About

Log in?

DTU users get better search results including licensed content and discounts on order fees.

Anyone can log in and get personalized features such as favorites, tags and feeds.

Log in as DTU user Log in as non-DTU user No thanks

DTU Findit

Printed book · Report

Report on the use of stability parameters and mesoscale modelling in short-term prediction

From

Meteorology, Wind Energy Division, Risø National Laboratory for Sustainable Energy, Technical University of Denmark1

Wind Energy Division, Risø National Laboratory for Sustainable Energy, Technical University of Denmark2

Risø National Laboratory for Sustainable Energy, Technical University of Denmark3

In this report investigations using atmospheric stability measures to improve wind speed predictions at wind farm sites are described. Various stability measures have been calculated based on numerical weather prediction model output. Their ability to improve the wind speed predictions is assessed at three locations.

One of the locations is in complex terrain. Mesoscale modelling has been carried out using KAMM at this location. The characteristics of the measured winds are captured well by the mesoscale modelling. It can be seen that the atmospheric stability plays an important role in determining how the flow is influence by the terrain.

A prediction system employing a look-up table approach based on wind class simulations is presented. The mesoscale modelling results produced by KAMM were validated using an alternative mesoscale model called WRF. A good agreement in the results of KAMM and WRF was found. It is shown that including a stability parameter in physical and/or statistical modelling can improve the wind speed predictions at a wind farm site.

A concept for the inclusion of a stability measure in the WPPT prediction system is presented, and the testing of the concept is outlined.

Language: English
Publisher: Risø National Laboratory
Year: 2007
Pages: 36 s.
Series: Denmark. Forskningscenter Risoe. Risoe-r
ISBN: 8755036155 and 9788755036154
ISSN: 01062840
Types: Printed book and Report
ORCIDs: Badger, Jake , Giebel, Gregor and Larsén, Xiaoli Guo

DTU users get better search results including licensed content and discounts on order fees.

Log in as DTU user

Access

Analysis