This paper presents the influence of the strut and the tower on the aerodynamic force of the blade for the vertical axis wind turbine (VAWT). It has been known that struts degrade the performance of VAWTs due to the inherent drag losses. In this study, three-dimensional Reynolds-averaged Navier-Stokes simulations have been conducted to investigate the effect of the strut and the tower on the flow pattern around the rotor region, the blade force distribution, and the rotor performance. A comparison has been made for three different cases where only the blade; both the blade and the strut; and all of the blade, the strut, and the tower are considered. A 12-kW three-bladed H-rotor VAWT has been studied for tip speed ratio of 4.16. This ratio is relatively high for this turbine, so the influence of the strut is expected to be crucial. The numerical model has been validated first for a single pitching blade and full VAWTs. The simulations show distinguished differences in the force distribution along the blade between two cases with and without struts. Since the wake from the struts interacts with the blades, the tangential force is reduced especially in the downwind side when the struts are considered. The calculated power coefficient is decreased by 43 %, which shows the importance of modeling the strut effect properly for accurate prediction of the turbine performance. The simulations also indicate that including the tower does not yield significant difference in the force distribution and the rotor power.
An analysis of the effect of low‐level wind maxima (LLWM) below hub height on sound propagating from wind turbines has been performed at a site in northern Sweden. The stably stratified boundary layer, which is typical for cold climates, commonly features LLWM. The simplified concept for the effects of refraction, based on the logarithmic wind profile or other approaches where the wind speed is continuously increasing with height, is often not applicable there. Long‐term meteorological measurements in the vicinity of a wind farm were therefore used to identify LLWM. Sound measurements were conducted simultaneously to the meteorological measurements. LLWM below hub height decrease the sound level close to the surface downwind of the wind farm. This effect increases with increasing strength of the LLWM. The occurrence of LLWM as well as strength and height of the LLWM are dependent on the wind direction.
The impact of snow on sound propagating from a wind farm in northern Sweden has been investigated. Simultaneous acoustic and meteorological measurements, combined with daily snow observations, have been analysed for the snow season in 2013 to 2014. Such measurements are crucial since significant knowledge gaps exist, especially for conditions in cold climates, in the implementation of atmospheric boundary layer complexity in sound propagation models. The effect of snow on sound propagation is shown to be dependent on the snow quality. Moreover, snow on trees (upplega) also has an influence on sound propagation. Compared with conditions without snow on trees, the average sound level is approximately 2 dBA lower. The effect is more distinct for higher frequencies compared with lower frequencies.
The technique of using imposed turbulence in combination with a forced boundary layer in order to model the atmospheric boundary layer is analyzed for a very long domain using large-eddy simulations with different combinations of prescribed velocity profiles and pregenerated turbulence fields based on the Mann model. The ambient flow is first studied in the absence of wind turbines. The velocity profiles undergo a transition throughout the domain with a velocity increase of 10% to 15% close to the ground far downstream in the domain. The turbulence characteristics close to the turbulence plane are, as expected, similar to those of the added Mann turbulence. The turbulence will then undergo a transition throughout the domain to finally reach a balance with the shear profile at a certain downstream distance. This distance is found to depend on the turbulence level of the added Mann turbulence planes. A lower Mann turbulence level generally results in a shorter "balancing" distance. Secondly, a row of 10 turbines is imposed in the simulations at different distances from the plane of turbulence in order to determine how the distance affects wake conditions and power production levels. Our results show that a "balancing" distance is needed between the turbulence plane and the first turbine in the row in order to ensure nonchanging ambient conditions throughout the turbine row. This introduces an increase in the computational costs. The computational cost for the forced boundary technique is normally lower compared with using precursor simulations, for longer domains; however, this needs to be verified further.
Accurately determining hydrodynamic force statistics is crucial for designing offshore engineering structures, including offshore wind turbine foundations, due to the significant impact of nonlinear wave-structure interactions. However, obtaining precise load statistics often involves computationally intensive simulations. Furthermore, the estimation of statistics using current practices is subject to ongoing discussion due to the inherent uncertainty involved. To address these challenges, we present a novel machine learning framework that leverages data-driven surrogate modeling to predict hydrodynamic loads on monopile foundations while reducing reliance on costly simulations and facilitate the load statistics reconstruction. The primary advantage of our approach is the significant reduction in evaluation time compared to traditional modeling methods. The novelty of our framework lies in its efficient construction of the surrogate model, utilizing the Gaussian process regression machine learning technique and a Bayesian active learning method to sequentially sample wave episodes that contribute to accurate predictions of extreme hydrodynamic forces. Additionally, a spectrum transfer technique combines computational fluid dynamics (CFD) results from both quiescent and extreme waves, further reducing data requirements. This study focuses on reducing the dimensionality of stochastic irregular wave episodes and their associated hydrodynamic force time series. Although the dimensionality reduction is linear, Gaussian process regression successfully captures high-order correlations. Furthermore, our framework incorporates built-in uncertainty quantification capabilities, facilitating efficient parameter sampling using traditional CFD tools. This paper provides comprehensive implementation details and demonstrates the effectiveness of our approach in delivering reliable statistics for hydrodynamic loads while overcoming the computational cost constraints associated with classical modeling methods.
