Simulation of atmospheric flows over complex terrain for wind power potential assessment

When assessing the economic viability of a wind farm, the estimation of the on-site wind power potential is perhaps the most important step. The most common way of evaluating the wind power potential of an area of interest consists of making on-site measurements for a period of one year. In order to take account of the inter-annual variation of wind speed, the one year of data are normally correlated with data recorded at a reference site where long-term data (typically > 10 years) are available. A correlation analysis is formulated for the concurrent data sets at the reference and prediction sites. This correlation is then used to transform the long-term wind speed at the reference site to the long-term wind speed that would have been expected at the prediction site had long-term measurements been made at this site. An alternative approach is also used, which consists of establishing site-to-site relationships using a numerical model to simulate meteorological situations which are typical for the area of interest. These relationships are then used to transpose the known long-term wind statistics of the reference site to the prediction site. Such an approach is applied in this work to the region of Chasseral & Mt-Crosin. The wind data available for a period of 16 years at Chasseral are transposed to the Mt-Crosin site where they are then compared to the data measured at the location of the installed wind farm. Over complex terrain, the linearised models traditionally used for wind power potential assessment fail to reproduce accurate wind fields. Therefore, to be applied to mountainous terrain such as that found in Switzerland, the approach relying on numerical simulation requires the development and validation of a numerical tool capable of simulating wind fields over complex topography. As the numerical model would have to deal with relatively steep slopes requiring a fine horizontal (50-100 m) and vertical resolution (∼5-10 m in the lowest levels), a fluid dynamics model was used which solves the complete set of Navier-Stokes equations with κ-ε turbulence closure. The standard version of the model used (CFX4) is modified in a novel way to extend its field of application so that atmospheric phenomena could be simulated which are typical of the meso-scale. The modified version solves the flow equations with the anelastic approximation (deep Boussinesq) and assuming a background rotation of the wind field (with the high altitude wind field following the geostrophic approximation). In the first part of this work, the numerical model is validated. The results obtained in this phase show that for meteorological situations for which the wind at the ground is coupled to the high altitude wind, the numerical model is able to satisfactorily reproduce: the flow in the surface layer, reproducing the effects associated with the ground roughness, roughness change, or heat flux through the ground; the flow in the Ekman layer together with the interaction between the free flow thermal stability conditions and the boundary layer; the linear and non-linear effects associated with the perturbation induced by a mountain in a stably stratified flow. In the second stage of this work, an extension of the standard Measure-Correlate-Predict method is presented to calculate the wind speed distribution at the prediction site, from transposition relationships and from the wind statistics at the reference site. The validity of the underlying assumptions is confirmed using concurrent data sets that were collected at both the reference and prediction sites. To evaluate the accuracy that can be achieved with the transposition assumptions, a back-prediction is performed using the transposition relationships obtained using the observations. Different types of transposition relationships have been investigated. Finally, the transposition methodology is applied to calculate the wind speed conditions at Mt-Crosin from the Chassera1 data, using the transposition relationships calculated by the numerical model for a range of meteorological situations typical for the area considered. The Mt-Crosin to Chassera1 sector wind speed ratios calculated by the numerical model tend to slightly underestimate those observed. The mean wind speeds obtained from the transposition are underestimated by 7% to 18% at the three measuring mast locations on Mt-Crosin. The yearly energy output that can be produced by a wind turbine in these conditions is underestimated by 8% to 36%. For a further period, the actual energy production of the three installed wind turbines has been compared with the model prediction at hub height, which showed that the transposition results underestimate the actual yearly production by 22% to 24%. From the transposition of the long-term data at Chassera1 (16 years), with the relationships obtained by the numerical model, a wind power potential of between 470 MWh/year (Côte Est) and 596 MWh/year (Côte Nord) is predicted using the characteristics of a Vestas-V44 wind turbine. From the work presented here, it appears that for well-exposed sites such as those located along the Jura Crest, the methods developed are able to give a wind power potential prediction with a similar accuracy as a one year measurement campaign performed on site.

