17:00 - 18:30 Annual energy production: improved estimates through advanced modelling
Resource assessment
![Onshore Onshore](onshore-neg.png)
![Offshore Offshore](offshore-neg.png)
Room: Hall G2
Advanced modelling methods are now standard in wind estimating modelling of annual energy production (AEP). In this session, speakers will present round robin tests of models for spatial variability of wind resource on projects using different modelling approaches. We will look at the consequences of including atmospheric stability in the calculation of AEP offshore and how you can measure wind profiles at heights of 100-200 metres by using LIDARs with emphasis on charactering extreme shear situations such as low-level jets causing extreme loads. Finally, we will hear about the variability of turbulence intensities measured offshore.
You attended this session?
Learning objectives
- Understand the different methods for modelling the spatial variability of wind resource at the project scale and the errors based on the different modelling approaches;
- How to incorporate stability in the AEP modelling in offshore wind farms;
- Understand the effect of using high resolution modelled wind climatologies combined with advanced boundary modelling on the estimation of the tall winds at 100-200 metres;
- How to characterise and define the extreme events such as low-level jets that can cause fatigue loads in a wind farm;
- Understand the variability of the turbulence intensities offshore measured from multiple measurement towers.
![](../submit-an-abstract/thumb/ADMIN_41Jorgensen,_Hans_E_-_Photo_-_2015.jpg)
Presenter
![](../submit-an-abstract/thumb/414_1955726473.jpeg)
Co-authors:
Manuela Barth (2) F P Christian Bernhofer (2) Johann-Dirk Hessel (1) Andreas Walter (1) Astrid Ziemann (2)
(1) Deutscher Wetterdienst, Offenbach, Germany (2) Technische Universitaet, Dresden, Germany
Presenter's biography
Biographies are supplied directly by presenters at WindEurope Summit 2016 and are published here uneditedTina Leiding studied meteorology at the Leibniz University of Hannover, Germany, and received her diploma in 2008. Afterwards, she worked at the Department of Meteorology and Geophysics in Vienna, Austria, as a Research and Teaching Assistant. Since July 2013, she is with the Germany's National Meteorological Service, Deutscher Wetterdienst (DWD). Her research interests include atmospheric boundary layer, microscale and mesoscale modeling and wind energy yields.
Abstract
A concept for modelling a quantitative wind climatology for wind energy applications at heights above 100 m
Introduction
To optimize wind energy yields, average hub height of modern wind turbines has increased to heights of over 100 m. Consequently, rotor diameters increase as well. Beside the rise in capacity a secondary effect of higher wind turbine towers is that areas with increased surface roughness become assessable for wind energy use. In forested areas, for example, only a small part of suitable sites in Germany is used for wind energy applications so far.
Approach
Present wind atlases and simply extrapolation methods, such as logarithmic wind profile, are not applicable for hub heights of 100 m and above nor for conditions of complex terrain and inhomogeneous vegetation cover in the surrounding of installation sites. Instead, for such locations daily and seasonal influences with regard to the wind field have to be investigated. One important phenomenon, which has to be taken into consideration, is associated with a nocturnal wind maximum in the atmospheric boundary layer, which is called low level jet (LLJ). This phenomenon is observed in 10-20% of all nights in northern Germany and contributes significantly to the average wind speed in hub heights of 100 m and above.
Currently, there is a lack of wind climatologies for heights above 100 m for different surface types, which are provided to potential users in a quality-assured form. The project QuWind100 will close this gap by establishing a climatological wind data base for Germany with high horizontal resolution (100 m x 100 m) for hub heights between 100 and 200 m.
Main body of abstract
To fulfill this task an innovative model chain will be introduced, which is composed of the mesoscale 3-dimensional weather model in climate mode (COSMO CLM), operated by DWD, and the microscale instationary 2-dimensional boundary layer model HIRVAC2D (High Resolution Vegetation Atmosphere Coupler), operated by TUD. A special characteristic of the latter is its capability of simulating flows over surface inhomogeneities including adjustable vertical profiles of different vegetation types.
Modell calculations will be performed for three climate periods (past, current state, and future) including appropriate land use and climate forcing scenarios. In doing so, daily and seasonal influences on the wind field in heights between 100 m and 200 m are derived depending on possible changes in climate and land use.
We will present the model concept as well as first simulation results with respect to the influence of different types of land use on the flow field in heights between 100 to 200 m above ground. Thereby, particular attention is paid to the characteristic of nocturnal low level jets and their influence on wind energy applications.
Conclusion
The project QuWind100 will provide a model chain composed of the 3D COSMO CLM model and the HIRVAC2D. Special characteristics of the model are: the high horizontal and vertical resolution, integration of current and future land use with focus on forest regions, potential impact of climate change on the wind field, and influences of daily and seasonal variability on statistic parameters of the wind field above heights of 100 m.
Learning objectives
A model chain for generation of horizontally highly resolved wind climatologies in Germany in heights between 100 m and 200 m is introduced which consists of a mesoscale weather model in climate mode and a microscale instationary boundary layer model. First simulation results are shown. Special regard is paid to low level jets, a phenomenon of local wind speed maxima in the nocturnal atmospheric boundary layer.
Follow EWEA on: