Potential and uncertainty of wind energy in the Swiss Alps

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.


Directeur(s):
Lehning, Michael
Année
2019
Publisher:
Lausanne, EPFL
Mots-clefs:
Laboratoires:
CRYOS




 Notice créée le 2019-03-13, modifiée le 2019-10-04

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