Potential and uncertainty of wind energy in the Swiss Alps

Albertus Christiaan Kruyt

Switzerland has committed itself to an ambitious energy strategy. It aims to replace the exist- ing nuclear generation capacity with predominantly indigenous renewable resources. Wind power could play a significant role in this transition, yet the wind resource in the mountainous terrain that makes up most of the country is poorly understood. There are indications that this resource could be significant, but studies undertaken so far acknowledge large uncertain- ties. This is because the complex topography of the mountains influences the flow patterns significantly, and these can become partially decoupled from the synoptic flow aloft. This thesis aims to improve the understanding of the wind resource in highly complex terrain, and thereby contribute to a well informed energy transition in Switzerland. We start out by investigating the characteristics of the Swiss wind resource based on data from two meteorological measurement networks. From the pair-wise correlation between stations, it is concluded that wind farms across the country can be combined to produce a stable power output. It is also shown that elevation plays an important role in the wind resource, with the likelihood of sustained low wind speeds decreasing as a function of elevation, while mean speeds tend to increase with elevation. Next, a state of the art Numerical Weather Prediction model is assessed in its ability to simulate wind speeds over the Alps, and is shown to improve drastically upon existing mean wind speed estimates. This same model is then used to calculate the wind turbine capacity that is required to produce significant amounts of wind power, and it is found that the required capacity can be significantly reduced by allowing for wind turbines to be built at high elevations. In the last part of this thesis, smaller areas of the Alpine domain are simulated at high resolu- tions, to investigate the effect of increased model resolution on the accuracy and height of resource assessments. While it is found that optimal model parameterization is dependent on weather and terrain, strong indications of higher wind power potential are found with high resolution models compared to a model at lower resolution. This is explained by the fact that high resolutions are required to properly resolve the complex topography, which has a significant influence on the flow patterns and therefore, on the potential energy production.

EPFL2019

Effects of wind direction and wind farm layout on turbine wakes and power losses in wind farms: An LES study

Fernando Porté Agel, Yu-Ting Wu

A recently-developed large-eddy simulation (LES) framework is validated and used to investigate the effects of wind direction and wind farm layout on the turbine wakes and power losses in wind farms. The subgrid-scale (SGS) turbulent stress is parameterized using a tuning-free Lagrangian scale-dependent dynamic SGS model. The turbine-induced forces are computed using a dynamic actuator-disk model with rotation (ADM-R), which couples blade-element theory with a turbine-specific relation between the blade angular velocity and the shaft torque to compute simultaneously turbine angular velocity and power output. Here, we choose the Horns Rev offshore wind farm as a case study for model validation. A series of simulations are performed for a wide range of wind direction angles. Results from the simulations are in good agreement with observed power data from the Horns Rev wind farm, and show a strong impact of wind direction on the farm power production and the spatial distribution of turbine-wake characteristics (e.g., velocity deficit and turbulence intensity). This can be explained by the fact that changing the wind angle can be viewed as changing the wind farm layout relative to the incoming wind, while keeping the same wind turbine density. To further investigate the effect of wind farm layout on the flow and the power extracted by the farm, simulations of wind farms with different circular and elliptic layouts are performed to compare with the results of the Horns Rev wind farm simulations. The results show that the proposed layouts not only provide more stable power output with different wind directions, but also enhance the performance of the total farm power production.

2014

Wind Tunnel Experiments and Modelling of Particle-Laden Boundary Layer Flows

Michael Lehning, Benjamin Andreas Walter

Particle-laden boundary flows occur in many geophysical and industrial environments yet are difficult to understand and quantitatively describe because the interactions of an often turbulent boundary layer flow with surface and particle dynamics are complex. The SLF wind tunnel allows the investigation of snow and sand particle laden boundary layer flows over their natural surfaces with and without the presence of a grass canopy.The experimental results are used to investigate the two possible approaches in describing the surface dynamics: (i) Models of particle transport, which assume a stationary flow situation and predict a mass flux for an hypothetical equilibrium; (ii) Models that take the temporal variability of the mass flux explicitly into account such as Lagrangian Stochastic particle tracking Models (LSM) on the basis of large eddy simulation (LES) or direct numerical simulation (DNS) of flow and turbulence. This presentation shows that wind tunnel data support the form of semi-empirical equilibrium models, which predict mass flux, q, as a function of the mean wind speed or the friction velocity, u, and a threshold velocity, uth: q=a(u-uth)x. For the exponent "x", a value of approximately 3, as based on theoretical considerations, is consistent with the data. This simple form of equilibrium models as well as more complicated equilibrium models are all based on the hypothesis that the surface shear stress induced by a fluid on the ground during sediment saltation is constant, i.e. independent of the magnitude of the particle mass flux (Owen's second hypothesis). Our surface shear stress measurements in a drifting-sand wind tunnel show a constant value of the fluid shear stress for saltation layers of various mass-flux magnitudes, directly validating Owen’s second hypothesis for the first time. The equilibrium models, however, only insufficiently describe the full dynamics of particle-laden flows. The second part of the presentation therefore discusses non-equilibrium features such as a high variability of the particle mass flux caused by flow turbulence and surface heterogeneity. Mass flux intermittency is primarily observed around the threshold value uth. Using a combination of LES and LSM models, we show how the simulation of individual feed-back processes leads to a more complete understanding of the mechanisms behind the flux variability.