. The sensitivity to rated power variations is likewise captured by the percent of the wind speed distribution between the turbines rated and cut‐out speeds. Finally, the sensitivity to hub height is proportional to lower atmospheric wind shear. Using a wind turbine component cost model, we also evaluate energy output increase per dollar investment in each turbine characteristic. We find that rotor diameter increases typically provide a much larger wind energy boost per dollar invested, although there are some zones where investment in the other two characteristics is competitive. Our study underscores the need for joint analysis of regional climate, turbine engineering and economic modeling to optimize wind energy production. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

Fuzzy modeling techniques and artificial neural networks to estimate annual energy output of a wind turbine

The purpose of this article is to develop a new method to estimate annual energy output for a given wind turbine in any region which should be easy to use and has satisfactory accuracy. To do this, hourly wind speeds of 25 different stations in Netherlands, output power curve of S47 wind turbine and fuzzy modeling techniques and artificial neural networks were used and a model is developed to estimate annual energy output for S47 wind turbine in different regions. Since this model has three inputs (average wind speed, standard deviation of wind speed, and air density of that region), this model is easy to use. The accuracy of this method is compared with the accuracy of conventional methods and it is shown that this new method performs better. Thereafter, we have shown that by making some small changes to this proposed model, other pitch control wind turbines could be modeled too. As an example, we have modeled E82 wind turbine based on the model developed for S47 and it is shown that this model has still satisfactory accuracy.     

Horizontal axis wind turbine working at maximum power coefficient continuously

The performance of a horizontal axis wind turbine continuously operating at its maximum power coefficient was evaluated by a calculation code based on Blade Element Momentum (BEM) theory. It was then evaluated for performance and Annual Energy Production (AEP) at a constant standard rotational velocity as well as at a variable velocity but at its maximum power coefficient.The mathematical code produced a power coefficiency curve which showed that notwithstanding further increases in rotational velocity a constant maximum power value was reached even as wind velocity increased.This means that as wind velocity varies there will always be a rotational velocity of the turbine which maximises its coefficient. It would be sufficient therefore to formulate the law governing the variation in rotational velocity as it varied with wind velocity to arrive at a power coefficient that is always the same and its maximum.This work demonstrates the methodology for determining the law governing the rotational velocity of the rotor and it highlights the advantages of a wind turbine whose power coefficient is always at maximum rather than very variable in line with the variation of wind velocity.     

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.     

Power capture optimization of variable-speed wind turbines using an output feedback controller

One of the major factors that can increase the efficiency of wind turbines is through control of the rotor speed to track the optimal value. A high performance controller can significantly increase the amount of energy that can be captured from wind. The main problem associated with controller design is the presence of uncertainties in the dynamic model of the system, which can be associated with unknown constant parameters and/or unmodeled dynamics such as external disturbances. several adaptive and robust control approaches have been developed to account for these uncertainties. In this paper, a robust controller is presented that compensates for both types of uncertainties; the full mechanical and electrical dynamics of the turbine are considered. These dynamics require acceleration of the rotor to provide feedback information which is not available in sufficiently accurate form during practice. Therefore, in this approach, an observer estimates this information using the speed of the rotor as the output, with the estimation error considered during the stability analysis. This presents one of the main advantages of the approach; the simulation results illustrate the effectiveness of the controller.