Direct numerical simulations of the Navier–Stokes equations are performed to achieve a better understanding of the behaviour of wakes generated by wind turbines. The simulations are performed by combining the in-house developed computer code EllipSys3D with the actuator-line methodology. In the actuator-line method, the blades are represented by lines along which body forces representing the loading are introduced. The body forces are determined by computing local angles of attack and using tabulated aerofoil coefficients. The advantage of using the actuator-line technique is that it is not needed to resolve blade boundary layers and instead the computational resources are devoted to simulating the dynamics of the flow structures. In the present study, approximately 5 million mesh points are used to resolve the wake structure in a 120-degree domain behind the turbine. The results from the computational fluid dynamics (CFD) simulations are evaluated and the downstream evolution of the velocity field is depicted. Special interest is given to the structure and position of the tip vortices. Further, the circulation from the wake flow field is computed and compared to the distribution of circulation on the blades.
The flow upstream a wind turbine is studied in order to investigate blockage effects. We use rotating wind turbine models in a wind tunnel, where velocity measurements have been made both with hot-wire anemometry up to approximately 4.5 diameters (D) upstream the turbine, as well as laser particle image velocimetry measurements close to the turbine rotor. Also, numerical simulations have been carried out by means of a finite volume code. The measurements show, among other things, that the flow is affected more than 3D upstream the rotor plane.
In the present work, the near‐wake generated for a vertical axis wind turbine (VAWT) was simulated using an actuator line model (ALM) in order to validate and evaluate its accuracy. The sensitivity of the model to the variation of the spatial and temporal discretization was studied and showed a bigger response to the variation in the mesh size as compared with the temporal discretization. The large eddy simulation (LES) approach was used to predict the turbulence effects. The performance of Smagorinsky, dynamic k‐equation, and dynamic Lagrangian turbulence models was tested, showing very little relevant differences between them. Generally, predicted results agree well with experimental data for velocity and vorticity fields in representative sections. The presented ALM was able to characterize the main phenomena involved in the flow pattern using a relatively low computational cost without stability concerns, identified the general wake structure (qualitatively and quantitatively), and the contribution from the blade tips and motion on it. Additionally, the effects of the tower and struts were investigated with respect to the overall structure of the wake, showing no significant modification. Similarities and discrepancies between numerical and experimental results are discussed. The obtained results from the various simulations carried out here can be used as a practical reference guideline for choosing parameters in VAWTs simulations using the ALM.
A numerical study of both a horizontal axis wind turbine (HAWT) and a vertical axis wind turbine (VAWT) with similar size and power rating is presented. These large scale turbines have been tested when operating stand-alone at their optimal tip speed ratio (TSR) within a neutrally stratified atmospheric boundary layer (ABL). The impact of three different surface roughness lengths on the turbine performance is studied for the both turbines. The turbines performance, the response to the variation in the surface roughness of terrain, and the most relevant phenomena involved on the resulting wake were investigated. The main goal was to evaluate the differences and similarities of these two different types of turbine when they operate under the same atmospheric flow conditions. An actuator line model (ALM) was used together with the large eddy simulation (LES) approach for predicting wake effects, and it was implemented using the open-source computational fluid dynamics (CFD) library OpenFOAM to solve the governing equations and to compute the resulting flow fields. This model was first validated using wind tunnel measurements of power coefficients and wake of interacting HAWTs, and then employed to study the wake structure of both full scale turbines. A preliminary study test comparing the forces on a VAWT blades against measurements was also investigated. These obtained results showed a better performance and shorter wake (faster recovery) for an HAWT compared with a VAWT for the same atmospheric conditions.
This work presents a numerical study of the obtained performance and the resulting flow field between two interacting large scale vertical-axis wind turbines (VAWTs), under the influence of a deflected wake through the struts pitching of the upwind turbine. The configuration consists of two VAWTs aligned in the direction of the incoming flow in which a wide range of fixed struts pitching angles in the upwind turbine have been investigated. The main goal is to evaluate the influence of the wake deflection on the turbines performance while they are operating at their optimal tip speed ratio (TSR), and to reproduce the most relevant phenomena involved in the flow pattern of the interacting wake. Arrangements with cross-stream offsets have also been tested for quantifying the contribution of this modification into the overall performance. For this purpose, an actuator line model (ALM) has been implemented using the open-source CFD library OpenFOAM in order to solve the governing equations and to calculate the resulting flow. The Large eddy simulation (LES) approach is considered to reproduce the turbulence flow effects. A preliminary study to identify the optimal TSR of the interacting downwind turbine has been investigated.
In this work, a closely spaced dual turbine concept is studied. The distance between the two side-by-side hubs is 1.05D$$ D $$, where D$$ D $$ is the rotor diameter. This configuration has a potential benefit for offshore wind developments in which power density can be maximized. The main goal is to evaluate the overall aerodynamic performance, blade loads, and wake structure of a reference wind turbine generator operating within this dual turbine configuration and to compare the effects against those for the typical single turbine configuration. For this purpose, an actuator line model has been employed together with the large eddy simulation approach for predicting the turbulence effects. This model was implemented by using the open-source computational fluid dynamics toolbox OpenFOAM. Results show a better performance for the dual turbine concept. Under same operating conditions, the aerodynamic power of each turbine within the dual concept is higher than the power of the stand alone turbine, particularly at lower operating wind speeds (approximately 2% to 3% of extra power per turbine). Comparison between the two configurations shows similar character of the tangential and normal forces acting on the blades in terms of magnitude and fluctuation, eliminating potential concerns regarding fatigue and blade design. The largest difference in the tangential and normal root bending moments are approximately 3% and 2%, respectively, between single and dual turbine configurations. Finally, wake recovery analysis shows a downwind velocity deficit that is not enhanced streamwise in the dual turbine configuration with no considerable difference after 7D$$ D $$.
The relation between power performance and turbulence intensity for a VAWT H-rotor is studied using logged data from a 14 month (discontinuous) period with the H-rotor operating in wind speeds up to 9 m/s. The turbine, designed originally fora nominal power of 200 kW, operated during this period mostly in a restricted mode due to mechanical concerns, reachingpower levels up to about 80 kW. Two different approaches are used for presenting results, one that can be compared topower curves consistent with the International Electrotechnical Commission (IEC) standard and one that allows isolatingthe effect of turbulence from the cubic variation of power with wind speed. Accounting for this effect, the turbine stillshows slightly higher efficiency at higher turbulence, proposing that the H-rotor is well suited for wind sites with turbulentwinds. The operational data are also used to create a Cp(λ) curve, showing slightly lower Cp compared with a curvesimulated by a double multiple streamtube model.
The power production of the Lillgrund wind farm is determined numerically using large-eddy simulations and compared with measurements. In order to simulate realistic atmospheric conditions, pre-generated turbulence and wind shear are imposed in the computational domain. The atmospheric conditions are determined from data extracted from a met mast, which was erected prior to the establishment of the farm. In order to allocate most of the computational power to the simulations of the wake flow, the turbines are modeled using an actuator disc method where the discs are imposed in the computational domain as body forces which for every time step are calculated from tabulated airfoil data. A study of the influence of imposed upstream ambient turbulence is performed and shows that higher levels of turbulence results in slightly increased total power production and that it is of great importance to include ambient turbulence in the simulations. By introducing ambient atmospheric turbulence, the simulations compare very well with measurements at the studied inflow angles. A final study aiming at increasing the farm production by curtailing the power output of the front row turbines and thus letting more kinetic energy pass downstream is performed. The results, however, show that manipulating only the front row turbines has no positive effect on the farm production, and therefore, more complex curtailment strategies are needed to be tested.
The purpose of the present work is to validate the capability of the actuator line method to compute vortex structures in the near wake behind the MEXICO experimental wind turbine rotor. In the MEXICO project/MexNext Annex, particle image velocimetry measurements have made it possible to determine the exact position of each tip vortex core in a plane parallel to the flow direction. Determining center positions of the vortex cores makes it possible to determine the trajectory of the tip vortices, and thus the wake expansion in space, for the analyzed tip speed ratios. The corresponding cases, in terms of tip speed ratios, have been simulated by large-eddy simulations using a Navier-Stokes code combined with the actuator line method. The flow field is analyzed in terms of wake expansion, vortex core radius, circulation and axial and radial velocity distributions. Generally, the actuator line method generates significantly larger vortex cores than in the experimental cases, but predicts the expansion, the circulation and the velocity distributions with satisfying results. Additionally, the simulation and experimental data are used to test three different techniques to compute the average axial induction in the wake flow. These techniques are based on the helical pitch of the tip vortex structure, 1D momentum theory and wake expansion combined with mass conservation. The results from the different methods vary quite much, especially at high values of . Copyright (c) 2014 John Wiley & Sons, Ltd.
