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.     

Optimization of turbine design in wind farms with multiple hub heights,using exact analytic gradients and structural constraints

Wind farms are generally designed with turbines of all the same hub height. If wind farms were designed with turbines of different hub heights, wake interference between turbines could be reduced, lowering the cost of energy (COE). This paper demonstrates a method to optimize onshore wind farms with two different hub heights using exact, analytic gradients. Gradient‐based optimization with exact gradients scales well with large problems and is preferable in this application over gradient‐free methods. Our model consisted of the following: a version of the FLOw Redirection and Induction in Steady‐State wake model that accommodated three‐dimensional wakes and calculated annual energy production, a wind farm cost model, and a tower structural model, which provided constraints during optimization. Structural constraints were important to keep tower heights realistic and account for additional mass required from taller towers and higher wind speeds. We optimized several wind farms with tower height, diameter, and shell thickness as coupled design variables. Our results indicate that wind farms with small rotors, low wind shear, and closely spaced turbines can benefit from having two different hub heights. A nine‐by‐nine grid wind farm with 70‐meter rotor diameters and a wind shear exponent of 0.08 realized a 4.9% reduction in COE by using two different tower sizes. If the turbine spacing was reduced to 3 diameters, the reduction in COE decreased further to 11.2%. Allowing for more than two different turbine heights is only slightly more beneficial than two heights and is likely not worth the added complexity.     

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%.     

Properties of the offshore low level jet and rotor layer wind shear as measured by scanning Doppler Lidar

The atmospheric flow phenomenon known as the Low Level Jet (LLJ) is an important source of wind power production in the Great Plains. However, due to the lack of measurements with the precision and vertical resolution needed, particularly at rotor heights, it is not well‐characterized or understood in offshore regions being considered for wind‐farm development. The present paper describes the properties of LLJs and wind shear through the rotor layer of a hypothetical wind turbine, as measured from a ship‐borne Doppler lidar in the Gulf of Maine in July–August 2004. LLJs, frequently observed below 600 m, were mostly during nighttime and transitional periods, but they were also were seen during some daytime hours. The presence of a LLJ significantly modified wind profiles producing vertical wind speed shear. When the wind shear was strong, the estimates of wind power based upon wind speeds measured at hub‐height could have significant errors. Additionally, the inference of hub‐height winds from near‐surface measurements may introduce further error in the wind power estimate. The lidar dataset was used to investigate the uncertainty of the simplified power‐law relation that is often employed in engineering approaches for the extrapolation of surface winds to higher elevations. The results show diurnal and spatial variations of the shear exponent empirically found from surface and hub‐height measurements. Finally, the discrepancies between wind power estimates using lidar‐measured hub‐height winds and rotor equivalent winds are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Investigating the possibility of using different hub height wind turbines in a wind farm

Many researchers have focused on the layout design of a wind farm using the computational methods. Most of previous researches focused on relevant large cell size and using same hub height wind turbines. In this paper, the authors investigate the possibility of using different hub height wind turbines in a wind farm. A limited area (2?km?×?2?km) with constant wind speed and direction is considered as the potential wind farm area, and a nested genetic algorithm is used as optimisation algorithm. Two different hub height wind turbines are introduced with two different cell sizes. Power output, cost, payback period, and total profit are selected as evaluation criteria when comparing the layouts with same hub height wind turbines with the layouts with different hub height wind turbines. The results demonstrate that it is feasible and possible to use different hub height wind turbines in a wind farm.     

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.     