In wind integration studies, sub-hourly, load synchronous wind data are often preferable. These datasets can be generatedby a hybrid approach, combining hourly measurements or output from meteorological models with a stochastic simulationof the high-frequency fluctuations. This paper presents a method for simulating aggregated intra-hourly wind power fluc-tuations for a power system, taking into account the time-varying volatility seen in measurements. Some key elements inthe modelling were transformations to stationarity, the use of frequency domain techniques including a search for appropri-ate phase angles and an adjustment of the resulting time series in order to get correct hourly means. Generation data fromDenmark and Germany with 5 and 15 min temporal resolution were used for training models. It is shown that the distribu-tion and non-stationarity of simulated deviations from hourly means closely follow those of measurements. Power spectraldensities and step change distributions agree well. Of particular importance is that the results are good also when the train-ing and objective power systems are not the same. The computational cost is low in comparison with other approaches forgenerating high-frequency data.
We show that Swedish wind turbines constructed before 2007 lose 0.15 capacity factor percentage points per year, corresponding to a lifetime energy loss of 6%. A gradual increase of downtime accounts for around one third of the deterioration and worsened efficiency for the remaining. Although the performance loss in Sweden is considerably smaller than previously reported in the UK, it is statistically significant and calls for a revision of the industry practice for wind energy calculations. The study is based on two partly overlapping datasets, comprising 1,100 monthly and 1,300 hourly time series spanning 5–25 years each.
The scaling behaviour of a straight-bladed vertical axis wind turbine is considered. A scaling scheme is described that, in the presence of a wind shear profile, aims at leaving the material stresses of the scaled construction unchanged. On the basis of a recent 200 kW three-bladed H-rotor design, a structural upper size of the turbine is proposed, this size being the scale at which the gravitational force starts to become important. As gravity has a much worse scaling behaviour than the aerodynamic and centrifugal forces, the construction work will become increasingly more difficult above this scale. The upper size is estimated to be around 30 MW.
The flow around an isolated horizontal-axis wind turbine is estimated by means of a new vortex code based on the Biot-Savart law with constant circulation along the blades. The results have been compared with numerical simulations where the wind turbine blades are replaced with actuator lines. Two different wind turbines have been simulated: one with constant circulation along the blades, to replicate the vortex method approximations, and the other with a realistic circulation distribution, to compare the outcomes of the vortex model with real operative wind-turbine conditions (Tjaereborg wind turbine). The vortex model matched the numerical simulation of the turbine with constant blade circulation in terms of the near-wake structure and local forces along the blade. The results from the Tjaereborg turbine case showed some discrepancies between the two approaches, but overall, the agreement is qualitatively good, validating the analytical method for more general conditions. The present results show that a simple vortex code is able to provide an estimation of the flow around the wind turbine similar to the actuator-line approach but with a negligible computational effort.
The wind and turbulence fields over a small, high‐latitude sea are investigated. These fields are highly influenced by the proximity to the coast, which is never more than 200 km away. Simulations with the WRF model over the Baltic Sea are compared with a simplified, stationary wind model driven by the synoptic forcing. The difference between the models is therefore representative of the mesoscale influence. The results show that the largest wind‐field modifications compared with a neutral atmosphere occur during spring and summer, with a mean monthly increase of up to approximately 1 ms−1 at typical hub heights and upper rotor area (120‐170 m height) in the WRF model. The main reason for this is large‐scale low‐level jets caused by the land‐sea temperature differences, likely increasing in strength due to inertial oscillations. These kind of events can be persistent for approximately 12 hours and cover almost the entire basin, causing wind speed and wind shear to increase considerably. The strongest effect is around 2000 to 2300 local time. Sea breezes and coastal low‐level jets are of less importance, but while sea breezes are mostly detected near the coastline, other types of coastal jets can extend large distances off the coast. During autumn and winter, there are fewer low‐level jet occurrences, but the wind profile cannot be explained by the classical theory of the one‐dimensional model. This indicates that the coastal environment is complex and may be affected by advection from land surfaces to a large degree even when unstable conditions dominate.
With the increasing demand for wind energy, it is important to be able to understand and predict the available wind resources. To that end, the present wind tunnel study addresses the flow in the induction and entrance region of wind farms through particle image velocimetry, with focus on differences between actuator disks and two-bladed rotating wind turbine models. Both staggered and aligned farm layouts are examined for three different incoming wind directions. For each layout, 69 disks or turbines are used, and the field of view ranges from 12 rotor diameters upstream of the farms to 8 diameters downstream of the first row. The results show that the induction, or blockage effect, is higher for the disks, even though the thrust (or drag) coefficient is the same. In contrast, the wake is stronger downstream of the turbines. The orientation and layout of the farm do not have a major impact on the results. Modal decomposition of the flow shows that the flow structure similarity between the disk and turbines improves downstream of the second row of wake generating objects, indicating that the substitution of wind turbines by actuator disks is more appropriate for wind farms than for the investigation of single wakes.