Classifying rotor‐layer wind to reduce offshore available power uncertainty

Rotor‐layer wind resource and turbine available power uncertainties prior to wind farm construction may contribute to significant increases in project risk and costs. Such uncertainties exist in part due to limited offshore wind measurements between 40 and 250 m and the lack of empirical methods to describe wind profiles that deviate from a priori, expected power law conditions. In this article, we introduce a novel wind profile classification algorithm that accounts for nonstandard, unexpected profiles that deviate from near power law conditions. Using this algorithm, offshore Doppler wind lidar measurements in the Mid‐Atlantic Bight are classified based on goodness‐of‐fit to several mathematical expressions and relative speed criteria. Results elucidate the limitations of using power law extrapolation methods to approximate average wind profile shape/shear conditions, as only approximately 18% of profiles fit well with this expression, while most consist of unexpected wind shear. Further, results demonstrate a relationship between classified profile variability and coastal meteorological features, including stability and offshore fetch. Power law profiles persist during unstable conditions and relatively weaker northeasterly flow from water (large fetch), whereas unexpected classified profiles are prevalent during stable conditions and stronger southwesterly flow from land (small fetch). Finally, the magnitude of the discrepancy between hub‐height wind speed and rotor equivalent wind speed available power estimates varies by classified wind‐profile type. During unexpected classified profiles, both a significant overprediction and underprediction of hub‐height wind available power is possible, illustrating the importance of accounting for site‐specific rotor‐layer wind shear when predicting available power.     

风电场中多台风力机的数值模拟

将NREL 5 MW风力机作为基本机型,使用致动线模型和大涡模拟相结合的数值方法,在中性大气边界层中模拟含有多台风力机的风电场。为了模拟风电场的复杂入流条件,首先模拟体积为3000 m(长)×3000 m(宽)×1000m(高)的大气边界层,并对模拟结果进行验证,结果表明:在覆盖逆温层以下,不同高度处的位温不变,平均风速满足剪切特性,脉动风速满足湍流谱特性;然后,分析了致动线模型中风轮直径上的网格节点数量(N)和高斯分布因子(ε)的取值规律,发现ε以网格尺度(η)为自变量取值时,N越大,η的系数越大,当N取63时,η的系数可取2或3,但N取25时,η只能取1.2;最后,使用致动线模型在大气边界层中布置8台风力机,模拟风电场,并对风力机间的相互干扰进行分析,发现第一排风力机功率明显大于其他风力机功率输出,占风场总功率输出的40.3%。     

Benefits of collocating vertical‐axis and horizontal‐axis wind turbines in large wind farms

In this study, we address the benefits of a vertically staggered (VS) wind farm, in which vertical‐axis and horizontal‐axis wind turbines are collocated in a large wind farm. The case study consists of 20 small vertical‐axis turbines added around each large horizontal‐axis turbine. Large‐eddy simulation is used to compare power extraction and flow properties of the VS wind farm versus a traditional wind farm with only large turbines. The VS wind farm produces up to 32% more power than the traditional one, and the power extracted by the large turbines alone is increased by 10%, caused by faster wake recovery from enhanced turbulence due to the presence of the small turbines. A theoretical analysis based on a top‐down model is performed and compared with the large‐eddy simulation. The analysis suggests a nonlinear increase of total power extraction with increase of the loading of smaller turbines, with weak sensitivity to various parameters, such as size, and type aspect ratio, and thrust coefficient of the vertical‐axis turbines. We conclude that vertical staggering can be an effective way to increase energy production in existing wind farms. Copyright © 2016 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.     

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.     

Analysis of wake measurements from the ECN Wind Turbine Test Site Wieringermeer,EWTW

This paper describes an analysis of wake measurements from the research farm at the ECN Wind Turbine Test Site Wieringermeer. This research farm is owned and operated by the Energy Research Centre of the Netherlands. The farm consists of five research turbines that are oriented in a single line with a mutual distance of 3.8D(iameter). The turbines are variable speed and pitch controlled, and they have a diameter and a hub height of 80 m. The rated power of the turbines is 2.5 MW. Extensive machine measurements (power, loads, yaw angle and pitch angles) are carried out on these turbines. In parallel, meteorological measurements are done on a 108 m mast that is instrumented at three heights (hub height and hub height ± 70% span) with sonic anemometers and cups and wind vanes. This mast is located at a shortest distance of 2.5D from one of the turbines. Data have been collected over a period of almost 5 years, and they are used to study several phenomena mainly related to wake aerodynamics, e.g. power losses in the wake of up to four wind turbines and meteorological wake phenomena at different distances behind the turbines. Copyright © 2011 John Wiley & Sons, Ltd.     

Time‐adaptive wind turbine model for an LES framework

Most large‐eddy simulation studies related to wind energy have been carried out either by using a fixed pressure gradient to ensure that mean wind direction is perpendicular to the wind turbine rotor disk or by forcing the flow with a geostrophic wind and timely readjusting the turbines' orientation. This has not allowed for the study of wind farm characteristics with a time‐varying wind vector. In this paper, a new time‐adaptive wind turbine model for the large‐eddy simulation framework is introduced. The new algorithm enables the wind turbines to dynamically realign with the incoming wind vector and self‐adjust the yaw orientation with the incoming wind vector similar to real wind turbines. The performance of the new model is tested first with a neutrally stratified atmospheric flow forced with a time‐varying geostrophic wind vector. A posteriori, the new model is used to further explore the interaction between a synthetic time‐changing thermal atmospheric boundary layer and an embedded wind farm. Results show that there is significant potential power to be harvested during the unstable time periods at the cost of designing wind turbines capable of adapting to the enhanced variance of these periods. Stable periods provide less power but are more constant over time with an enhanced lateral shear induced by an increased change in wind direction with height. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Dependence of optimal wind turbine spacing on wind farm length

Recent large eddy simulations have led to improved parameterizations of the effective roughness height of wind farms. This effective roughness height can be used to predict the wind velocity at hub‐height as function of the geometric mean of the spanwise and streamwise turbine spacings and the turbine loading factors. Recently, Meyers and Meneveau used these parameterizations to make predictions for the optimal wind turbine spacing in infinitely large wind farms. They found that for a realistic cost ratio between the turbines and the used land surface, the optimal turbine spacing may be considerably larger than that used in conventional wind farms. Here, we extend this analysis by taking the length of the wind farm, i.e. the number of rows in the downstream direction into account and show that the optimal turbine spacing strongly depends on the wind farm length. For small to moderately sized wind farms, the model predictions are consistent with spacings found in operational wind farms. For much larger wind farms, the extended optimal spacing found for infinite wind farms is confirmed. Copyright © 2015 John Wiley & Sons, Ltd.     

Large eddy simulation study of the humidity variation in the shadow of a large wind farm

Numerous studies have shown that wind turbine wakes within a large wind farm bring about changes to both the dynamics and thermodynamics of the atmospheric boundary layers (ABL). Previously, we investigated the relative humidity budget within a wind farm via field measurements in the near‐wake region and large eddy simulations (LES). The effect of the compounding wakes within a large wind farm on the relative humidity was also investigated by LES. In this study, we investigate how the areas of relative humidity variation, that was observed in the near‐wake, develop downstream in the shadow region of a large wind farm. To this end, LES of a wind farm consisting of 8x6 wind turbines with periodic boundary condition in the lateral direction (inferring an infinitely wide farm) interacting with a stable ABL is carried out. Two wind farm layouts, aligned and staggered, are considered in the analysis and the results from both configurations are compared to each other. It is observed that a decrease of relative humidity underneath the hub height and an increase above the hub height build up within the wind farm, and are maintained in the downstream of the farm for long distances. The staggered farm layout is more effective in keeping a more elongated region of low relative humidity underneath the hub, when compared to the aligned layout.     

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.     

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.     

Effects of inflow turbulence intensity and turbine arrangements on the power generation efficiency of large wind farms

In this study, we conduct a series of large‐eddy simulations (LESs) to study the impact of different incoming turbulent boundary layer flows over large wind farms, with a particular focus on the overall efficiency of electricity production and the evolution of the turbine wake structure. Five representative turbine placements in the large wind farm are considered, including an aligned layout and four staggered layouts with lateral or vertical offset arrangements. Four incoming flow conditions are used and arranged from the LESs of the ABL flow over homogeneous flat surfaces with four different aerodynamic roughness lengths (i.e., z0 = 0.5, 0.1, 0.01, and 0.0001 m), where the hub‐height turbulence intensity levels are about 11.1%, 8.9%, 6.8%, and 4.9%, respectively. The simulation results indicate that an enhancement in the inflow turbulence level can effectively increase the power generation efficiency in the large wind farms, with about 23.3% increment on the overall farm power production and up to about 32.0% increment on the downstream turbine power production. Under the same inflow condition, the change of the turbine‐array layouts can increase power outputs within the first 10 turbine rows, which has a maximum increment of about 26.5% under the inflow condition with low turbulence. By comparison, the increase of the inflow turbulence intensity facilitates faster wake recovery that raises the power generation efficiency of large wind farms than the adjustment of the turbine placing layouts.